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107 Commits

Author SHA1 Message Date
matlabbe
fe896260c5 commonFiltering(): warn when normals could not be computed (returned all NaNs) 2021-05-16 11:58:17 -04:00
matlabbe
56bc15d7cd MainWindow: fixed bg color not shown on loop closures when only scans are used. 2021-05-16 11:15:05 -04:00
matlabbe
e9d7fcd7ae Vtk9 support (#722)
* Fixed build with VTK9

* Fixed VTK9 build with OctoMap dependency (vtkRenderingVolumeOpenGL2 missing)
2021-05-15 19:43:47 -04:00
matlabbe
8c336e1e39 Voxel filter: added support for very large clouds. Gui/Export: added footprint filtering option. Moved all filtering options under Cloud Filtering group. 2021-05-14 21:02:09 -04:00
matlabbe
4390cb6428 calibration tool: added RealSense2 T265 support 2021-05-12 18:31:41 -04:00
matlabbe
20c2e8b5be Docker: updated libpointmatcher version in bionic/focal images (https://github.com/introlab/rtabmap/issues/720) 2021-05-12 14:01:26 -04:00
matlabbe
ad8b2301d8 Docker/focal: fixed alicevision patch corrupted (no newline) 2021-05-12 11:27:26 -04:00
matlabbe
d75f9524f3 Export: added --texture_depth_error option 2021-05-12 10:56:16 -04:00
matlabbe
aedc70218b Docker: added AliceVision dependency to focal image 2021-05-12 10:38:37 -04:00
matlabbe
a11492943a Export CLI: added print info for coloring mesh step 2021-05-10 15:19:48 -04:00
matlabbe
854a52c6a5 Export CLI: added noise_radius and noise_k options to filter noise 2021-05-10 14:45:35 -04:00
chameau5050
b4f11e18f3 add flood fill filter (#714)
* add flood fill filter

* change to use unordoned_multiset

Co-authored-by: MarcLeclercGit <marcantoine.leclerc96@gmail.com>
2021-05-07 17:05:01 -04:00
matlabbe
6449302318 appveyor: added opencv 4.5.0 binaries with opencv_contrib 2021-05-02 21:41:48 -04:00
matlabbe
3623ede989 Update .appveyor.yml 2021-05-02 20:37:45 -04:00
matlabbe
0e051a16a0 Update .appveyor.yml 2021-05-02 20:00:16 -04:00
matlabbe
c88e3d0a8b Update .appveyor.yml 2021-05-02 19:55:57 -04:00
matlabbe
ff956a725e Fixed "localization won't be corrected with gravity" warning in localization mode and imu data are not used (while Optimizer/GravitySigma>0) 2021-05-02 19:42:59 -04:00
matlabbe
40ab98a814 docker-focal: cleanup downloaded k4a binaries 2021-05-02 13:30:57 -04:00
matlabbe
f02efb5836 docker-focal: added libfreenect2, k4a, realsense2, zed open capture support (#673) 2021-05-02 13:17:53 -04:00
matlabbe
0764999f22 Fixed focal docker image with gtsam (#673) 2021-05-02 11:59:36 -04:00
matlabbe
7515556444 Update LICENSE 2021-04-23 20:42:39 -04:00
matlabbe
3b7c6cd1f4 DBViewer: added camera projection on scan option (GUI params). Fixed some deprecated warnings. 2021-04-19 18:14:20 -04:00
matlabbe
93bfad626e Update .travis.yml
Removed deprecated trusty build from travis (https://travis-ci.org/github/introlab/rtabmap/jobs/766950721)
2021-04-14 13:12:31 -04:00
matlabbe
2fcef88016 Export: added --poses_format option (default 10=RGBD-SLAM format). Added new pose format 11=RGBD-SLAM + ID. 2021-04-13 15:49:04 -04:00
matlabbe
f4207979ad Export: fixed calibration not exported if camera name is not set. For multi-camera, added index suffix to yaml. 2021-04-09 16:20:08 -04:00
matlabbe
b92f55be43 Export tool: added multi-camera support when exporting camera poses 2021-04-08 10:23:38 -04:00
matlabbe
a8f0abf892 MainWindow::processOdometry() rectify images if Rtabmap/ImagesAlreadyRectified is false. 2021-04-02 19:06:03 -04:00
matlabbe
54267b1b33 Preferences: fixed backward compatibility error "Conversion failed from true for parameter Icp/Strategy" when loading old database with Icp/PM 2021-03-31 12:02:56 -04:00
matlabbe
4c1e72d82e Added OpenVINS minimal support (tested with EuRoC dataset) 2021-03-28 23:51:02 -04:00
matlabbe
a58ec494d1 icpCC: when force3DoF is true, set z to 0 in data conversion 2021-03-28 09:28:55 -04:00
matlabbe
69735b6271 Added removeNaNFromPointCloud for PCLPointCloud2 type 2021-03-28 00:15:47 -04:00
matlabbe
d002711f21 reprocess tool: Updated usage description to upgrade db version 2021-03-27 16:21:52 -04:00
matlabbe
06e85e140c Refactored RegistrationIcp: libpointmatcher yaml config usage / integrated CCCoreLib (#704)
* Refactored RegistrationIcp so that libpointmatcher yaml can work with icp odometry (we can then avoid refiltering data with local map of F2M). All data filtering (including libpointmatcher DataFilters) are done at the beginning of the function.

* ICP: Restored ref and data scans order for libpointmatcher (seems more stable this way).

* Fixed compilation error without libpointmatcher

* CCCoreLib integration (Icp/Strategy=2). Icp/PMForce4DoF is now Icp/Force4DoF. Icp/PM is now Icp/Strategy. Icp/PMOutlierRatio is now Icp/OutlierRatio.

* Fixed build without CCCoreLib

* Cleanup RegistrationIcp from third party functions.

* Preferences: disable libpointmatcher and cccorlib options if not available
2021-03-27 15:11:20 -04:00
matlabbe
c4d127cae4 Export: added more options for pose format and image file name. 2021-03-21 19:05:24 -04:00
matlabbe
21737f9937 Added description fo RGBD/Enabled parameter 2021-03-17 23:58:12 -04:00
matlabbe
ccc519ec58 Export: added --output name option. 2021-03-13 20:58:10 -05:00
matlabbe
1e4b172a7d Export: added poisson polygon size option 2021-03-13 19:01:09 -05:00
matlabbe
752509fb15 Rtabmap::detectMoreLoopClosures: added clusterRadiusMin parameter and update optimized poses after each accepted loop closure (also in MainWindow) like in DbViewer. Added graph::computeMinMax(poses). OdometryInfo: added guess transform. Export: added min/max axis ranges to filter nodes before expoting clouds. 2021-03-13 18:42:13 -05:00
matlabbe
f6e17be2b4 Added ViewPlane XY, XZ and YZ options to GraphViewer
Parameter RGBD/SavedLocalizationIgnored now called RGBD/StartAtOrigin (updated description, used only in localization mode)
IcpReg: if Force4DoF, set lower covariance values for roll and pitch
DbViewer: updated detectMoreLoopClosures with new minRadius option and update optimized poses between each new accepted loop closures.
MainWindow: suppressed warning if depth image is not found in current node data (when rgb is).
3D Map view: changed default map point size to 1 (was 2)
2021-03-12 17:47:36 -05:00
matlabbe
da2e2f810c Updated images 2021-03-09 17:48:40 -05:00
matlabbe
5b44c557b3 Update README.md 2021-03-09 17:44:39 -05:00
matlabbe
600d68932d updated images 2021-03-09 17:43:27 -05:00
matlabbe
800d087b07 Added archive directory to put paper related scripts 2021-03-09 17:08:42 -05:00
matlabbe
db43479e44 Added ORB_SLAM3 support. IMU Filter: added base frame conversion option. (#698)
Referred issues:
#655
https://github.com/introlab/rtabmap_ros/issues/492

Note: IMU not supported yet with ORB_SLAM3.

Commits:
* Added orbslam3 support. UI-Source->IMU filtering: Added base frame conversion option of IMU data to uniformize yaw initialization. Madgwick: fixed yaw initialization accordingly to Z acc.

* fixed regression build error with ORB_SLAM2

* Renamed OdometryORBSLAM2 to OdometryORBSLAM (can be 2 or 3 now)
2021-03-09 16:00:41 -05:00
matlabbe
736c8aceae Export tool: show an error if file doesn't exist 2021-03-09 14:06:33 -05:00
matlabbe
351c659beb Integrated DepthAI (gen2) (#696)
* Added OAK-D camera support (DepthAI)

* Fixed build without DepthAI dependency

* Added minimum version 2 for depthai

* fixed trusty build
2021-03-07 12:27:21 -05:00
matlabbe
ab8f0e2b34 Fixed #695 (footprint not cleared correctly when GridGlobal/OccupancyThr>0) 2021-03-05 18:35:49 -05:00
matlabbe
4f46d8e904 Updated some RGBD/Proximity**** parameter descriptions. Added parameter RGBD/LoopClosureIdentityGuess. Fixed local map cleared in localization when RGBD/SavedLocalizationIgnored is true (should then assume it is starting from origin). 2021-03-04 11:26:35 -05:00
matlabbe
98c69c4578 Fixed Force4DoF param not used exception on older libpointmatcher versions 2021-03-02 17:27:25 -05:00
matlabbe
4e4207a6dd CMake: updated to support latest g2oConfig.cmake (using targets) 2021-03-02 18:17:09 +00:00
matlabbe
ea4cc7cb6c Refactored how IMU is used in odometry (if guess is not set, use imu orientation for guess). Changed canProcessIMU() to canProcessAsynIMU() to make it more clear for odometry approaches able to process IMU between image frames (VIO approaches). ZedOC: fixed device closed if imu is not detected. 2021-03-01 19:27:24 -05:00
matlabbe
f7bc47572b Parameters: Icp/VoxelSize default updated from 0 to 0.05 2021-03-01 11:22:40 -05:00
matlabbe
d119487dd7 Coloring scan (camera projection on point cloud) (#693)
* ExportClouds: Added camera projection options

* ExportClouds: fixed ceiling/floor filtering options not saved in config

* ExportClouds: fixed colorless scan points still exported when option is unchecked.

* Export tool: added --bin, --poses, --images, --las and --cam_projection options; export with intensity with --scan option. PDALWriter: added binary option (only used for PLY an PCD formats). Rtabmap: Do graph optimization if neighbor link refined and Mem/UseOdomGravity is used.
2021-03-01 09:56:37 -05:00
matlabbe
967c57d165 Added CameraStereoZedOC (Zed Open Capture driver).
* Added CameraStereoZedOC (Zed Open Capture driver). Calibration: added stereo baseline option, show warning if fx is very different after stereo calibration.

* Fixed build without Zed Open Capture. Fixed "any" prefix added to all tools when WITH_ZEDOC=ON. UI: fixed Zed Open Capture action not disabled when not built with it.
2021-02-28 10:31:18 -05:00
matlabbe
862eb0a90a CameraStereoVideo: added resolution options for usb camera 2021-02-25 22:22:44 -05:00
matlabbe
cad184e82b Added Icp/PMForce4DoF parameter (works only with libpointmatcher > April 2020). Fixed some deprecated warnings. 2021-02-24 09:43:22 -05:00
matlabbe
d61e463595 Updated About dialog with opencv license 2021-02-21 13:59:36 -05:00
matlabbe
5cdb346a35 Updated opencv license to Apache2 when version >= 4.5 2021-02-21 13:03:19 -05:00
matlabbe
8696a38343 Added parameter GridGlobal/AltitudeDelta 2021-02-21 13:00:16 -05:00
matlabbe
e59aad03ed Fixed android build with latest laserScanFromPointCloud changes 2021-02-19 14:25:34 +00:00
matlabbe
9bf12742b1 fixed #688 2021-02-18 21:04:00 -05:00
matlabbe
bb7e9edb9b Fixed create2DMap assert on 32FC2 when subscribing 2D scans with intensity. LaserScan: fixed assert when angle_min > angle_max (with angle_increment < 0) 2021-02-16 10:47:31 -05:00
matlabbe
f871e4359d Fixed optimized map cleared when optimized graph is smaller than WM (poses should still refer to nodes in WM). Removed warning about max scan points smaller than actual scan (this can happen when assembling scans for proximity detection). Lowering default Icp/PMOutlierRatio to 0.85. 2021-02-12 18:40:40 -05:00
matlabbe
03cfaf2063 DBViewer: Added option to export odometry poses 2021-02-12 11:22:02 -05:00
matlabbe
089441a496 Fixed loadScan return 2D cloud for organized PCD 2021-02-10 21:35:09 -05:00
matlabbe
481a140f84 util3d: Refactored laserScanFromPointCloud() functions to return LaserScan with correct format instead of cv::Mat. 2021-02-07 17:27:55 -05:00
matlabbe
c42a4e3d7e Fixed assert when loading database having optimized poses different from the working memory (force re-update graph in this case). 2021-02-06 15:10:18 -05:00
matlabbe
c1a22609f3 Extract images: added timestamp.jpg/.png filname options (to match RGBD-SLAM pose format). Fixed wrong calibration file when first node is an intermdediate node. Export poses: ignore intermediate nodes when output frame is camera or scan. 2021-02-02 09:36:12 -05:00
matlabbe
b759b1b4d1 DBReader: set calibrated true when only scans in db. RegIcp: added intensity matching option when complexity is low. OdomF2M: accept first key frame on low complexity if a guess is provided. DbViewer: added gravity visualization in 3D view. 2021-02-01 11:31:45 -05:00
matlabbe
6b119c1f90 Camera test view: show intensity/rgb/normals if input scans have them 2021-01-25 17:16:46 -05:00
matlabbe
7e298e1999 CameraImages: timestamp file is optional for pose format containing stamp 2021-01-25 13:21:39 -05:00
matlabbe
c9472962d7 bumpt 0.20.9 version 2021-01-24 13:48:05 -05:00
matlabbe
4d75361fe0 CameraImages: support scan only dataset. 2021-01-24 13:21:30 -05:00
matlabbe
e99c658276 fixed scan-only nodes wrongly set as intermediate nodes by default 2021-01-24 11:35:48 -05:00
matlabbe
57326214f1 Fixed texture projection when fx!=fy, cx!=w/2 or cy!=h/2 2021-01-24 10:39:36 -05:00
matlabbe
47e40ef34d MainWindow: add fake frustum when only lidar is received 2021-01-22 12:51:47 -05:00
matlabbe
aa31a900fb fixed trusty build (#682)
* fixed trusty build (g2o backward compatibility)
2021-01-20 22:54:48 -05:00
matlabbe
28e624e6b2 fixed g2o build with c++14 #681 2021-01-20 10:45:45 -05:00
matlabbe
731b073ed8 Cleanup ObjDeletionHandler not used. Zed: fixed assert "qual >= sl::DEPTH_MODE::NONE && qual < sl::DEPTH_MODE::LAST" with latest sdk. 2021-01-19 17:24:38 -05:00
matlabbe
5d777469ff CameraRealSense2: refactored for freezing/crash issues on stop 2021-01-18 14:58:33 -05:00
matlabbe
70e9dff7da L515: downscale depth image if it has been upscaled during registration, fixed depth not correctly scaled in IR mode 2021-01-18 11:33:10 -05:00
matlabbe
814a243693 Add boost link dir on Windows #678 2021-01-17 15:06:47 -05:00
matlabbe
c49785061f Added PyDetector (#677)
* Added PyDetector. Refactored PyMatcher.

* Fixed python freezing with multi-threading
2021-01-17 01:56:27 -05:00
matlabbe
0bc483b6d3 Added pdal optional dependency (export to LAS, E57, ...) 2021-01-14 15:49:18 -05:00
matlabbe
eae5f2b428 fixed #674 2021-01-11 11:38:31 -05:00
matlabbe
94cf1dfd32 Fixed zero-ed 3D words when receiving odometry's 2D keypoints > Kp/MaxFeatures and empty 3D points 2021-01-09 20:52:34 -05:00
matlabbe
1a967127d9 Bump 0.20.8 version. Parameters: updated default of Vis/CorGuessWinSize=40 (was 20), GFTT/MinDistance=7 (was 3), Optimizer/GravitySigma=0.3 if built with g2o or gtsam. Those parameters help for smooth tracking on latest sensors with higher resolution and use IMU by default if available. Updated docker jfr2018 to use original parameters. CameraStereoZed: wait for imu to be available before sending frames (Zed-m and Zed2). 2021-01-08 13:04:24 -05:00
matlabbe
792c967d46 MainWindow: added driver options to differentiate between cameras having IMU or not (D400 vs D435i, ZED vs Zedm and Zed2). Enabled imu filtering by default for Freenect driver (Kinect XBOX360). 2021-01-08 01:10:23 -05:00
matlabbe
a67dbc26f2 L515 refactoring (realsense v2.41.0, firmware 1.5.3): added IR-only mode support, fixed support with latest firmware, T265+L515 working, related to #574 #614 #629. MainWindow: Selecting RealSense2, ZED sdk, K4A, Mynteye drivers automatically enable gravity optimization (with IMU filtering). 2021-01-08 00:01:08 -05:00
matlabbe
f1993d9cd7 android: fixed z-fighting on some android devices 2021-01-02 18:14:55 -05:00
matlabbe
da99d7e4a0 disabled osx travis build (too long to do) 2020-12-20 00:07:34 -05:00
matlabbe
e896ffb5c0 Update .travis.yml 2020-12-19 23:16:28 -05:00
matlabbe
04cbf56cc0 Update .travis.yml 2020-12-19 22:37:13 -05:00
matlabbe
c5051bf82a Update .travis.yml 2020-12-19 21:38:13 -05:00
matlabbe
7a9f01b9a3 Update .travis.yml 2020-12-19 12:55:12 -05:00
matlabbe
70094edb75 Update .travis.yml 2020-12-19 12:38:36 -05:00
matlabbe
eb2af19a89 Update .travis.yml 2020-12-19 12:28:02 -05:00
matlabbe
af227bad51 Update .travis.yml 2020-12-19 12:21:25 -05:00
matlabbe
ee63ce338a Update .travis.yml 2020-12-19 12:11:19 -05:00
matlabbe
1b3a6abb82 Update .travis.yml 2020-12-19 11:48:06 -05:00
matlabbe
4a8a20c7d1 Update .travis.yml 2020-12-19 11:24:19 -05:00
matlabbe
a125797e50 Update .travis.yml
Added osx
2020-12-19 11:18:20 -05:00
matlabbe
a6f0877045 Parameters: added Rtabmap/ImagesAlreadyRectified to odometry parameters (to be shown with --params) 2020-12-18 17:57:43 -05:00
matlabbe
b5cae38eb9 Fixed -lBoost:timer not defined when building with latest GTSAM binaries 2020-12-18 17:01:11 -05:00
matlabbe
d8ebbc2645 CameraK4A: rectifying color image (this improves a lot visual odometry accuracy) 2020-12-13 15:27:17 -05:00
matlabbe
d700d09339 DataRecorder tool: interface changed to use config file (#661) 2020-12-13 12:42:58 -05:00
matlabbe
3104dff006 Update README.md 2020-12-13 11:10:22 -05:00
182 changed files with 14862 additions and 5501 deletions

View File

@@ -33,13 +33,16 @@ install:
- set OPENNI2_LIB64=C:\Program Files\OpenNI2\Lib
- set OPENNI2_REDIST64=C:\Program Files\OpenNI2\Redist
# OpenCV
#- ps: wget 'http://kent.dl.sourceforge.net/project/opencvlibrary/opencv-win/3.3.1/opencv-3.3.1-vc14.exe' -outfile opencv-3.3.1-vc14.exe
#- cmd: opencv-3.3.1-vc14.exe -o"C:\Program Files" -y
- ps: $url = "https://downloads.sourceforge.net/project/opencvlibrary/opencv-win/2.4.13/opencv-2.4.13.6-vc14.exe?r=&ts="+([int64](([datetime]::UtcNow)-(get-date "1/1/1970")).TotalSeconds) ; wget $url -outfile opencv-2.4.13.6-vc14.exe
- cmd: opencv-2.4.13.6-vc14.exe -o"C:\Program Files" -y
#- appveyor-retry appveyor DownloadFile http://downloads.sourceforge.net/project/opencvlibrary/4.5.2/opencv-4.5.2-vc14_vc15.exe
#- cmd: opencv-4.5.2-vc14_vc15.exe -o"C:\Program Files" -y
#- ECHO "Installed OpenCV:"
#- ps: "ls \"C:/Program Files/opencv/build\""
#- set PATH=%PATH%;C:\Program Files\opencv\build\x64\vc14\bin
- ps: wget 'https://dl.dropboxusercontent.com/s/o6ofn491bc0jso1/opencv450_vc14.exe?dl=0' -outfile opencv.exe
- cmd: opencv.exe -o"C:\Program Files" -y
- ECHO "Installed OpenCV:"
- ps: "ls \"C:/Program Files/opencv/build\""
- set PATH=%PATH%;C:\Program Files\opencv\build\x64\vc14\bin
- ps: "ls \"C:/Program Files/opencv\""
- set PATH=%PATH%;C:\Program Files\opencv\x64\vc14\bin
# VTK (including QVTK)
- ps: wget 'https://dl.dropboxusercontent.com/s/1l33b5l3f3y52gf/VTK-6_3-msvc140.exe?dl=0' -outfile VTK-6_3.exe
- cmd: VTK-6_3.exe -o"C:\Program Files" -y
@@ -105,12 +108,7 @@ install:
- ECHO "Installed Open Chisel:"
- ps: "ls \"C:/Program Files/open_chisel\""
- set PATH=%PATH%;C:\Program Files\open_chisel\bin
# cvsba
- ps: wget 'https://dl.dropboxusercontent.com/s/4ey8ergerx46zvj/cvsba_x64_vc14.exe?dl=0' -outfile cvsba.exe
- cmd: cvsba.exe -o"C:\Program Files" -y
- ECHO "Installed cvsba:"
- ps: "ls \"C:/Program Files/cvsba\""
- set PATH=%PATH%;C:\Program Files\cvsba\bin
# yaml-cpp
- ps: wget 'https://dl.dropboxusercontent.com/s/22qfvftwj6zq8tj/yaml-cpp_x64_vc14.exe?dl=0' -outfile yaml-cpp.exe
- cmd: yaml-cpp.exe -o"C:\Program Files" -y
- ECHO "Installed yaml-cpp:"
@@ -134,7 +132,7 @@ before_build:
- cd c:\projects\rtabmap\build
- ECHO %PROGRAMFILES%
- ECHO %PATH%
- cmake -G "Visual Studio 14 2015 Win64" -DOpenCV_DIR="C:\Program Files\opencv\build" -DPCL_DIR="C:\Program Files\PCL\cmake" -DCPUTSDF_DIR="C:\Program Files\cpu_tsdf\share\cpu_tsdf" -Dcvsba_DIR="C:\Program Files\cvsba\lib\cmake" -Dyaml-cpp_DIR="C:\Program Files\yaml-cpp\CMake" -DBUILD_AS_BUNDLE=ON ..
- cmake -G "Visual Studio 14 2015 Win64" -DOpenCV_DIR="C:\Program Files\opencv\build" -DPCL_DIR="C:\Program Files\PCL\cmake" -DCPUTSDF_DIR="C:\Program Files\cpu_tsdf\share\cpu_tsdf" -Dyaml-cpp_DIR="C:\Program Files\yaml-cpp\CMake" -DBUILD_AS_BUNDLE=ON ..
after_build :
- cmake --build . --config Release --target package

View File

@@ -1,29 +1,34 @@
sudo: true
language: cpp
group: deprecated-2017Q3
compiler:
- gcc
matrix:
jobs:
include:
# - name: osx
# compiler: clang
# os: osx
# install:
# - brew install sqlite
# - brew install pcl
# - brew install opencv@3
# - name: linux-trusty
# compiler: gcc
# os: linux
# dist: trusty
# install:
# - sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu trusty main" > /etc/apt/sources.list.d/ros-latest.list'
# - wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
# - sudo apt-get update
# - sudo apt-get update && sudo apt-get install dpkg
# - sudo apt-get -y install ros-indigo-rtabmap-ros
# - sudo apt-get -y remove ros-indigo-rtabmap
#
# before_script:
# - source /opt/ros/indigo/setup.bash
- dist: trusty
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu trusty main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
- sudo apt-get update
- sudo apt-get update && sudo apt-get install dpkg
- sudo apt-get -y install ros-indigo-rtabmap-ros
- sudo apt-get -y remove ros-indigo-rtabmap
script:
- source /opt/ros/indigo/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
- dist: xenial
- name: linux-xenial
compiler: gcc
os: linux
dist: xenial
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu xenial main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -32,13 +37,13 @@ matrix:
- sudo apt-get -y install ros-kinetic-rtabmap-ros
- sudo apt-get -y remove ros-kinetic-rtabmap
script:
before_script:
- source /opt/ros/kinetic/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
- dist: bionic
- name: linux-bionic
compiler: gcc
os: linux
dist: bionic
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu bionic main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -47,13 +52,13 @@ matrix:
- sudo apt-get -y install ros-melodic-rtabmap-ros
- sudo apt-get -y remove ros-melodic-rtabmap
script:
before_script:
- source /opt/ros/melodic/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
- dist: focal
- name: linux-focal
compiler: gcc
os: linux
dist: focal
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu focal main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -62,11 +67,13 @@ matrix:
- sudo apt-get -y install ros-noetic-rtabmap-ros
- sudo apt-get -y remove ros-noetic-rtabmap
script:
before_script:
- source /opt/ros/noetic/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
script:
- mkdir -p build && cd build
- cmake ..
- make
notifications:
email:

View File

@@ -21,7 +21,7 @@ SET(CMAKE_MODULE_PATH "${PROJECT_SOURCE_DIR}/cmake_modules")
#######################
SET(RTABMAP_MAJOR_VERSION 0)
SET(RTABMAP_MINOR_VERSION 20)
SET(RTABMAP_PATCH_VERSION 7)
SET(RTABMAP_PATCH_VERSION 10)
SET(RTABMAP_VERSION
${RTABMAP_MAJOR_VERSION}.${RTABMAP_MINOR_VERSION}.${RTABMAP_PATCH_VERSION})
@@ -163,8 +163,10 @@ ELSE()
option(WITH_QT "Include Qt support" ON)
ENDIF()
option(WITH_ORB_OCTREE "Include ORB Octree feature support" ON)
option(WITH_SUPERPOINT_TORCH "Include SuperPoint Torch feature support" ON)
option(WITH_PYMATCHER "Include Python3 matchers support" OFF)
option(WITH_TORCH "Include Torch support (SuperPoint)" OFF)
option(WITH_PYTHON "Include Python3 support (PyMatcher, PyDetector)" OFF)
option(WITH_PYTHON_THREADING "Use more than one Python interpreter." OFF)
option(WITH_PDAL "Include PDAL support" ON)
option(WITH_FREENECT "Include Freenect support" ON)
option(WITH_FREENECT2 "Include Freenect2 support" ON)
option(WITH_K4W2 "Include Kinect for Windows v2 support" ON)
@@ -178,13 +180,16 @@ option(WITH_CERES "Include Ceres support" ON)
option(WITH_VERTIGO "Include Vertigo support" ON)
option(WITH_CVSBA "Include cvsba support" ON)
option(WITH_POINTMATCHER "Include libpointmatcher support" ON)
option(WITH_CCCORELIB "Include CCCoreLib support" ON)
option(WITH_LOAM "Include LOAM support" ON)
option(WITH_FLYCAPTURE2 "Include FlyCapture2/Triclops support" ON)
option(WITH_ZED "Include ZED sdk support" ON)
option(WITH_ZEDOC "Include ZED Open Capture support" ON)
option(WITH_REALSENSE "Include RealSense support" ON)
option(WITH_REALSENSE_SLAM "Include RealSenseSlam support" ON)
option(WITH_REALSENSE2 "Include RealSense support" ON)
option(WITH_MYNTEYE "Include mynteye-s support" ON)
option(WITH_DEPTHAI "Include depthai-core support" ON)
option(WITH_OCTOMAP "Include Octomap support" ON)
option(WITH_CPUTSDF "Include CPUTSDF support" ON)
option(WITH_OPENCHISEL "Include open_chisel support" ON)
@@ -192,10 +197,11 @@ option(WITH_ALICE_VISION "Include AliceVision support" OFF)
option(WITH_FOVIS "Include FOVIS support" ON)
option(WITH_VISO2 "Include VISO2 support" ON)
option(WITH_DVO "Include DVO support" ON)
option(WITH_ORB_SLAM2 "Include ORB_SLAM2 support" ON)
option(WITH_ORB_SLAM "Include ORB_SLAM2 or ORB_SLAM3 support" ON)
option(WITH_OKVIS "Include OKVIS support" ON)
option(WITH_MSCKF_VIO "Include MSCKF_VIO support" OFF)
option(WITH_VINS "Include VINS-Fusion support" ON)
option(WITH_OPENVINS "Include OpenVINS support" ON)
option(WITH_MADGWICK "Include Madgwick IMU filtering support" ON)
option(WITH_FASTCV "Include FastCV support" ON)
IF(ANDROID)
@@ -295,11 +301,15 @@ IF(WITH_QT)
IF("${VTK_MAJOR_VERSION}" EQUAL 5)
FIND_PACKAGE(QVTK REQUIRED) # only for VTK 5
ELSE()
list(FIND PCL_LIBRARIES vtkGUISupportQt value)
IF(value EQUAL -1)
SET(PCL_LIBRARIES "${PCL_LIBRARIES};vtkGUISupportQt")
SET(ADD_VTK_GUI_SUPPORT_QT_TO_CONF TRUE)
ENDIF(value EQUAL -1)
list(FIND PCL_LIBRARIES VTK::GUISupportQt value)
IF(value EQUAL -1)
list(FIND PCL_LIBRARIES vtkGUISupportQt value)
IF(value EQUAL -1)
SET(PCL_LIBRARIES "${PCL_LIBRARIES};vtkGUISupportQt")
SET(ADD_VTK_GUI_SUPPORT_QT_TO_CONF TRUE)
ENDIF(value EQUAL -1)
ENDIF(value EQUAL -1)
MESSAGE(STATUS "VTK_RENDERING_BACKEND=${VTK_RENDERING_BACKEND}")
IF(VTK_RENDERING_BACKEND STREQUAL "OpenGL2")
@@ -315,6 +325,14 @@ IF(WITH_QT)
IF(value EQUAL -1)
SET(PCL_LIBRARIES "${PCL_LIBRARIES};vtkRenderingVolumeOpenGL")
ENDIF(value EQUAL -1)
ELSEIF("${VTK_MAJOR_VERSION}" EQUAL 9)
list(FIND PCL_LIBRARIES VTK::RenderingOpenGL2 value)
IF(NOT value EQUAL -1)
list(FIND PCL_LIBRARIES VTK::RenderingVolumeOpenGL2 value)
IF(value EQUAL -1)
SET(PCL_LIBRARIES "${PCL_LIBRARIES};VTK::RenderingVolumeOpenGL2")
ENDIF(value EQUAL -1)
ENDIF(NOT value EQUAL -1)
ENDIF()
ENDIF()
@@ -322,19 +340,26 @@ IF(WITH_QT)
ENDIF(QT4_FOUND OR Qt5_FOUND)
ENDIF(WITH_QT)
IF(WITH_SUPERPOINT_TORCH)
IF(WITH_TORCH)
FIND_PACKAGE(Torch QUIET)
IF(TORCH_FOUND)
MESSAGE(STATUS "Found Torch: ${TORCH_INCLUDE_DIRS}")
ENDIF(TORCH_FOUND)
ENDIF(WITH_SUPERPOINT_TORCH)
ENDIF(WITH_TORCH)
IF(WITH_PYMATCHER)
IF(WITH_PYTHON)
FIND_PACKAGE(Python3 COMPONENTS Interpreter Development)
IF(Python3_FOUND)
MESSAGE(STATUS "Found Python3")
ENDIF(Python3_FOUND)
ENDIF(WITH_PYMATCHER)
ENDIF(WITH_PYTHON)
IF(WITH_PDAL)
FIND_PACKAGE(PDAL QUIET)
IF(PDAL_FOUND)
MESSAGE(STATUS "Found PDAL ${PDAL_VERSION}: ${PDAL_INCLUDE_DIRS}")
ENDIF(PDAL_FOUND)
ENDIF(WITH_PDAL)
IF(WITH_FREENECT)
FIND_PACKAGE(Freenect QUIET)
@@ -399,10 +424,17 @@ IF(WITH_DC1394)
ENDIF(WITH_DC1394)
IF(WITH_G2O)
FIND_PACKAGE(G2O QUIET)
IF(G2O_FOUND)
MESSAGE(STATUS "Found g2o: ${G2O_INCLUDE_DIRS}")
ENDIF(G2O_FOUND)
FIND_PACKAGE(g2o QUIET NO_MODULE)
IF(g2o_FOUND)
MESSAGE(STATUS "Found g2o (targets)")
SET(G2O_FOUND ${g2o_FOUND})
SET(G2O_CPP11 1)
ELSE()
FIND_PACKAGE(G2O QUIET)
IF(G2O_FOUND)
MESSAGE(STATUS "Found g2o: ${G2O_INCLUDE_DIRS}")
ENDIF(G2O_FOUND)
ENDIF()
ENDIF(WITH_G2O)
IF(WITH_GTSAM)
@@ -427,14 +459,28 @@ ENDIF(WITH_CVSBA)
IF(WITH_POINTMATCHER)
find_package(libpointmatcher QUIET)
IF(libpointmatcher_FOUND)
find_package(Boost COMPONENTS thread filesystem system program_options date_time REQUIRED)
if (Boost_MINOR_VERSION GREATER 47)
find_package(Boost COMPONENTS thread filesystem system program_options date_time chrono timer REQUIRED)
endif (Boost_MINOR_VERSION GREATER 47)
MESSAGE(STATUS "Found libpointmatcher: ${libpointmatcher_INCLUDE_DIRS}")
ENDIF(libpointmatcher_FOUND)
ENDIF(WITH_POINTMATCHER)
IF(libpointmatcher_FOUND OR GTSAM_FOUND)
find_package(Boost COMPONENTS thread filesystem system program_options date_time REQUIRED)
IF(Boost_MINOR_VERSION GREATER 47)
find_package(Boost COMPONENTS thread filesystem system program_options date_time chrono timer REQUIRED)
ENDIF(Boost_MINOR_VERSION GREATER 47)
IF(WIN32)
MESSAGE(STATUS "Boost_LIBRARY_DIRS=${Boost_LIBRARY_DIRS}")
link_directories(${Boost_LIBRARY_DIRS})
ENDIF(WIN32)
ENDIF(libpointmatcher_FOUND OR GTSAM_FOUND)
IF(WITH_CCCORELIB)
find_package(CCCoreLib QUIET)
IF(CCCoreLib_FOUND)
MESSAGE(STATUS "Found CCCoreLib: ${CCCoreLib_INCLUDE_DIRS}")
ENDIF(CCCoreLib_FOUND)
ENDIF(WITH_CCCORELIB)
IF(WITH_LOAM)
find_package(loam_velodyne QUIET)
IF(loam_velodyne_FOUND)
@@ -458,6 +504,20 @@ IF(WITH_ZED)
ENDIF(ZED_FOUND)
ENDIF(WITH_ZED)
IF(WITH_ZEDOC)
find_package(ZEDOC QUIET)
IF(ZEDOC_FOUND)
MESSAGE(STATUS "Found ZED Open Capture: ${ZEDOC_INCLUDE_DIRS}")
## look for HIDAPI
find_package(HIDAPI)
IF(HIDAPI_FOUND)
MESSAGE(STATUS "Found HIDAPI: ${HIDAPI_INCLUDE_DIRS}")
ELSE()
MESSAGE(FATAL_ERROR "HIDAPI is required to build with Zed Open Capture! Set -DWITH_ZEDOC=OFF if you don't have HIDAPI.")
ENDIF()
ENDIF(ZEDOC_FOUND)
ENDIF(WITH_ZEDOC)
IF(WITH_REALSENSE)
IF(WITH_REALSENSE_SLAM)
FIND_PACKAGE(RealSense QUIET COMPONENTS slam)
@@ -490,6 +550,13 @@ IF(WITH_MYNTEYE)
ENDIF(mynteye_FOUND)
ENDIF(WITH_MYNTEYE)
IF(WITH_DEPTHAI)
FIND_PACKAGE(depthai 2 QUIET)
IF(depthai_FOUND)
MESSAGE(STATUS "Found depthai-core (targets)")
ENDIF(depthai_FOUND)
ENDIF(WITH_DEPTHAI)
IF(WITH_OCTOMAP)
FIND_PACKAGE(octomap QUIET)
IF(octomap_FOUND)
@@ -517,6 +584,9 @@ ENDIF(WITH_OPENCHISEL)
IF(WITH_ALICE_VISION)
find_package(AliceVision CONFIG QUIET)
IF(AliceVision_FOUND)
IF(${AliceVision_VERSION} VERSION_LESS_EQUAL "2.2")
find_package(Boost COMPONENTS log log_setup container REQUIRED)
ENDIF(${AliceVision_VERSION} VERSION_LESS_EQUAL "2.2")
SET(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH};/usr/local/lib/cmake/modules")
find_package(Geogram REQUIRED QUIET)
add_definitions("-DRTABMAP_ALICE_VISION_MAJOR=${AliceVision_VERSION_MAJOR}")
@@ -581,6 +651,13 @@ IF(WITH_VINS)
ENDIF(vins_FOUND)
ENDIF(WITH_VINS)
IF(WITH_OPENVINS)
FIND_PACKAGE(ov_msckf QUIET)
IF(ov_msckf_FOUND)
MESSAGE(STATUS "Found ov_msckf: ${ov_msckf_INCLUDE_DIRS}")
ENDIF(ov_msckf_FOUND)
ENDIF(WITH_OPENVINS)
IF(WITH_FASTCV)
FIND_PACKAGE(FastCV QUIET)
IF(FastCV_FOUND)
@@ -588,59 +665,54 @@ IF(WITH_FASTCV)
ENDIF(FastCV_FOUND)
ENDIF(WITH_FASTCV)
IF(WITH_ORB_SLAM2 AND NOT G2O_FOUND)
FIND_PACKAGE(ORB_SLAM2 QUIET)
IF(ORB_SLAM2_FOUND)
MESSAGE(STATUS "Found ORB_SLAM2: ${ORB_SLAM2_INCLUDE_DIRS}")
FIND_PACKAGE(Pangolin QUIET)
IF(NOT Pangolin_FOUND)
SET(ORB_SLAM2_FOUND FALSE)
MESSAGE(STATUS "Found ORB_SLAM2 but not Pangolin, disabling ORB_SLAM2.")
ELSE()
MESSAGE(STATUS "Found Pangolin: ${Pangolin_INCLUDE_DIRS}")
SET(ORB_SLAM2_INCLUDE_DIRS ${ORB_SLAM2_INCLUDE_DIRS} ${Pangolin_INCLUDE_DIRS})
SET(ORB_SLAM2_LIBRARIES ${ORB_SLAM2_LIBRARIES} ${Pangolin_LIBRARIES})
ENDIF()
ENDIF(ORB_SLAM2_FOUND)
ENDIF(WITH_ORB_SLAM2 AND NOT G2O_FOUND)
IF(WITH_ORB_SLAM AND NOT G2O_FOUND)
FIND_PACKAGE(ORB_SLAM QUIET)
IF(ORB_SLAM_FOUND)
MESSAGE(STATUS "Found ORB_SLAM${ORB_SLAM_VERSION}: ${ORB_SLAM_INCLUDE_DIRS}")
ENDIF(ORB_SLAM_FOUND)
ENDIF(WITH_ORB_SLAM AND NOT G2O_FOUND)
IF(loam_velodyne_FOUND OR PCL_VERSION VERSION_GREATER "1.9.1" OR TORCH_FOUND)
#LOAM and PCL>=1.10 require c++14
IF(NOT MSVC)
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++14" COMPILER_SUPPORTS_CXX14)
IF(COMPILER_SUPPORTS_CXX14)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14")
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++14 support. Please use a different C++ compiler if you want to use LOAM (set \"-DWITH_LOAM=OFF\" to build without LOAM).")
ENDIF()
ENDIF()
ELSEIF(G2O_FOUND OR
GTSAM_FOUND OR
CERES_FOUND OR
ZED_FOUND OR
ANDROID OR
RealSense_FOUND OR
realsense2_FOUND OR
ORB_SLAM2_FOUND OR
okvis_FOUND OR
open_chisel_FOUND OR
msckf_vio_FOUND OR
vins_FOUND OR
libpointmatcher_FOUND)
#Newest versions require std11
IF(NOT MSVC)
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORTS_CXX11)
CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORTS_CXX0X)
IF(COMPILER_SUPPORTS_CXX11)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
ELSEIF(COMPILER_SUPPORTS_CXX0X)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++11 support. Please use a different C++ compiler.")
ENDIF()
ENDIF()
IF(NOT MSVC)
IF(loam_velodyne_FOUND OR PCL_VERSION VERSION_GREATER "1.9.1" OR TORCH_FOUND OR G2O_FOUND OR CCCoreLib_FOUND)
#LOAM, PCL>=1.10, latest g2o and CCCoreLib require c++14
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++14" COMPILER_SUPPORTS_CXX14)
IF(COMPILER_SUPPORTS_CXX14)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14")
set(CMAKE_CXX_STANDARD 14)
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++14 support. Please use a different C++ compiler if you want to use LOAM, latest PCL or g2o.")
ENDIF()
ENDIF(loam_velodyne_FOUND OR PCL_VERSION VERSION_GREATER "1.9.1" OR TORCH_FOUND OR G2O_FOUND OR CCCoreLib_FOUND)
IF( (NOT (${CMAKE_CXX_STANDARD} STREQUAL "14")) AND (
G2O_FOUND OR
GTSAM_FOUND OR
CERES_FOUND OR
ZED_FOUND OR
ZEDOC_FOUND OR
ANDROID OR
RealSense_FOUND OR
realsense2_FOUND OR
ORB_SLAM_FOUND OR
okvis_FOUND OR
open_chisel_FOUND OR
msckf_vio_FOUND OR
vins_FOUND OR
ov_msckf_FOUND OR
libpointmatcher_FOUND))
#Newest versions require std11
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORTS_CXX11)
CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORTS_CXX0X)
IF(COMPILER_SUPPORTS_CXX11)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
ELSEIF(COMPILER_SUPPORTS_CXX0X)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++11 support. Please use a different C++ compiler.")
ENDIF()
ENDIF()
ENDIF()
####### OSX BUNDLE CMAKE_INSTALL_PREFIX #######
@@ -724,9 +796,15 @@ ENDIF()
IF(NOT libpointmatcher_FOUND)
SET(POINTMATCHER "//")
ENDIF(NOT libpointmatcher_FOUND)
IF(NOT CCCoreLib_FOUND)
SET(CCCORELIB "//")
ENDIF(NOT CCCoreLib_FOUND)
IF(NOT FastCV_FOUND)
SET(FASTCV "//")
ENDIF(NOT FastCV_FOUND)
IF(NOT PDAL_FOUND)
SET(PDAL "//")
ENDIF(NOT PDAL_FOUND)
IF(NOT loam_velodyne_FOUND)
SET(LOAM "//")
ENDIF(NOT loam_velodyne_FOUND)
@@ -770,6 +848,11 @@ IF(NOT ZED_FOUND)
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ZED_LIBRARIES} ${CUDA_LIBRARIES})
ENDIF()
IF(NOT ZEDOC_FOUND)
SET(ZEDOC "//")
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ZEDOC_LIBRARIES})
ENDIF()
IF(NOT RealSense_FOUND)
SET(REALSENSE "//")
ELSE()
@@ -786,6 +869,9 @@ ENDIF()
IF(NOT mynteye_FOUND)
SET(MYNTEYE "//")
ENDIF(NOT mynteye_FOUND)
IF(NOT depthai_FOUND)
SET(DEPTHAI "//")
ENDIF(NOT depthai_FOUND)
IF(NOT octomap_FOUND)
SET(OCTOMAP "//")
ELSE()
@@ -834,19 +920,24 @@ IF(NOT vins_FOUND)
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${vins_LIBRARIES})
ENDIF()
IF(NOT ORB_SLAM2_FOUND)
SET(ORB_SLAM2 "//")
IF(NOT ov_msckf_FOUND)
SET(OPENVINS "//")
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ORB_SLAM2_LIBRARIES})
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ov_msckf_LIBRARIES})
ENDIF()
IF(NOT ORB_SLAM_FOUND)
SET(ORB_SLAM "//")
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ORB_SLAM_LIBRARIES})
ENDIF()
IF(NOT WITH_ORB_OCTREE)
SET(ORB_OCTREE "//")
ENDIF()
IF(NOT TORCH_FOUND)
SET(SUPERPOINT_TORCH "//")
SET(TORCH "//")
ENDIF()
IF(NOT Python3_FOUND)
SET(PYMATCHER "//")
SET(PYTHON "//")
ENDIF()
IF(ADD_VTK_GUI_SUPPORT_QT_TO_CONF)
SET(CONF_VTK_QT true)
@@ -1030,7 +1121,8 @@ INCLUDE(CPack)
MESSAGE(STATUS "--------------------------------------------")
MESSAGE(STATUS "Info :")
MESSAGE(STATUS " Version : ${RTABMAP_VERSION}")
MESSAGE(STATUS " RTAB-Map Version = ${RTABMAP_VERSION}")
MESSAGE(STATUS " CMAKE_VERSION = ${CMAKE_VERSION}")
MESSAGE(STATUS " CMAKE_INSTALL_PREFIX = ${CMAKE_INSTALL_PREFIX}")
MESSAGE(STATUS " CMAKE_BUILD_TYPE = ${CMAKE_BUILD_TYPE}")
MESSAGE(STATUS " CMAKE_INSTALL_LIBDIR = ${CMAKE_INSTALL_LIBDIR}")
@@ -1064,12 +1156,20 @@ IF(OpenCV_FOUND)
ELSE()
IF(OPENCV_XFEATURES2D_FOUND)
IF(NONFREE STREQUAL "//")
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = NO (License: BSD)")
IF((OpenCV_VERSION_MAJOR LESS 4) OR ((OpenCV_VERSION_MAJOR EQUAL 4) AND (OpenCV_VERSION_MINOR LESS 5)))
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = NO (License: BSD)")
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = NO (License: Apache 2)")
ENDIF()
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = YES (License: Non commercial)")
ENDIF()
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = NO, nonfree = NO (License: BSD)")
IF((OpenCV_VERSION_MAJOR LESS 4) OR ((OpenCV_VERSION_MAJOR EQUAL 4) AND (OpenCV_VERSION_MINOR LESS 5)))
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = NO, nonfree = NO (License: BSD)")
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = NO, nonfree = NO (License: Apache 2)")
ENDIF()
ENDIF()
ENDIF()
ENDIF(OpenCV_FOUND)
@@ -1101,18 +1201,18 @@ ENDIF()
IF(TORCH_FOUND)
MESSAGE(STATUS " With SupertPoint = YES (License: GPLv3) libtorch=${Torch_VERSION}")
ELSEIF(NOT WITH_SUPERPOINT_TORCH)
MESSAGE(STATUS " With SupertPoint = NO (WITH_SUPERPOINT_TORCH=OFF)")
ELSEIF(NOT WITH_TORCH)
MESSAGE(STATUS " With SupertPoint = NO (WITH_TORCH=OFF)")
ELSE()
MESSAGE(STATUS " With SupertPoint = NO (libtorch not found)")
ENDIF()
IF(Python3_FOUND)
MESSAGE(STATUS " With Python3 = YES (License: PSF)")
ELSEIF(NOT WITH_PYMATCHER)
MESSAGE(STATUS " With Python3 = NO (WITH_PYMATCHER=OFF)")
MESSAGE(STATUS " With Python${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR} = YES (License: PSF)")
ELSEIF(NOT WITH_PYTHON)
MESSAGE(STATUS " With Python3 = NO (WITH_PYTHON=OFF)")
ELSE()
MESSAGE(STATUS " With Python3 = NO (python3 not found)")
MESSAGE(STATUS " With Python3 = NO (python not found)")
ENDIF()
IF(WITH_MADGWICK)
@@ -1129,6 +1229,14 @@ ELSE()
MESSAGE(STATUS " With FastCV = NO (FastCV not found)")
ENDIF()
IF(PDAL_FOUND)
MESSAGE(STATUS " With PDAL = YES (License: BSD)")
ELSEIF(NOT WITH_PDAL)
MESSAGE(STATUS " With PDAL = NO (WITH_PDAL=OFF)")
ELSE()
MESSAGE(STATUS " With PDAL = NO (PDAL not found)")
ENDIF()
MESSAGE(STATUS "")
MESSAGE(STATUS " Solvers:")
IF(WITH_TORO)
@@ -1187,6 +1295,14 @@ ELSE()
MESSAGE(STATUS " *With libpointmatcher = NO (libpointmatcher not found)")
ENDIF()
IF(CCCoreLib_FOUND)
MESSAGE(STATUS " With CCCoreLib = YES (License: GPLv2)")
ELSEIF(NOT WITH_POINTMATCHER)
MESSAGE(STATUS " With CCCoreLib = NO (WITH_CCCORELIB=OFF)")
ELSE()
MESSAGE(STATUS " With CCCoreLib = NO (CCCoreLib not found)")
ENDIF()
MESSAGE(STATUS "")
MESSAGE(STATUS " Reconstruction Approaches:")
IF(octomap_FOUND)
@@ -1287,6 +1403,14 @@ ELSE()
MESSAGE(STATUS " With ZED = NO (ZED sdk and/or cuda not found)")
ENDIF()
IF(ZEDOC_FOUND)
MESSAGE(STATUS " With ZEDOC = YES")
ELSEIF(NOT WITH_ZEDOC)
MESSAGE(STATUS " With ZEDOC = NO (WITH_ZEDOC=OFF)")
ELSE()
MESSAGE(STATUS " With ZEDOC = NO (ZED Open Capture not found)")
ENDIF()
IF(RealSense_FOUND)
MESSAGE(STATUS " With RealSense = YES (License: Apache-2)")
IF(RealSenseSlam_FOUND)
@@ -1318,6 +1442,14 @@ ELSE()
MESSAGE(STATUS " With MyntEyeS = NO (mynteye s sdk not found)")
ENDIF()
IF(depthai_FOUND)
MESSAGE(STATUS " With DepthAI = YES (License: MIT)")
ELSEIF(NOT WITH_DEPTHAI)
MESSAGE(STATUS " With DepthAI = NO (WITH_DEPTHAI=OFF)")
ELSE()
MESSAGE(STATUS " With DepthAI = NO (depthai-core not found)")
ENDIF()
MESSAGE(STATUS "")
MESSAGE(STATUS " Odometry Approaches:")
IF(loam_velodyne_FOUND)
@@ -1376,14 +1508,22 @@ ELSE()
MESSAGE(STATUS " With VINS-Fusion = NO (VINS-Fusion not found)")
ENDIF()
IF(ORB_SLAM2_FOUND)
MESSAGE(STATUS " With ORB_SLAM2 = YES (License: GPLv3)")
ELSEIF(NOT WITH_ORB_SLAM2)
MESSAGE(STATUS " With ORB_SLAM2 = NO (WITH_ORB_SLAM2=OFF)")
ELSEIF(G2O_FOUND)
MESSAGE(STATUS " With ORB_SLAM2 = NO (WITH_G2O should be OFF as ORB_SLAM2 uses its own g2o version)")
IF(ov_msckf_FOUND)
MESSAGE(STATUS " With OpenVINS = YES (License: GPLv3)")
ELSEIF(NOT WITH_OPENVINS)
MESSAGE(STATUS " With OpenVINS = NO (WITH_OPENVINS=OFF)")
ELSE()
MESSAGE(STATUS " With ORB_SLAM2 = NO (ORB_SLAM2 not found, make sure environment variable ORB_SLAM2_ROOT_DIR is set)")
MESSAGE(STATUS " With OpenVINS = NO (ov_msckf not found)")
ENDIF()
IF(ORB_SLAM_FOUND)
MESSAGE(STATUS " With ORB_SLAM${ORB_SLAM_VERSION} = YES (License: GPLv3)")
ELSEIF(NOT WITH_ORB_SLAM)
MESSAGE(STATUS " With ORB_SLAM = NO (WITH_ORB_SLAM=OFF)")
ELSEIF(G2O_FOUND)
MESSAGE(STATUS " With ORB_SLAM = NO (WITH_G2O should be OFF as ORB_SLAM uses its own g2o version)")
ELSE()
MESSAGE(STATUS " With ORB_SLAM = NO (ORB_SLAM2 and ORB_SLAM3 not found, make sure environment variable ORB_SLAM_ROOT_DIR is set)")
ENDIF()
MESSAGE(STATUS "Show all options with: cmake -LA | grep WITH_")

View File

@@ -1,5 +1,6 @@
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
RTAB-Map - https://github.com/introlab/rtabmap
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke, all rights reserved.
Copyright (c) XXX, contributors, all rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
@@ -11,7 +12,7 @@ modification, are permitted provided that the following conditions are met:
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the names of its
* Neither the name of the copyright holders nor the names of the
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
@@ -24,4 +25,4 @@ DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

View File

@@ -7,7 +7,7 @@ rtabmap ![Analytics](https://ga-beacon-279122.nn.r.appspot.com/UA-56986679-3/git
[![License][license-image]][license]
Linux: [![Build Status](https://travis-ci.org/introlab/rtabmap.svg?branch=master)](https://travis-ci.org/introlab/rtabmap) Windows: [![Build status](https://ci.appveyor.com/api/projects/status/hr73xspix9oqa26h/branch/master?svg=true)](https://ci.appveyor.com/project/matlabbe/rtabmap/branch/master)
[release-image]: https://img.shields.io/badge/release-0.20.2-green.svg?style=flat
[release-image]: https://img.shields.io/badge/release-0.20.7-green.svg?style=flat
[releases]: https://github.com/introlab/rtabmap/releases
[license-image]: https://img.shields.io/badge/license-BSD-green.svg?style=flat

View File

@@ -51,15 +51,19 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
@K4A@#define RTABMAP_K4A
@CVSBA@#define RTABMAP_CVSBA
@POINTMATCHER@#define RTABMAP_POINTMATCHER
@CCCORELIB@#define RTABMAP_CCCORELIB
@FASTCV@#define RTABMAP_FASTCV
@PDAL@#define RTABMAP_PDAL
@LOAM@#define RTABMAP_LOAM
@DC1394@#define RTABMAP_DC1394
@FLYCAPTURE2@#define RTABMAP_FLYCAPTURE2
@ZED@#define RTABMAP_ZED
@ZEDOC@#define RTABMAP_ZEDOC
@REALSENSE@#define RTABMAP_REALSENSE
@REALSENSESLAM@#define RTABMAP_REALSENSE_SLAM
@REALSENSE2@#define RTABMAP_REALSENSE2
@MYNTEYE@#define RTABMAP_MYNTEYE
@DEPTHAI@#define RTABMAP_DEPTHAI
@OCTOMAP@#define RTABMAP_OCTOMAP
@CPUTSDF@#define RTABMAP_CPUTSDF
@ALICE_VISION@#define RTABMAP_ALICE_VISION
@@ -70,10 +74,11 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
@OKVIS@#define RTABMAP_OKVIS
@MSCKF_VIO@#define RTABMAP_MSCKF_VIO
@VINS@#define RTABMAP_VINS
@ORB_SLAM2@#define RTABMAP_ORB_SLAM2
@OPENVINS@#define RTABMAP_OPENVINS
@ORB_SLAM@#define RTABMAP_ORB_SLAM @ORB_SLAM_VERSION@
@ORB_OCTREE@#define RTABMAP_ORB_OCTREE
@SUPERPOINT_TORCH@#define RTABMAP_SUPERPOINT_TORCH
@PYMATCHER@#define RTABMAP_PYMATCHER
@TORCH@#define RTABMAP_TORCH
@PYTHON@#define RTABMAP_PYTHON
@MADGWICK@#define RTABMAP_MADGWICK
#include <pcl/pcl_config.h>

View File

@@ -2901,7 +2901,7 @@ bool RTABMapApp::exportMesh(
// save in database
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
pcl::fromPCLPointCloud2(polygonMesh->cloud, *cloud);
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false)); // for database
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false).data()); // for database
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons(1);
polygons[0].resize(polygonMesh->polygons.size());
for(unsigned int p=0; p<polygonMesh->polygons.size(); ++p)
@@ -2918,7 +2918,7 @@ bool RTABMapApp::exportMesh(
{
pcl::PointCloud<pcl::PointNormal>::Ptr cloud(new pcl::PointCloud<pcl::PointNormal>);
pcl::fromPCLPointCloud2(textureMesh->cloud, *cloud);
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false)); // for database
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false).data()); // for database
// save in database
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons(textureMesh->tex_polygons.size());
@@ -3054,7 +3054,7 @@ bool RTABMapApp::exportMesh(
// save in database
{
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*mergedClouds)); // for database
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*mergedClouds).data()); // for database
boost::mutex::scoped_lock lock(rtabmapMutex_);
rtabmap_->getMemory()->saveOptimizedMesh(cloudMat);
success = true;

View File

@@ -57,7 +57,7 @@ enum PointCloudShaders
// PointCloud shaders
const std::string kPointCloudVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec3 aColor;\n"
@@ -75,7 +75,7 @@ const std::string kPointCloudVertexShader =
" vColor = aColor;\n"
"}\n";
const std::string kPointCloudLightingVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec3 aNormal;\n"
@@ -100,7 +100,7 @@ const std::string kPointCloudLightingVertexShader =
"}\n";
const std::string kPointCloudFragmentShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"uniform float uGainR;\n"
"uniform float uGainG;\n"
@@ -127,7 +127,8 @@ const std::string kPointCloudBlendingFragmentShader =
" vec4 textureColor = vec4(vColor.z, vColor.y, vColor.x, 1.0);\n"
" float alpha = 1.0;\n"
" vec2 coord = uScreenScale * gl_FragCoord.xy;\n;"
" float depth = texture2D(uDepthTexture, coord).r;\n"
" vec4 depthPacked = texture2D(uDepthTexture, coord);\n"
" float depth = dot(depthPacked, 1./vec4(1.,255.,65025.,16581375.));\n"
" float num = (2.0 * uNearZ * uFarZ);\n"
" float diff = (uFarZ - uNearZ);\n"
" float add = (uFarZ + uNearZ);\n"
@@ -141,7 +142,7 @@ const std::string kPointCloudBlendingFragmentShader =
"}\n";
const std::string kPointCloudDepthPackingVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"uniform mat4 uMVP;\n"
@@ -154,15 +155,15 @@ const std::string kPointCloudDepthPackingFragmentShader =
"precision highp float;\n"
"precision mediump int;\n"
"void main() {\n"
" float toFixed = 255.0/256.0;\n"
" vec4 enc = vec4(1.0, 255.0, 65025.0, 160581375.0) * toFixed * gl_FragCoord.z;\n"
" vec4 enc = vec4(1.,255.,65025.,16581375.) * gl_FragCoord.z;\n"
" enc = fract(enc);\n"
" enc -= enc.yzww * vec2(1./255., 0.).xxxy;\n"
" gl_FragColor = enc;\n"
"}\n";
// Texture shaders
const std::string kTextureMeshVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec2 aTexCoord;\n"
@@ -185,7 +186,7 @@ const std::string kTextureMeshVertexShader =
" vLightWeighting = 1.0;\n"
"}\n";
const std::string kTextureMeshLightingVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec3 aNormal;\n"
@@ -214,7 +215,7 @@ const std::string kTextureMeshLightingVertexShader =
" vLightWeighting=0.5;\n"
"}\n";
const std::string kTextureMeshFragmentShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"uniform sampler2D uTexture;\n"
"uniform float uGainR;\n"
@@ -245,7 +246,8 @@ const std::string kTextureMeshBlendingFragmentShader =
" vec4 textureColor = texture2D(uTexture, vTexCoord);\n"
" float alpha = 1.0;\n"
" vec2 coord = uScreenScale * gl_FragCoord.xy;\n;"
" float depth = texture2D(uDepthTexture, coord).r;\n"
" vec4 depthPacked = texture2D(uDepthTexture, coord);\n"
" float depth = dot(depthPacked, 1./vec4(1.,255.,65025.,16581375.));\n"
" float num = (2.0 * uNearZ * uFarZ);\n"
" float diff = (uFarZ - uNearZ);\n"
" float add = (uFarZ + uNearZ);\n"

View File

@@ -97,6 +97,7 @@ Scene::Scene() :
g_(0.0f),
b_(0.0f),
fboId_(0),
rboId_(0),
depthTexture_(0),
screenWidth_(0),
screenHeight_(0),
@@ -176,6 +177,8 @@ void Scene::DeleteResources() {
{
glDeleteFramebuffers(1, &fboId_);
fboId_ = 0;
glDeleteRenderbuffers(1, &rboId_);
rboId_ = 0;
glDeleteTextures(1, &depthTexture_);
depthTexture_ = 0;
}
@@ -220,16 +223,23 @@ void Scene::SetupViewPort(int w, int h) {
UASSERT(gesture_camera_ != 0);
gesture_camera_->SetWindowSize(static_cast<float>(w), static_cast<float>(h));
glViewport(0, 0, w, h);
if(screenWidth_ != w || fboId_ == 0)
if(screenWidth_ != w || screenHeight_ != h || fboId_ == 0)
{
if(fboId_>0)
{
glDeleteFramebuffers(1, &fboId_);
fboId_ = 0;
glDeleteRenderbuffers(1, &rboId_);
rboId_ = 0;
glDeleteTextures(1, &depthTexture_);
depthTexture_ = 0;
}
// regenerate fbo texture
// create a framebuffer object, you need to delete them when program exits.
glGenFramebuffers(1, &fboId_);
glBindFramebuffer(GL_FRAMEBUFFER, fboId_);
// Create depth texture
glGenTextures(1, &depthTexture_);
glBindTexture(GL_TEXTURE_2D, depthTexture_);
@@ -237,16 +247,17 @@ void Scene::SetupViewPort(int w, int h) {
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE);
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
glTexImage2D(GL_TEXTURE_2D, 0, GL_DEPTH_COMPONENT, w, h, 0, GL_DEPTH_COMPONENT, GL_UNSIGNED_INT, NULL);
glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, w, h, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
glBindTexture(GL_TEXTURE_2D, 0);
// regenerate fbo texture
// create a framebuffer object, you need to delete them when program exits.
glGenFramebuffers(1, &fboId_);
glBindFramebuffer(GL_FRAMEBUFFER, fboId_);
glGenRenderbuffers(1, &rboId_);
glBindRenderbuffer(GL_RENDERBUFFER, rboId_);
glRenderbufferStorage(GL_RENDERBUFFER, GL_DEPTH_COMPONENT16, w, h);
glBindRenderbuffer(GL_RENDERBUFFER, 0);
// Set the texture to be at the depth attachment point of the FBO
glFramebufferTexture2D(GL_FRAMEBUFFER, GL_DEPTH_ATTACHMENT, GL_TEXTURE_2D, depthTexture_, 0);
// Set the texture to be at the color attachment point of the FBO (we pack depth 32 bits in color)
glFramebufferTexture2D(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0, GL_TEXTURE_2D, depthTexture_, 0);
glFramebufferRenderbuffer(GL_FRAMEBUFFER, GL_DEPTH_ATTACHMENT, GL_RENDERBUFFER, rboId_);
GLuint status = glCheckFramebufferStatus(GL_FRAMEBUFFER);
if ( status != GL_FRAMEBUFFER_COMPLETE)
@@ -464,14 +475,13 @@ int Scene::Render(const float * uvsTransformed, glm::mat4 arViewMatrix, glm::mat
// set the rendering destination to FBO
glBindFramebuffer(GL_FRAMEBUFFER, fboId_);
glColorMask(GL_FALSE, GL_FALSE, GL_FALSE, GL_FALSE);
glClearColor(1, 1, 1, 1);
glClearColor(0, 0, 0, 0);
glClear(GL_DEPTH_BUFFER_BIT | GL_COLOR_BUFFER_BIT);
if(renderBackgroundCamera)
{
PointCloudDrawable drawable(occlusionMesh);
drawable.Render(projectionMatrix, viewMatrix, true, pointSize_, false, false, 999.0f);
drawable.Render(projectionMatrix, viewMatrix, true, pointSize_, false, false, 999.0f, 0, 0, 0, 0, 0, true);
}
else
{
@@ -479,13 +489,12 @@ int Scene::Render(const float * uvsTransformed, glm::mat4 arViewMatrix, glm::mat
for(std::vector<PointCloudDrawable*>::const_iterator iter=cloudsToDraw.begin(); iter!=cloudsToDraw.end(); ++iter)
{
// set large distance to cam to use low res polygons for fast processing
(*iter)->Render(projectionMatrix, viewMatrix, meshRendering_, pointSize_, false, false, 999.0f);
(*iter)->Render(projectionMatrix, viewMatrix, meshRendering_, pointSize_, false, false, 999.0f, 0, 0, 0, 0, 0, true);
}
}
// back to normal window-system-provided framebuffer
glBindFramebuffer(GL_FRAMEBUFFER, 0); // unbind
glColorMask(GL_TRUE, GL_TRUE, GL_TRUE, GL_TRUE);
}
if(doubleTapOn_ && gesture_camera_->GetCameraType() != tango_gl::GestureCamera::kFirstPerson)
@@ -501,8 +510,7 @@ int Scene::Render(const float * uvsTransformed, glm::mat4 arViewMatrix, glm::mat
GLubyte zValue[4];
glReadPixels(doubleTapPos_.x*screenWidth_, screenHeight_-doubleTapPos_.y*screenHeight_, 1, 1, GL_RGBA, GL_UNSIGNED_BYTE, zValue);
float fromFixed = 256.0f/255.0f;
float zValueF = float(zValue[0]/255.0f)*fromFixed + float(zValue[1]/255.0f)*fromFixed/255.0f + float(zValue[2]/255.0f)*fromFixed/65025.0f + float(zValue[3]/255.0f)*fromFixed/160581375.0f;
float zValueF = float(zValue[0]/255.0f) + float(zValue[1]/255.0f)/255.0f + float(zValue[2]/255.0f)/65025.0f + float(zValue[3]/255.0f)/160581375.0f;
if(zValueF != 0.0f)
{

View File

@@ -204,6 +204,7 @@ class Scene {
float g_;
float b_;
GLuint fboId_;
GLuint rboId_;
GLuint depthTexture_;
GLsizei screenWidth_;
GLsizei screenHeight_;

View File

@@ -1,19 +1,6 @@
### Qt Gui stuff ###
SET(headers_ui
./ObjDeletionHandler.h
)
#This will generate moc_* for Qt
IF(QT4_FOUND)
QT4_WRAP_CPP(moc_srcs ${headers_ui})
ELSE()
QT5_WRAP_CPP(moc_srcs ${headers_ui})
ENDIF()
SET(SRC_FILES
main.cpp
${moc_srcs}
)
SET(INCLUDE_DIRS

View File

@@ -35,7 +35,10 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include "rtabmap/utilite/UObjDeletionThread.h"
#include "rtabmap/utilite/UFile.h"
#include "rtabmap/utilite/UConversion.h"
#include "ObjDeletionHandler.h"
#ifdef RTABMAP_PYTHON
#include "rtabmap/core/PythonInterface.h"
#endif
using namespace rtabmap;
@@ -45,6 +48,10 @@ int main(int argc, char* argv[])
ULogger::setType(ULogger::kTypeConsole);
ULogger::setLevel(ULogger::kWarning);
#ifdef RTABMAP_PYTHON
PythonInterface python; // Make sure we initialize python in main thread
#endif
/* Create tasks */
QApplication * app = new QApplication(argc, argv);
app->setStyleSheet("QMessageBox { messagebox-text-interaction-flags: 5; }"); // selectable message box

View File

@@ -0,0 +1,22 @@
## Multi-Session Visual SLAM for Illumination Invariant Localization in Indoor Environments
* Paper: https://arxiv.org/abs/2103.03827
* The setup: we did 6 mapping sessions at dusk to evaluate how well RTAB-Map can localize (only by vision) on maps taken at different illumination conditions. The data has been collected with [RTAB-Map Tango](https://play.google.com/store/apps/details?id=com.introlab.rtabmap&hl=en_CA&gl=US).
![Overview](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_overview.jpg)]
## Description
This folder contains scripts to re-generate results from the paper. The main idea behind this work is that using Multi-Session mapping can help to localize visually in illumination changing environments even with features that are not very robust to such conditions. We compared common hand-made visual features like SIFT, SURF, BRIEF, BRISK, FREAK, DAISY, KAZE with learned descriptor SuperPoint. The following picture show how robust are the visual features tested when localizing against single session recorded at different time. For example, the bottom-left and top-right cells are when the robot tries to localize the night on a map taken the day or vice-versa. The diagonal is localization performance when the localization session is about the same time than when the map was recorded. SuperPoint has clearly an advantage on this single-session experiment.
![All sessions](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_single_percentage.jpg)]
The following image shows when we do the same localization experiment at different hours, but against maps created by assembling maps taken at different hours. In this case, we can see that even binary features like BRIEF can work relatively well in illumination-variant environments. See the paper for more detailled results and comments. The line `1+2+3+4+5+6` refers to the assembled map shown below containing all mapping sessions linked together in same database.
![All sessions](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_merged_percentage.jpg)]
![All sessions](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_map_merged_999.jpg)]

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View File

@@ -0,0 +1,135 @@
clear all
close all
pkg load signal
# rtabmap-report --loc 32 Loop/Odom_correction_norm/m Loop/Visual_inliers/ Timing/Total/ms . Keypoint/Current_frame/words
# Right-click on thr legend of the figure, copy all data to clipboard
# Paste in correction#.txt, inliers#.txt and time#.txt where # is the
# number of the descriptor used
skipFrameDir = '0';
prefix = 'Stat';
RAMaddOverhead = 1;
% Inliers_ratio = 'Loop/Visual_inliers/' ./ 'Keypoint/Current_frame/words'
% Odometry_average = 'Memory/Distance_travelled/m'(2:end) - 'Memory/Distance_travelled/m'(1:end-1)
statNames = {'Loop/Odom_correction_norm/m', 'Inliers_ratio_%', 'Timing/Total/ms', 'Memory/RAM_usage/MB', 'Memory/RAM_estimated/MB', 'Keypoint/Current_frame/words', 'Loop/Map_id/'}; % 'Odometry_average'
datasets = [ 0 1 6 7 9 12 14 11]; % 0 1 6 7 8 9 11 12
sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
allCumResults = {};
allMaxResults = {};
for s=1:length(statNames)
avgResults = {};
maxResults = {};
totalResults = {};
absResults = {};
statName = strrep(statNames{s},'/','-');
for d=1:length(datasets)
if strcmp(statName,'Inliers_ratio_%')
data = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' 'Loop-Visual_inliers-' '.txt'], '\t', 1, 0, "emptyvalue", 0);
dataWords = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' 'Keypoint-Current_frame-words' '.txt'], '\t', 1, 0, "emptyvalue", 0);
data(:, 2:end) = data(:, 2:end) ./ dataWords(:, 2:end) * 100;
elseif strcmp(statName, 'Odometry_average')
data = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' 'Memory-Distance_travelled-m' '.txt'], '\t', 1, 0, "emptyvalue", 0);
else
data = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' statName '.txt'], '\t', 1, 0, "emptyvalue", 0);
endif
sessions = size(data,2)-1;
avgResultsTmp = zeros(sessions, length(sep)-1);
maxResultsTmp = zeros(sessions, length(sep)-1);
totalResultsTmp = zeros(sessions, length(sep)-1);
absResultsTmp = zeros(sessions, length(sep)-1);
for i = 1:sessions
for j = 1:length(sep)-1
x = data(:,1);
y = data(:,i+1);
y = y(x>=sep(j) & x<=sep(j+1), :);
x = x(x>=sep(j) & x<=sep(j+1), :);
if strcmp(statName, 'Odometry_average')
y(2:end) = y(2:end) - y(1:end-1);
y(y < 0.05) = 0;
elseif strcmp(statName, 'Loop-Map_id-')
y = y+1;
y(y>0) = 1;
end
if strcmp(statName, 'Memory-RAM_estimated-MB') && RAMaddOverhead == 1
% Valgrind estimated around 90 MB constant overhead
y = y + 90;
if datasets(d) == 7
%% 135 MB overhead for BRISK kernel
y = y + 135;
elseif datasets(d) == 11
%% 645 MB (library cuda) + 800 MB (network) for SuperPoint
y = y + 645+800;
elseif datasets(d) == 13 || datasets(d) == 14
%% 64 MB overhead for DAISY
y = y + 64;
endif
endif
nonzeros = y(y>0);
if strcmp(statName, 'Loop-Map_id-')
nonzeros = y;
end
if length(nonzeros) > 0
avgValue = sum(nonzeros)/length(nonzeros);
avgResultsTmp(i,j) = avgValue;
maxResultsTmp(i,j) = max(nonzeros);
totalResultsTmp(i,j) = length(nonzeros);
absResultsTmp(i,j) = sum(nonzeros);
endif
endfor
endfor
avgResults{1,d} = avgResultsTmp;
maxResults{1,d} = maxResultsTmp;
totalResults{1,d} = totalResultsTmp;
absResults{1,d} = absResultsTmp;
endfor
% compute cumulative results
cumResults = zeros(sessions+2, length(datasets)+1);
for d=1:length(datasets)
cumResults(1,d+1) = datasets(d);
if sum(totalResults{1,d}, 2)
cumResults(2:end-1,d+1) = sum(absResults{1,d}, 2) ./ sum(totalResults{1,d}, 2);
endif
cumResults(end,d+1) = sum(sum(absResults{1,d}(1:6,1:6).*eye(6,6))) / sum(sum(totalResults{1,d}(1:6,1:6).*eye(6,6)));
end
cumResults(2:end-1,1) = 1:sessions;
allCumResults{1,s} = statNames{s};
if strcmp(statNames{s}, 'Loop/Odom_correction_norm/m')
cumResults(2:end,2:end) = cumResults(2:end,2:end) * 1000;
allCumResults{1,s} = 'Loop/Odom_correction_norm/mm';
elseif strcmp(statNames{s}, 'Loop/Map_id/')
cumResults(2:end,2:end) = cumResults(2:end,2:end) * 100;
endif
allCumResults{2,s} = round(cumResults);
% compute max results
cumMaxResults = zeros(sessions+2, length(datasets)+1);
for d=1:length(datasets)
cumMaxResults(1,d+1) = datasets(d);
if sum(totalResults{1,d}, 2)
cumMaxResults(2:end-1,d+1) = max(maxResults{1,d}, [], 2);
endif
cumMaxResults(end,d+1) = max(max(maxResults{1,d}(1:6,1:6).*eye(6,6)));
end
cumMaxResults(2:end-1,1) = 1:sessions;
allMaxResults{1,s} = statNames{s};
allMaxResults{2,s} = cumMaxResults;
endfor % statNames

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@@ -0,0 +1,235 @@
close all
clear all
pkg load signal
# rtabmap-report --loc 32 Loop/Map_id/ loc
# Right-click on thr legend of the figure, copy all data to clipboard
# Paste in data#.txt where # is the number of the descriptor used
resultsToShow = 1; % 1=single loc, 2=merged loc, 3=consecutive
skipFrameDir = '0';
datasetPrefix = 'Stat';
datasets = [0 1 6 7 9 12 14 11]; % 0 1 6 7 8 9 11 12
datasetsName = {'SURF' 'SIFT' 'ORB' 'FAST/FREAK' 'FAST/BRIEF' 'GFTT/FREAK' 'GFTT/BRIEF' 'BRISK' 'GFTT/ORB' 'KAZE' 'ORB-OCTREE' 'SuperPoint' 'SURF/FREAK' 'GFTT/DAISY' 'SURF/DAISY'};
sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
if resultsToShow == 3
sep = [0, 1000, 3000, 5000, 7000, 9000];
sepName = {'17:27', '17:54', '18:27', '18:56', '19:35'};
datasetPrefix = 'Consecutive'
endif
percentResults = {};
totalResults = {};
locResults = {};
figure
colors = get(gca, 'ColorOrder');
tmp=colors(3,:);
colors(3,:) = colors(5,:);
colors(5,:) = tmp;
globalSeparators = [];
globalx = [];
globaly = [];
globalc = [];
for d=1:length(datasets)
data = dlmread([skipFrameDir '/' datasetPrefix num2str(datasets(d)) '-Loop-Map_id-' '.txt'], '\t', 1, 0, "emptyvalue", NaN);
curvesBeg = 2;
curvesEnd = size(data,2)-4;
if resultsToShow == 2
curvesBeg = 8;
curvesEnd = size(data,2);
elseif resultsToShow == 3
curvesEnd = size(data,2);
endif
curves = curvesEnd - curvesBeg + 1;
percentResultsTmp = zeros(curves, length(sep)-1);
totalResultsTmp = zeros(curves, length(sep)-1);
locResultsTmp = zeros(curves, length(sep)-1);
offset = 1;
for i = 1:curves
index = i + curvesBeg - 1;
separators = [];
x_all = [];
y_all = [];
m_all = [];
previousMax = 0;
for j = 1:length(sep)-1
x = data(:,1);
y = data(:,index);
y = y(x>=sep(j) & x<=sep(j+1), :);
x = x(x>=sep(j) & x<=sep(j+1), :);
minimum = x(1,1);
separators = [separators previousMax];
x = x - (minimum-previousMax);
previousMax = x(end,1);
y = y + 1;
m = y;
y(y>0) = 1;
y(isnan(y)) = 0;
percent = sum(y)/length(y);
percentResultsTmp(i,j) = percent;
locResultsTmp(i,j) = sum(y);
totalResultsTmp(i,j) = length(y);
y(y>0) = -(d-1)*curves -i - (d-1)*offset;
%x(y==0) = nan;
m(y==0) = nan;
y(y==0) = nan;
if resultsToShow == 2
if i==1 %% Merged 1, 6
m(m==1) = 1;
m(m==2) = 6;
elseif i==2 %% Merged 1,3(2 sessions),5
m(m==1) = 1;
m(m==2) = 3;
m(m==3) = 3;
m(m==4) = 5;
elseif i==3 %% Merged 2(2 sessions),4,6
m(m==1) = 2;
m(m==2) = 2;
m(m==4) = 6;
m(m==3) = 4;
elseif i>=4 %% Merged 1, 2(2 sessions), 3(2 sessions),4,5,6
m(m==1) = 1;
m(m==2) = 2;
m(m==3) = 2;
m(m==4) = 3;
m(m==5) = 3;
m(m==6) = 4;
m(m==7) = 5;
m(m==8) = 6;
endif
endif
x = upsample(x, 2);
y = upsample(y, 2);
m = upsample(m, 2);
x(2:2:end-1) = x(3:2:end);
y(2:2:end-1) = y(3:2:end);
m(2:2:end) = m(1:2:end);
x = x(1:end-1);
y = y(1:end-1);
m = m(1:end-1);
x_all = [x_all nan x'];
y_all = [y_all nan y'];
m_all = [m_all nan m'];
endfor
if resultsToShow == 2
globalx = [globalx x_all];
globaly = [globaly y_all];
globalc = [globalc m_all];
else
plot(x_all,y_all, 'linewidth', 3, 'color', colors(i,:))
hold on
endif
separators = [separators previousMax];
globalSeparators = separators;
endfor
percentResults{1,d} = percentResultsTmp;
totalResults{1,d} = totalResultsTmp;
locResults{1,d} = locResultsTmp;
endfor
if resultsToShow == 2
indColors = ones(length(globalc), 3);
for j=1:length(globalc)
if ~isnan(globalc(j))
indColors(j,:) = colors(globalc(j),:);
endif
endfor
for i=1:6
tmpx = globalx;
tmpy = globaly;
tmpx(globalc~=i) = nan;
tmpy(globalc~=i) = nan;
plot(tmpx, tmpy, 'linewidth', 3, 'color', colors(i,:));
if i==1
hold on
endif
endfor
endif
for j=1:length(globalSeparators)
x = globalSeparators(j);
plot([x,x],[(-length(datasets)*(curves+1)) ,0], 'k','linewidth', 2);
endfor
for d=1:length(datasets)
annotation ("textbox", [0, 0.96-((d-0.5)/length(datasets))*0.95, 0,0], 'string', datasetsName{datasets(d)+1})
endfor
for s=1:length(sep)-1
annotation ("textbox", [0.1 + ((separators(s+1)-separators(s))/2+separators(s))/separators(end)*0.75, 0.98, 0,0], 'string', sepName{s})
endfor
axis('tight')
set(gca, 'units', 'normalized');
Tight = get(gca, 'Position');
NewPos = [Tight(1) 0.01 0.77 0.95]; %New plot position [X Y W H]
set(gca, 'Position', NewPos);
if length(sep) == 7
legend('16:46', '17:27', '17:54', '18:27', '18:56', '19:35', "location", 'northeastoutside' )
else
legend('16:46', '17:27', '17:54', '18:27', '18:56', "location", 'northeastoutside' )
endif
box off
axis off
#disp(percentResults);
#disp(totalResults);
figure;
for d=1:length(datasets)
subplot(4,2,d)
data=percentResults{1,d}*100;
data(isnan(data)) = 0;
hAxes = gca;
imagesc( hAxes, data, [0, 100])
%title({"",datasetsName{datasets(d)+1}})
colors = [ones(100,1) [1:100]'*0.01 [1:100]'*0];
colors(1,:) = 1;
colormap( hAxes , colors)
c = colorbar;
labels = {};
for v=get(c,'ytick'), labels{end+1} = sprintf('%d%%',v); end
set(c,'yticklabel',labels);
if mod(d,2) == 1
ylabel("Map")
endif
xlabel([datasetsName{datasets(d)+1} " Localization"])
set (gca, "xaxislocation", "top");
set(gca, 'XTickLabel', sepName, 'fontsize',7)
if resultsToShow == 3
set(gca, 'YTickLabel', {'16:46', '17:27', '17:54', '18:27', '18:56'}, 'fontsize',7)
elseif resultsToShow == 2
set(gca, 'YTickLabel', {'1+6', '1+3+5', '2+4+6', '1+2+3+4+6', 'bundle', 'reduced'}, 'fontsize',7)
else
set(gca, 'YTickLabel', {'16:46', '17:27', '17:54', '18:27', '18:56', '19:35'}, 'fontsize',7)
endif
endfor
% compute cumulative localizations
cumResults = zeros(curves+2, length(datasets)+1);
for d=1:length(datasets)
cumResults(1,d+1) = datasets(d);
cumResults(2:end-1,d+1) = round(sum(locResults{1,d}, 2) ./ sum(totalResults{1,d}, 2) * 100);
if resultsToShow == 1
cumResults(end,d+1) = round(sum(sum(locResults{1,d}.*eye(curves,curves))) / sum(totalResults{1,d},2)(1,1) * 100);
endif
end
cumResults(2:end-1,1) = 1:curves;
cumResults

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@@ -0,0 +1,19 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14) #0 1 6 7 8 9 11 12 13 14
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPORT_TOOL="${PREFIX}rtabmap-report"
for d in "${DETECTOR[@]}"
do
$REPORT_TOOL --export --export_prefix "Stat$d" --loc 32 Loop/Odom_correction_norm/m Loop/Visual_inliers/ Timing/Total/ms Loop/Map_id/ Keypoint/Current_frame/words Memory/RAM_usage/MB Memory/RAM_estimated/MB Memory/Distance_travelled/m "$SKIP/$d/loc"
$REPORT_TOOL --export --export_prefix "Consecutive$d" --loc 32 Loop/Map_id/ "$SKIP/$d/consecutive_loc"
done

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@@ -0,0 +1,42 @@
#!/bin/bash
if [ $# -eq 0 ]
then
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint)."
exit
fi
TYPE=$1
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
DETECT_MORE_LOOP_CLOSURE_TOOL="${PREFIX}rtabmap-detectMoreLoopClosures"
[ ! -d "$SKIP" ] && mkdir $SKIP
[ ! -d "$SKIP/$TYPE" ] && mkdir $SKIP/$TYPE
# 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db'
DATABASES=( 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db' )
PARAMS="--Kp/DetectorStrategy $TYPE --Vis/FeatureType $TYPE"
if [ $TYPE -eq 2 ] || [ $TYPE -eq 3 ] || [ $TYPE -eq 4 ] || [ $TYPE -eq 5 ] || [ $TYPE -eq 6 ] || [ $TYPE -eq 7 ] || [ $TYPE -eq 8 ] || [ $TYPE -eq 10 ] || [ $TYPE -eq 12 ]
then
# binary descriptors
PARAMS="--Vis/CorNNDR 0.8 $PARAMS"
else
# float descriptors
PARAMS="--Vis/CorNNDR 0.6 $PARAMS"
if
echo $PARAMS
for db in "${DATABASES[@]}"
do
$REPROCESS_TOOL --skip $SKIP --RGBD/MarkerDetection false --RGBD/ProximityBySpace true --RGBD/LocalRadius 1 --Mem/InitWMWithAllNodes true --Rtabmap/TimeThr 0 --Mem/UseOdomFeatures false --Optimizer/GravitySigma 0.1 --Mem/UseOdomGravity true --RGBD/OptimizeFromGraphEnd false --Mem/DepthAsMask false --RGBD/OptimizeMaxError 4 --RGBD/ProximityOdomGuess false --Vis/MaxFeatures 1000 --Kp/MaxFeatures 400 --Vis/EpipolarGeometryVar 0.1 --Vis/EstimationType 1 --Vis/MinInliers 20 --Rtabmap/MaxRetrieved 2 --Optimizer/Iterations 20 --Mem/CompressionParallelized true --Kp/Parallelized true --Kp/MaxDepth 0 --Kp/BadSignRatio 0.2 --BRIEF/Bytes 32 --Kp/ByteToFloat true --SURF/HessianThreshold 100 --SIFT/ContrastThreshold 0.02 --BRISK/Thresh 10 --SuperPoint/ModelPath superpoint.pt --Rtabmap/PublishRAMUsage true --ORB/EdgeThreshold 19 --ORB/ScaleFactor 2 --ORB/NLevels 3 --uerror $PARAMS $db $SKIP/$TYPE/$db
$DETECT_MORE_LOOP_CLOSURE_TOOL --uwarn $SKIP/$TYPE/$db
done

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@@ -0,0 +1,16 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14)
for d in "${DETECTOR[@]}"
do
./reprocess_maps.sh $d $SKIP
./run_merge.sh $d $SKIP
done

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@@ -0,0 +1,13 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
./reprocess_maps_all.sh $SKIP
./run_merge.sh $SKIP
./run_localization_single_all.sh $SKIP
./run_consecutive_localization_all.sh $SKIP

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@@ -0,0 +1,31 @@
#!/bin/bash
if [ $# -eq 0 ]
then
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint)."
exit
fi
TYPE=$1
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
SOURCE=('map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db')
TARGETS=($SKIP/$TYPE'/map_190321-172717.db;'$SKIP/$TYPE'/map_190321-175428.db;'$SKIP/$TYPE'/map_190321-193556.db' $SKIP/$TYPE'/map_190321-175428.db;'$SKIP/$TYPE'/map_190321-182709.db;' $SKIP/$TYPE'/map_190321-182709.db;'$SKIP/$TYPE'/map_190321-185608.db' $SKIP/$TYPE'/map_190321-185608.db;'$SKIP/$TYPE'/map_190321-193556.db' $SKIP/$TYPE'/map_190321-193556.db' )
[ ! -d "$SKIP/$TYPE/consecutive_loc" ] && mkdir $SKIP/$TYPE/consecutive_loc
for i in ${!SOURCE[@]}
do
db=${SOURCE[$i]}
loc_dbs=${TARGETS[$i]}
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --uwarn "$SKIP/$TYPE/$db;$loc_dbs" $SKIP/$TYPE/consecutive_loc/loc_$db
done

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@@ -0,0 +1,15 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14)
for d in "${DETECTOR[@]}"
do
./run_consecutive_localization.sh $d $SKIP
done

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@@ -0,0 +1,38 @@
#!/bin/bash
if [ $# -eq 0 ]
then
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint)."
exit
fi
TYPE=$1
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
# loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db
LOCALIZATION_DATABASES="loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db"
[ ! -d "$SKIP/$TYPE/loc" ] && mkdir $SKIP/$TYPE/accuracy
db=merged_9999.db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce true --Vis/BundleAdjustment 1 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOn_BaOn_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce false --Vis/BundleAdjustment 1 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOff_BaOn_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce true --Vis/BundleAdjustment 0 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOn_BaOff_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce false --Vis/BundleAdjustment 0 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOff_BaOff_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess true --Reg/RepeatOnce true --Vis/BundleAdjustment 1 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOn_DoubleRegOn_BaOn_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess true --Reg/RepeatOnce true --Vis/BundleAdjustment 0 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOn_DoubleRegOn_BaOff_$db

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@@ -0,0 +1,32 @@
#!/bin/bash
if [ $# -eq 0 ]
then
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint)."
exit
fi
TYPE=$1
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
# 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db' 'merged_9999.db' 'merged_135.db' 'merged_246.db' 'merged_16.db' 'merged_9999_reduced.db'
DATABASES=( 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db' 'merged_9999.db' 'merged_135.db' 'merged_246.db' 'merged_16.db' )
# loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db
LOCALIZATION_DATABASES="loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db"
[ ! -d "$SKIP/$TYPE/loc" ] && mkdir $SKIP/$TYPE/loc
echo $PARAMS
for db in "${DATABASES[@]}"
do
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/loc/loc_$db
done

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@@ -0,0 +1,15 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14)
for d in "${DETECTOR[@]}"
do
./run_localization_single.sh $d $SKIP
done

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@@ -0,0 +1,38 @@
#!/bin/bash
if [ $# -eq 0 ]
then
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint)."
exit
fi
TYPE=$1
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
DETECT_MORE_LOOP_CLOSURE_TOOL="${PREFIX}rtabmap-detectMoreLoopClosures"
DATABASES="$SKIP/$TYPE/map_190321-164651.db;$SKIP/$TYPE/map_190321-172717.db;$SKIP/$TYPE/map_190321-175428.db;$SKIP/$TYPE/map_190321-182709.db;$SKIP/$TYPE/map_190321-185608.db;$SKIP/$TYPE/map_190321-193556.db"
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$DATABASES" $SKIP/$TYPE/merged_9999.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_9999.db
#$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 --Mem/ReduceGraph true --Vis/MinInliers 60 "$DATABASES" $SKIP/$TYPE/merged_9999_reduced.db
#$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_9999_reduced.db
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$SKIP/$TYPE/map_190321-164651.db;$SKIP/$TYPE/map_190321-193556.db" $SKIP/$TYPE/merged_16.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_16.db
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$SKIP/$TYPE/map_190321-164651.db;$SKIP/$TYPE/map_190321-175428.db;$SKIP/$TYPE/map_190321-185608.db" $SKIP/$TYPE/merged_135.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_135.db
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$SKIP/$TYPE/map_190321-172717.db;$SKIP/$TYPE/map_190321-182709.db;$SKIP/$TYPE/map_190321-193556.db" $SKIP/$TYPE/merged_246.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_246.db

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@@ -0,0 +1,19 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 8 9 11 12 14)
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPORT_TOOL="${PREFIX}rtabmap-report"
for d in "${DETECTOR[@]}"
do
valgrind --tool=massif --time-unit=ms --detailed-freq=1 --max-snapshots=100 ${PREFIX}rtabmap-reprocess --Mem/IncrementalMemory false --Kp/IncrementalFlann false "${SKIP}/${d}/merged_9999.db;map_190321-164651.db" output.db
rm output.db
done

View File

@@ -0,0 +1,234 @@
#.rst:
# FindHIDAPI
# ----------
#
# Try to find HIDAPI library, from http://www.signal11.us/oss/hidapi/
#
# Cache Variables: (probably not for direct use in your scripts)
# HIDAPI_INCLUDE_DIR
# HIDAPI_LIBRARY
#
# Non-cache variables you might use in your CMakeLists.txt:
# HIDAPI_FOUND
# HIDAPI_INCLUDE_DIRS
# HIDAPI_LIBRARIES
#
# COMPONENTS
# ^^^^^^^^^^
#
# This module respects several COMPONENTS specifying the backend you prefer:
# ``any`` (the default), ``libusb``, and ``hidraw``.
# The availablility of the latter two depends on your platform.
#
#
# IMPORTED Targets
# ^^^^^^^^^^^^^^^^
# This module defines :prop_tgt:`IMPORTED` target ``HIDAPI::hidapi`` (in all cases or
# if no components specified), ``HIDAPI::hidapi-libusb`` (if you requested the libusb component),
# and ``HIDAPI::hidapi-hidraw`` (if you requested the hidraw component),
#
# Result Variables
# ^^^^^^^^^^^^^^^^
#
# ``HIDAPI_FOUND``
# True if HIDAPI or the requested components (if any) were found.
#
# We recommend using the imported targets instead of the following.
#
# ``HIDAPI_INCLUDE_DIRS``
# ``HIDAPI_LIBRARIES``
#
# Original Author:
# 2009-2010, 2019 Ryan Pavlik <ryan.pavlik@collabora.com> <abiryan@ryand.net>
# http://academic.cleardefinition.com
#
# Copyright Iowa State University 2009-2010.
# Copyright Collabora, Ltd. 2019.
# Distributed under the Boost Software License, Version 1.0.
# (See accompanying file LICENSE_1_0.txt or copy at
# http://www.boost.org/LICENSE_1_0.txt)
cmake_policy(SET CMP0045 NEW)
cmake_policy(SET CMP0053 NEW)
cmake_policy(SET CMP0054 NEW)
set(HIDAPI_ROOT_DIR
"${HIDAPI_ROOT_DIR}"
CACHE PATH "Root to search for HIDAPI")
# Clean up components
if("${HIDAPI_FIND_COMPONENTS}")
if(WIN32 OR APPLE)
# This makes no sense on Windows or Mac, which have native APIs
list(REMOVE HIDAPI_FIND_COMPONENTS libusb)
endif()
if(NOT ${CMAKE_SYSTEM} MATCHES "Linux")
# hidraw is only on linux
list(REMOVE HIDAPI_FIND_COMPONENTS hidraw)
endif()
endif()
if(NOT "${HIDAPI_FIND_COMPONENTS}")
# Default to any
set(HIDAPI_FIND_COMPONENTS any)
endif()
# Ask pkg-config for hints
find_package(PkgConfig QUIET)
if(PKG_CONFIG_FOUND)
set(_old_prefix_path "${CMAKE_PREFIX_PATH}")
# So pkg-config uses HIDAPI_ROOT_DIR too.
if(HIDAPI_ROOT_DIR)
list(APPEND CMAKE_PREFIX_PATH ${HIDAPI_ROOT_DIR})
endif()
pkg_check_modules(PC_HIDAPI_LIBUSB QUIET hidapi-libusb)
pkg_check_modules(PC_HIDAPI_HIDRAW QUIET hidapi-hidraw)
# Restore
set(CMAKE_PREFIX_PATH "${_old_prefix_path}")
endif()
# Actually search
find_library(
HIDAPI_UNDECORATED_LIBRARY
NAMES hidapi
PATHS "${HIDAPI_ROOT_DIR}"
PATH_SUFFIXES lib)
find_library(
HIDAPI_LIBUSB_LIBRARY
NAMES hidapi hidapi-libusb
PATHS "${HIDAPI_ROOT_DIR}"
PATH_SUFFIXES lib
HINTS ${PC_HIDAPI_LIBUSB_LIBRARY_DIRS})
if(CMAKE_SYSTEM MATCHES "Linux")
find_library(
HIDAPI_HIDRAW_LIBRARY
NAMES hidapi-hidraw
HINTS ${PC_HIDAPI_HIDRAW_LIBRARY_DIRS})
endif()
find_path(
HIDAPI_INCLUDE_DIR
NAMES hidapi.h
PATHS "${HIDAPI_ROOT_DIR}"
PATH_SUFFIXES hidapi include include/hidapi
HINTS ${PC_HIDAPI_HIDRAW_INCLUDE_DIRS} ${PC_HIDAPI_LIBUSB_INCLUDE_DIRS})
find_package(Threads QUIET)
###
# Compute the "I don't care which backend" library
###
set(HIDAPI_LIBRARY)
# First, try to use a preferred backend if supplied
if("${HIDAPI_FIND_COMPONENTS}" MATCHES "libusb"
AND HIDAPI_LIBUSB_LIBRARY
AND NOT HIDAPI_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_LIBUSB_LIBRARY})
endif()
if("${HIDAPI_FIND_COMPONENTS}" MATCHES "hidraw"
AND HIDAPI_HIDRAW_LIBRARY
AND NOT HIDAPI_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_HIDRAW_LIBRARY})
endif()
# Then, if we don't have a preferred one, settle for anything.
if(NOT HIDAPI_LIBRARY)
if(HIDAPI_LIBUSB_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_LIBUSB_LIBRARY})
elseif(HIDAPI_HIDRAW_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_HIDRAW_LIBRARY})
elseif(HIDAPI_UNDECORATED_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_UNDECORATED_LIBRARY})
endif()
endif()
###
# Determine if the various requested components are found.
###
set(_hidapi_component_required_vars)
foreach(_comp IN LISTS HIDAPI_FIND_COMPONENTS)
if("${_comp}" STREQUAL "any")
list(APPEND _hidapi_component_required_vars HIDAPI_INCLUDE_DIR
HIDAPI_LIBRARY)
if(HIDAPI_INCLUDE_DIR AND EXISTS "${HIDAPI_LIBRARY}")
set(HIDAPI_any_FOUND TRUE)
mark_as_advanced(HIDAPI_INCLUDE_DIR)
else()
set(HIDAPI_any_FOUND FALSE)
endif()
elseif("${_comp}" STREQUAL "libusb")
list(APPEND _hidapi_component_required_vars HIDAPI_INCLUDE_DIR
HIDAPI_LIBUSB_LIBRARY)
if(HIDAPI_INCLUDE_DIR AND EXISTS "${HIDAPI_LIBUSB_LIBRARY}")
set(HIDAPI_libusb_FOUND TRUE)
mark_as_advanced(HIDAPI_INCLUDE_DIR HIDAPI_LIBUSB_LIBRARY)
else()
set(HIDAPI_libusb_FOUND FALSE)
endif()
elseif("${_comp}" STREQUAL "hidraw")
list(APPEND _hidapi_component_required_vars HIDAPI_INCLUDE_DIR
HIDAPI_HIDRAW_LIBRARY)
if(HIDAPI_INCLUDE_DIR AND EXISTS "${HIDAPI_HIDRAW_LIBRARY}")
set(HIDAPI_hidraw_FOUND TRUE)
mark_as_advanced(HIDAPI_INCLUDE_DIR HIDAPI_HIDRAW_LIBRARY)
else()
set(HIDAPI_hidraw_FOUND FALSE)
endif()
else()
message(WARNING "${_comp} is not a recognized HIDAPI component")
set(HIDAPI_${_comp}_FOUND FALSE)
endif()
endforeach()
unset(_comp)
###
# FPHSA call
###
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(
HIDAPI REQUIRED_VARS ${_hidapi_component_required_vars} THREADS_FOUND
HANDLE_COMPONENTS)
if(HIDAPI_FOUND)
set(HIDAPI_LIBRARIES "${HIDAPI_LIBRARY}")
set(HIDAPI_INCLUDE_DIRS "${HIDAPI_INCLUDE_DIR}")
if(NOT TARGET HIDAPI::hidapi)
add_library(HIDAPI::hidapi UNKNOWN IMPORTED)
set_target_properties(
HIDAPI::hidapi
PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "C"
IMPORTED_LOCATION ${HIDAPI_LIBRARY})
set_property(
TARGET HIDAPI::hidapi PROPERTY IMPORTED_LINK_INTERFACE_LIBRARIES
Threads::Threads)
endif()
endif()
if(HIDAPI_libusb_FOUND AND NOT TARGET HIDAPI::hidapi-libusb)
add_library(HIDAPI::hidapi-libusb UNKNOWN IMPORTED)
set_target_properties(
HIDAPI::hidapi-libusb
PROPERTIES IMPORTED_LINK_INTERFACE_LANGUAGES "C" IMPORTED_LOCATION
${HIDAPI_LIBUSB_LIBRARY})
set_property(TARGET HIDAPI::hidapi-libusb
PROPERTY IMPORTED_LINK_INTERFACE_LIBRARIES Threads::Threads)
endif()
if(HIDAPI_hidraw_FOUND AND NOT TARGET HIDAPI::hidapi-hidraw)
add_library(HIDAPI::hidapi-hidraw UNKNOWN IMPORTED)
set_target_properties(
HIDAPI::hidapi-hidraw
PROPERTIES IMPORTED_LINK_INTERFACE_LANGUAGES "C" IMPORTED_LOCATION
${HIDAPI_HIDRAW_LIBRARY})
set_property(TARGET HIDAPI::hidapi-hidraw
PROPERTY IMPORTED_LINK_INTERFACE_LIBRARIES Threads::Threads)
endif()

View File

@@ -0,0 +1,53 @@
# - Find ORB_SLAM2 OR ORB_SLAM3
#
# It sets the following variables:
# ORB_SLAM_FOUND - Set to false, or undefined, if ORB_SLAM isn't found.
# ORB_SLAM_INCLUDE_DIRS - The ORB_SLAM include directory.
# ORB_SLAM_LIBRARIES - The ORB_SLAM library to link against.
# ORB_SLAM_VERSION - The ORB_SLAM major version.
#
# Set ORB_SLAM_ROOT_DIR environment variable as the path to ORB_SLAM2 or ORB_SLAM3 root folder.
find_path(ORB_SLAM_INCLUDE_DIR NAMES System.h PATHS $ENV{ORB_SLAM_ROOT_DIR}/include)
find_library(ORB_SLAM2_LIBRARY NAMES ORB_SLAM2 PATHS $ENV{ORB_SLAM_ROOT_DIR}/lib)
find_library(ORB_SLAM3_LIBRARY NAMES ORB_SLAM3 PATHS $ENV{ORB_SLAM_ROOT_DIR}/lib)
find_path(g2o_INCLUDE_DIR NAMES g2o/core/sparse_optimizer.h PATHS $ENV{ORB_SLAM_ROOT_DIR}/Thirdparty/g2o NO_DEFAULT_PATH)
find_library(g2o_LIBRARY NAMES g2o PATHS $ENV{ORB_SLAM_ROOT_DIR}/Thirdparty/g2o/lib NO_DEFAULT_PATH)
find_library(DBoW2_LIBRARY NAMES DBoW2 PATHS $ENV{ORB_SLAM_ROOT_DIR}/Thirdparty/DBoW2/lib NO_DEFAULT_PATH)
IF(ORB_SLAM2_LIBRARY)
SET(ORB_SLAM_VERSION 2)
SET(ORB_SLAM_LIBRARY ${ORB_SLAM2_LIBRARY})
ELSEIF(ORB_SLAM3_LIBRARY)
SET(ORB_SLAM_VERSION 3)
SET(ORB_SLAM_LIBRARY ${ORB_SLAM3_LIBRARY})
ENDIF()
IF (ORB_SLAM_INCLUDE_DIR AND ORB_SLAM_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
SET(ORB_SLAM_FOUND TRUE)
SET(ORB_SLAM_INCLUDE_DIRS ${ORB_SLAM_INCLUDE_DIR} ${ORB_SLAM_INCLUDE_DIR}/CameraModels ${g2o_INCLUDE_DIR} $ENV{ORB_SLAM_ROOT_DIR})
SET(ORB_SLAM_LIBRARIES ${g2o_LIBRARY} ${ORB_SLAM_LIBRARY} ${DBoW2_LIBRARY})
ENDIF (ORB_SLAM_INCLUDE_DIR AND ORB_SLAM_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
FIND_PACKAGE(Pangolin QUIET)
IF(NOT Pangolin_FOUND)
SET(ORB_SLAM_FOUND FALSE)
MESSAGE(STATUS "Found ORB_SLAM but not Pangolin, disabling ORB_SLAM.")
ELSE()
MESSAGE(STATUS "Found Pangolin: ${Pangolin_INCLUDE_DIRS}")
SET(ORB_SLAM_INCLUDE_DIRS ${ORB_SLAM_INCLUDE_DIRS} ${Pangolin_INCLUDE_DIRS})
SET(ORB_SLAM_LIBRARIES ${ORB_SLAM_LIBRARIES} ${Pangolin_LIBRARIES})
ENDIF()
IF (ORB_SLAM_FOUND)
# show which ORB_SLAM was found only if not quiet
IF (NOT ORB_SLAM_FIND_QUIETLY)
MESSAGE(STATUS "Found ORB_SLAM${ORB_SLAM_VERSION}: ${ORB_SLAM_LIBRARIES}")
ENDIF (NOT ORB_SLAM_FIND_QUIETLY)
ELSE (ORB_SLAM_FOUND)
# fatal error if ORB_SLAM is required but not found
IF (ORB_SLAM_FIND_REQUIRED)
MESSAGE(FATAL_ERROR "Could not find ORB_SLAM")
ENDIF (ORB_SLAM_FIND_REQUIRED)
ENDIF (ORB_SLAM_FOUND)

View File

@@ -1,33 +0,0 @@
# - Find ORB_SLAM2
#
# It sets the following variables:
# ORB_SLAM2_FOUND - Set to false, or undefined, if ORB_SLAM2 isn't found.
# ORB_SLAM2_INCLUDE_DIRS - The ORB_SLAM2 include directory.
# ORB_SLAM2_LIBRARIES - The ORB_SLAM2 library to link against.
#
# Set ORB_SLAM2_ROOT_DIR environment variable as the path to ORB_SLAM2 root folder.
find_path(ORB_SLAM2_INCLUDE_DIR NAMES System.h PATHS $ENV{ORB_SLAM2_ROOT_DIR}/include)
find_library(ORB_SLAM2_LIBRARY NAMES ORB_SLAM2 PATHS $ENV{ORB_SLAM2_ROOT_DIR}/lib)
find_path(g2o_INCLUDE_DIR NAMES g2o/core/sparse_optimizer.h PATHS $ENV{ORB_SLAM2_ROOT_DIR}/Thirdparty/g2o NO_DEFAULT_PATH)
find_library(g2o_LIBRARY NAMES g2o PATHS $ENV{ORB_SLAM2_ROOT_DIR}/Thirdparty/g2o/lib NO_DEFAULT_PATH)
find_library(DBoW2_LIBRARY NAMES DBoW2 PATHS $ENV{ORB_SLAM2_ROOT_DIR}/Thirdparty/DBoW2/lib NO_DEFAULT_PATH)
IF (ORB_SLAM2_INCLUDE_DIR AND ORB_SLAM2_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
SET(ORB_SLAM2_FOUND TRUE)
SET(ORB_SLAM2_INCLUDE_DIRS ${ORB_SLAM2_INCLUDE_DIR} ${g2o_INCLUDE_DIR} $ENV{ORB_SLAM2_ROOT_DIR})
SET(ORB_SLAM2_LIBRARIES ${g2o_LIBRARY} ${ORB_SLAM2_LIBRARY} ${DBoW2_LIBRARY})
ENDIF (ORB_SLAM2_INCLUDE_DIR AND ORB_SLAM2_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
IF (ORB_SLAM2_FOUND)
# show which ORB_SLAM2 was found only if not quiet
IF (NOT ORB_SLAM2_FIND_QUIETLY)
MESSAGE(STATUS "Found ORB_SLAM2: ${ORB_SLAM2_LIBRARIES}")
ENDIF (NOT ORB_SLAM2_FIND_QUIETLY)
ELSE (ORB_SLAM2_FOUND)
# fatal error if ORB_SLAM2 is required but not found
IF (ORB_SLAM2_FIND_REQUIRED)
MESSAGE(FATAL_ERROR "Could not find ORB_SLAM2")
ENDIF (ORB_SLAM2_FIND_REQUIRED)
ENDIF (ORB_SLAM2_FOUND)

View File

@@ -0,0 +1,28 @@
# - Find ZED Open Capture
# This module finds zed open capture library
#
# It sets the following variables:
# ZEDOC_FOUND - Set to false, or undefined, if ZEDOC isn't found.
# ZEDOC_INCLUDE_DIRS - The ZEDOC include directory.
# ZEDOC_LIBRARIES - The ZEDOC library to link against.
find_library(ZEDOC_LIBRARY NAMES zed_open_capture PATHS $ENV{ZEDOC_ROOT_DIR}/lib)
find_path(ZEDOC_INCLUDE_DIR NAMES zed-open-capture/videocapture.hpp PATHS $ENV{ZEDOC_ROOT_DIR}/include)
IF (ZEDOC_INCLUDE_DIR AND ZEDOC_LIBRARY)
SET(ZEDOC_FOUND TRUE)
SET(ZEDOC_INCLUDE_DIRS ${ZEDOC_INCLUDE_DIR})
SET(ZEDOC_LIBRARIES ${ZEDOC_LIBRARY})
ENDIF (ZEDOC_INCLUDE_DIR AND ZEDOC_LIBRARY)
IF (ZEDOC_FOUND)
# show which ZEDOC was found only if not quiet
IF (NOT _FIND_QUIETLY)
MESSAGE(STATUS "Found ZEDOC: ${ZEDOC_LIBRARIES}")
ENDIF (NOT ZEDOC_FIND_QUIETLY)
ELSE (ZEDOC_FOUND)
# fatal error if ZEDOC is required but not found
IF (ZEDOC_FIND_REQUIRED)
MESSAGE(FATAL_ERROR "Could not find ZEDOC (Zed Open Capture)")
ENDIF (ZEDOC_FIND_REQUIRED)
ENDIF (ZEDOC_FOUND)

View File

@@ -124,6 +124,7 @@ public:
double fovY() const; // in radians
double horizontalFOV() const; // in degrees
double verticalFOV() const; // in degrees
bool isFisheye() const {return D_.cols == 6;}
bool load(const std::string & filePath);
bool load(const std::string & directory, const std::string & cameraName);

View File

@@ -32,5 +32,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <rtabmap/core/camera/CameraStereoImages.h>
#include <rtabmap/core/camera/CameraStereoVideo.h>
#include <rtabmap/core/camera/CameraStereoZed.h>
#include <rtabmap/core/camera/CameraStereoZedOC.h>
#include <rtabmap/core/camera/CameraStereoTara.h>
#include <rtabmap/core/camera/CameraMyntEye.h>
#include <rtabmap/core/camera/CameraDepthAI.h>

View File

@@ -69,7 +69,7 @@ public:
void setDistortionModel(const std::string & path);
void enableBilateralFiltering(float sigmaS, float sigmaR);
void disableBilateralFiltering() {_bilateralFiltering = false;}
void enableIMUFiltering(int filteringStrategy=1, const ParametersMap & parameters = ParametersMap());
void enableIMUFiltering(int filteringStrategy=1, const ParametersMap & parameters = ParametersMap(), bool baseFrameConversion = false);
void disableIMUFiltering();
RTABMAP_DEPRECATED(void setScanParameters(
@@ -125,6 +125,7 @@ private:
float _bilateralSigmaS;
float _bilateralSigmaR;
IMUFilter * _imuFilter;
bool _imuBaseFrameConversion;
};
} // namespace rtabmap

View File

@@ -120,7 +120,8 @@ public:
kFeatureSuperPointTorch=11, //new 0.19.7
kFeatureSurfFreak=12, //new 0.20.4
kFeatureGfttDaisy=13, //new 0.20.6
kFeatureSurfDaisy=14}; //new 0.20.6
kFeatureSurfDaisy=14, //new 0.20.6
kFeaturePyDetector=15}; //new 0.20.8
static std::string typeName(Type type)
{

View File

@@ -46,9 +46,9 @@ namespace graph {
// Graph utilities
////////////////////////////////////////////
bool RTABMAP_EXP exportPoses(
bool RTABMAP_EXP exportPoses(
const std::string & filePath,
int format, // 0=Raw (*.txt), 1=RGBD-SLAM motion capture (*.txt) (10=without change of coordinate frame), 2=KITTI (*.txt), 3=TORO (*.graph), 4=g2o (*.g2o)
int format, // 0=Raw (*.txt), 1=RGBD-SLAM motion capture (*.txt) (10=without change of coordinate frame, 11=10+ID), 2=KITTI (*.txt), 3=TORO (*.graph), 4=g2o (*.g2o)
const std::map<int, Transform> & poses,
const std::multimap<int, Link> & constraints = std::multimap<int, Link>(), // required for formats 3 and 4
const std::map<int, double> & stamps = std::map<int, double>(), // required for format 1
@@ -56,7 +56,7 @@ namespace graph {
bool RTABMAP_EXP importPoses(
const std::string & filePath,
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame), 2=KITTI, 3=TORO, 4=g2o, 5=NewCollege(t,x,y), 6=Malaga Urban GPS, 7=St Lucia INS, 8=Karlsruhe, 9=EuRoC MAV
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame, 11=10+ID), 2=KITTI, 3=TORO, 4=g2o, 5=NewCollege(t,x,y), 6=Malaga Urban GPS, 7=St Lucia INS, 8=Karlsruhe, 9=EuRoC MAV
std::map<int, Transform> & poses,
std::multimap<int, Link> * constraints = 0, // optional for formats 3 and 4
std::map<int, double> * stamps = 0); // optional for format 1 and 9
@@ -327,6 +327,9 @@ std::list<std::map<int, Transform> > RTABMAP_EXP getPaths(
std::map<int, Transform> poses,
const std::multimap<int, Link> & links);
void RTABMAP_EXP computeMinMax(const std::map<int, Transform> & poses,
cv::Vec3f & min,
cv::Vec3f & max);
} /* namespace graph */

View File

@@ -9,7 +9,8 @@
#define IMU_H_
#include <opencv2/core/core.hpp>
#include <rtabmap/utilite/ULogger.h>
#include <rtabmap/utilite/UEvent.h>
#include <rtabmap/core/Transform.h>
namespace rtabmap {
@@ -60,6 +61,9 @@ public:
const Transform & localTransform() const {return localTransform_;}
// apply local transform rotation to data, and set Identity rotation for local transform
void convertToBaseFrame();
bool empty() const
{
return localTransform_.isNull();

View File

@@ -71,11 +71,35 @@ public:
public:
LaserScan();
LaserScan(const LaserScan & data,
int maxPoints,
float maxRange,
const Transform & localTransform = Transform::getIdentity());
RTABMAP_DEPRECATED(LaserScan(const LaserScan & data,
int maxPoints,
float maxRange,
Format format,
const Transform & localTransform = Transform::getIdentity()), "Use version without \"format\" argument.");
LaserScan(const cv::Mat & data,
int maxPoints,
float maxRange,
Format format,
const Transform & localTransform = Transform::getIdentity());
RTABMAP_DEPRECATED(LaserScan(const LaserScan & data,
Format format,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform = Transform::getIdentity()), "Use version without \"format\" argument.");
LaserScan(const LaserScan & data,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform = Transform::getIdentity());
LaserScan(const cv::Mat & data,
Format format,
float minRange,
@@ -114,6 +138,17 @@ public:
void clear() {data_ = cv::Mat();}
private:
void init(const cv::Mat & data,
Format format,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
int maxPoints,
const Transform & localTransform = Transform::getIdentity());
private:
cv::Mat data_;
Format format_;

View File

@@ -193,7 +193,8 @@ public:
std::vector<int> * groundIndices = 0,
bool originalRefPoints = true,
std::vector<int> * frontierIndices = 0,
std::vector<double> * cloudProb = 0) const;
std::vector<double> * cloudProb = 0,
bool applyFloodFill = false ) const;
cv::Mat createProjectionMap(
float & xMin,

View File

@@ -49,11 +49,12 @@ public:
kTypeFovis = 2,
kTypeViso2 = 3,
kTypeDVO = 4,
kTypeORBSLAM2 = 5,
kTypeORBSLAM = 5,
kTypeOkvis = 6,
kTypeLOAM = 7,
kTypeMSCKF = 8,
kTypeVINS = 9
kTypeVINS = 9,
kTypeOpenVINS = 10
};
public:
@@ -67,7 +68,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() = 0;
virtual bool canProcessRawImages() const {return false;}
virtual bool canProcessIMU() const {return false;}
virtual bool canProcessAsyncIMU() const {return false;}
//getters
const Transform & getPose() const {return _pose;}

View File

@@ -84,6 +84,7 @@ public:
output.transformFiltered = transformFiltered;
output.transformGroundTruth = transformGroundTruth;
output.guessVelocity = guessVelocity;
output.guess = guess;
output.distanceTravelled = distanceTravelled;
output.memoryUsage = memoryUsage;
output.gravityRollError = gravityRollError;
@@ -111,7 +112,8 @@ public:
Transform transform;
Transform transformFiltered;
Transform transformGroundTruth;
Transform guessVelocity;
Transform guessVelocity; // deprecated, will be removed. Use guess and interval instead.
Transform guess;
float distanceTravelled;
int memoryUsage; //MB
double gravityRollError;

View File

@@ -0,0 +1,47 @@
/*
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef CORELIB_INCLUDE_RTABMAP_CORE_PDALWRITER_H_
#define CORELIB_INCLUDE_RTABMAP_CORE_PDALWRITER_H_
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
namespace rtabmap {
std::string getPDALSupportedWriters();
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZ> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZI> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
}
#endif /* CORELIB_INCLUDE_RTABMAP_CORE_PDALWRITER_H_ */

View File

@@ -244,9 +244,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Kp, NndrRatio, float, 0.8, "NNDR ratio (A matching pair is detected, if its distance is closer than X times the distance of the second nearest neighbor.)");
#if CV_MAJOR_VERSION > 2 && !defined(HAVE_OPENCV_XFEATURES2D)
// OpenCV>2 without xFeatures2D module doesn't have BRIEF
RTABMAP_PARAM(Kp, DetectorStrategy, int, 8, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY");
RTABMAP_PARAM(Kp, DetectorStrategy, int, 8, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#else
RTABMAP_PARAM(Kp, DetectorStrategy, int, 6, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY");
RTABMAP_PARAM(Kp, DetectorStrategy, int, 6, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#endif
RTABMAP_PARAM(Kp, TfIdfLikelihoodUsed, bool, true, "Use of the td-idf strategy to compute the likelihood.");
RTABMAP_PARAM(Kp, Parallelized, bool, true, "If the dictionary update and signature creation were parallelized.");
@@ -296,7 +296,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(FAST, CV, int, 0, "Enable FastCV implementation if non-zero (and RTAB-Map is built with FastCV support). Values should be 9 and 10.");
RTABMAP_PARAM(GFTT, QualityLevel, double, 0.001, "");
RTABMAP_PARAM(GFTT, MinDistance, double, 3, "");
RTABMAP_PARAM(GFTT, MinDistance, double, 7, "");
RTABMAP_PARAM(GFTT, BlockSize, int, 3, "");
RTABMAP_PARAM(GFTT, UseHarrisDetector, bool, false, "");
RTABMAP_PARAM(GFTT, K, double, 0.04, "");
@@ -332,6 +332,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(SuperPoint, NMSRadius, int, 4, uFormat("[%s=true] Minimum distance (pixels) between keypoints.", kSuperPointNMS().c_str()));
RTABMAP_PARAM(SuperPoint, Cuda, bool, true, "Use Cuda device for Torch, otherwise CPU device is used by default.");
RTABMAP_PARAM_STR(PyDetector, Path, "", "Path to python script file (see available ones in rtabmap/corelib/src/python/*). See the header to see where the script should be copied.");
RTABMAP_PARAM(PyDetector, Cuda, bool, true, "Use cuda.");
// BayesFilter
RTABMAP_PARAM(Bayes, VirtualPlacePriorThr, float, 0.9, "Virtual place prior");
RTABMAP_PARAM_STR(Bayes, PredictionLC, "0.1 0.36 0.30 0.16 0.062 0.0151 0.00255 0.000324 2.5e-05 1.3e-06 4.8e-08 1.2e-09 1.9e-11 2.2e-13 1.7e-15 8.5e-18 2.9e-20 6.9e-23", "Prediction of loop closures (Gaussian-like, here with sigma=1.6) - Format: {VirtualPlaceProb, LoopClosureProb, NeighborLvl1, NeighborLvl2, ...}.");
@@ -344,7 +347,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(VhEp, RansacParam2, float, 0.99, "Fundamental matrix (see cvFindFundamentalMat()): Performance of RANSAC.");
// RGB-D SLAM
RTABMAP_PARAM(RGBD, Enabled, bool, true, "");
RTABMAP_PARAM(RGBD, Enabled, bool, true, "Activate metric SLAM. If set to false, classic RTAB-Map loop closure detection is done using only images and without any metric information.");
RTABMAP_PARAM(RGBD, LinearUpdate, float, 0.1, "Minimum linear displacement (m) to update the map. Rehearsal is done prior to this, so weights are still updated.");
RTABMAP_PARAM(RGBD, AngularUpdate, float, 0.1, "Minimum angular displacement (rad) to update the map. Rehearsal is done prior to this, so weights are still updated.");
RTABMAP_PARAM(RGBD, LinearSpeedUpdate, float, 0.0, "Maximum linear speed (m/s) to update the map (0 means not limit).");
@@ -353,7 +356,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, OptimizeFromGraphEnd, bool, false, "Optimize graph from the newest node. If false, the graph is optimized from the oldest node of the current graph (this adds an overhead computation to detect to oldest node of the current graph, but it can be useful to preserve the map referential from the oldest node). Warning when set to false: when some nodes are transferred, the first referential of the local map may change, resulting in momentary changes in robot/map position (which are annoying in teleoperation).");
RTABMAP_PARAM(RGBD, OptimizeMaxError, float, 3.0, uFormat("Reject loop closures if optimization error ratio is greater than this value (0=disabled). Ratio is computed as absolute error over standard deviation of each link. This will help to detect when a wrong loop closure is added to the graph. Not compatible with \"%s\" if enabled.", kOptimizerRobust().c_str()));
RTABMAP_PARAM(RGBD, MaxLoopClosureDistance, float, 0.0, "Reject loop closures/localizations if the distance from the map is over this distance (0=disabled).");
RTABMAP_PARAM(RGBD, SavedLocalizationIgnored, bool, false, "Ignore last saved localization pose from previous session. If true, RTAB-Map won't assume it is restarting from the same place than where it shut down previously.");
RTABMAP_PARAM(RGBD, StartAtOrigin, bool, false, uFormat("If true, rtabmap will assume the robot is starting from origin of the map. If false, rtabmap will assume the robot is restarting from the last saved localization pose from previous session (the place where it shut down previously). Used only in localization mode (%s=false).", kMemIncrementalMemory().c_str()));
RTABMAP_PARAM(RGBD, GoalReachedRadius, float, 0.5, "Goal reached radius (m).");
RTABMAP_PARAM(RGBD, PlanStuckIterations, int, 0, "Mark the current goal node on the path as unreachable if it is not updated after X iterations (0=disabled). If all upcoming nodes on the path are unreachabled, the plan fails.");
RTABMAP_PARAM(RGBD, PlanLinearVelocity, float, 0, "Linear velocity (m/sec) used to compute path weights.");
@@ -362,8 +365,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, MaxLocalRetrieved, unsigned int, 2, "Maximum local locations retrieved (0=disabled) near the current pose in the local map or on the current planned path (those on the planned path have priority).");
RTABMAP_PARAM(RGBD, LocalRadius, float, 10, "Local radius (m) for nodes selection in the local map. This parameter is used in some approaches about the local map management.");
RTABMAP_PARAM(RGBD, LocalImmunizationRatio, float, 0.25, "Ratio of working memory for which local nodes are immunized from transfer.");
RTABMAP_PARAM(RGBD, ScanMatchingIdsSavedInLinks, bool, true, "Save scan matching IDs in link's user data.");
RTABMAP_PARAM(RGBD, ScanMatchingIdsSavedInLinks, bool, true, "Save scan matching IDs from one-to-many proximity detection in link's user data.");
RTABMAP_PARAM(RGBD, NeighborLinkRefining, bool, false, uFormat("When a new node is added to the graph, the transformation of its neighbor link to the previous node is refined using registration approach selected (%s).", kRegStrategy().c_str()));
RTABMAP_PARAM(RGBD, LoopClosureIdentityGuess, bool, false, uFormat("Use Identity matrix as guess when computing loop closure transform, otherwise no guess is used, thus assuming that registration strategy selected (%s) can deal with transformation estimation without guess.", kRegStrategy().c_str()));
RTABMAP_PARAM(RGBD, LoopClosureReextractFeatures, bool, false, "Extract features even if there are some already in the nodes.");
RTABMAP_PARAM(RGBD, LocalBundleOnLoopClosure, bool, false, "Do local bundle adjustment with neighborhood of the loop closure.");
RTABMAP_PARAM(RGBD, CreateOccupancyGrid, bool, false, "Create local occupancy grid maps. See \"Grid\" group for parameters.");
@@ -375,12 +379,12 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, ProximityByTime, bool, false, "Detection over all locations in STM.");
RTABMAP_PARAM(RGBD, ProximityBySpace, bool, true, "Detection over locations (in Working Memory) near in space.");
RTABMAP_PARAM(RGBD, ProximityMaxGraphDepth, int, 50, "Maximum depth from the current/last loop closure location and the local loop closure hypotheses. Set 0 to ignore.");
RTABMAP_PARAM(RGBD, ProximityMaxPaths, int, 3, "Maximum paths compared (from the most recent) for proximity detection by space. 0 means no limit.");
RTABMAP_PARAM(RGBD, ProximityPathFilteringRadius, float, 1, "Path filtering radius to reduce the number of nodes to compare in a path. A path should also be inside that radius to be considered for proximity detection.");
RTABMAP_PARAM(RGBD, ProximityPathMaxNeighbors, int, 0, "Maximum neighbor nodes compared on each path. Set to 0 to disable merging the laser scans.");
RTABMAP_PARAM(RGBD, ProximityPathRawPosesUsed, bool, true, "When comparing to a local path, merge the scan using the odometry poses (with neighbor link optimizations) instead of the ones in the optimized local graph.");
RTABMAP_PARAM(RGBD, ProximityAngle, float, 45, "Maximum angle (degrees) for visual proximity detection.");
RTABMAP_PARAM(RGBD, ProximityOdomGuess, bool, false, "Use odometry as motion guess for visual proximity detection.");
RTABMAP_PARAM(RGBD, ProximityMaxPaths, int, 3, "Maximum paths compared (from the most recent) for proximity detection. 0 means no limit.");
RTABMAP_PARAM(RGBD, ProximityPathFilteringRadius, float, 1, "Path filtering radius to reduce the number of nodes to compare in a path in one-to-many proximity detection. The nearest node in a path should be inside that radius to be considered for one-to-one proximity detection.");
RTABMAP_PARAM(RGBD, ProximityPathMaxNeighbors, int, 0, "Maximum neighbor nodes compared on each path for one-to-many proximity detection. Set to 0 to disable one-to-many proximity detection (by merging the laser scans).");
RTABMAP_PARAM(RGBD, ProximityPathRawPosesUsed, bool, true, "When comparing to a local path for one-to-many proximity detection, merge the scans using the odometry poses (with neighbor link optimizations) instead of the ones in the optimized local graph.");
RTABMAP_PARAM(RGBD, ProximityAngle, float, 45, "Maximum angle (degrees) for one-to-one proximity detection.");
RTABMAP_PARAM(RGBD, ProximityOdomGuess, bool, false, "Use odometry as motion guess for one-to-one proximity detection.");
// Graph optimization
#ifdef RTABMAP_GTSAM
@@ -408,9 +412,13 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Optimizer, Robust, bool, false, uFormat("Robust graph optimization using Vertigo (only work for g2o and GTSAM optimization strategies). Not compatible with \"%s\" if enabled.", kRGBDOptimizeMaxError().c_str()));
RTABMAP_PARAM(Optimizer, PriorsIgnored, bool, true, "Ignore prior constraints (global pose or GPS) while optimizing. Currently only g2o and gtsam optimization supports this.");
RTABMAP_PARAM(Optimizer, LandmarksIgnored, bool, false, "Ignore landmark constraints while optimizing. Currently only g2o and gtsam optimization supports this.");
#if defined(RTABMAP_G2O) || defined(RTABMAP_GTSAM)
RTABMAP_PARAM(Optimizer, GravitySigma, float, 0.3, uFormat("Gravity sigma value (>=0, typically between 0.1 and 0.3). Optimization is done while preserving gravity orientation of the poses. This should be used only with visual/lidar inertial odometry approaches, for which we assume that all odometry poses are aligned with gravity. Set to 0 to disable gravity constraints. Currently supported only with g2o and GTSAM optimization strategies (see %s).", kOptimizerStrategy().c_str()));
#else
RTABMAP_PARAM(Optimizer, GravitySigma, float, 0.0, uFormat("Gravity sigma value (>=0, typically between 0.1 and 0.3). Optimization is done while preserving gravity orientation of the poses. This should be used only with visual/lidar inertial odometry approaches, for which we assume that all odometry poses are aligned with gravity. Set to 0 to disable gravity constraints. Currently supported only with g2o and GTSAM optimization strategies (see %s).", kOptimizerStrategy().c_str()));
#endif
#ifdef RTABMAP_ORB_SLAM2
#ifdef RTABMAP_ORB_SLAM
RTABMAP_PARAM(g2o, Solver, int, 3, "0=csparse 1=pcg 2=cholmod 3=Eigen");
#else
RTABMAP_PARAM(g2o, Solver, int, 0, "0=csparse 1=pcg 2=cholmod 3=Eigen");
@@ -452,7 +460,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(OdomF2M, ScanSubtractAngle, float, 45, uFormat("[Geometry] Max angle (degrees) used to filter points of a new added scan to local map (when \"%s\">0). 0 means any angle.", kOdomF2MScanSubtractRadius().c_str()).c_str());
RTABMAP_PARAM(OdomF2M, ScanRange, float, 0, "[Geometry] Distance Range used to filter points of local map (when > 0). 0 means local map is updated using time and not range.");
RTABMAP_PARAM(OdomF2M, ValidDepthRatio, float, 0.75, "If a new frame has points without valid depth, they are added to local feature map only if points with valid depth on total points is over this ratio. Setting to 1 means no points without valid depth are added to local feature map.");
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2)
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM)
RTABMAP_PARAM(OdomF2M, BundleAdjustment, int, 1, "Local bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
#else
RTABMAP_PARAM(OdomF2M, BundleAdjustment, int, 0, "Local bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
@@ -513,12 +521,12 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(OdomViso2, BucketHeight, double, 50, "Height of bucket.");
// Odometry ORB_SLAM2
RTABMAP_PARAM_STR(OdomORBSLAM2, VocPath, "", "Path to ORB vocabulary (*.txt).");
RTABMAP_PARAM(OdomORBSLAM2, Bf, double, 0.076, "Fake IR projector baseline (m) used only when stereo is not used.");
RTABMAP_PARAM(OdomORBSLAM2, ThDepth, double, 40.0, "Close/Far threshold. Baseline times.");
RTABMAP_PARAM(OdomORBSLAM2, Fps, float, 0.0, "Camera FPS.");
RTABMAP_PARAM(OdomORBSLAM2, MaxFeatures, int, 1000, "Maximum ORB features extracted per frame.");
RTABMAP_PARAM(OdomORBSLAM2, MapSize, int, 3000, "Maximum size of the feature map (0 means infinite).");
RTABMAP_PARAM_STR(OdomORBSLAM, VocPath, "", "Path to ORB vocabulary (*.txt).");
RTABMAP_PARAM(OdomORBSLAM, Bf, double, 0.076, "Fake IR projector baseline (m) used only when stereo is not used.");
RTABMAP_PARAM(OdomORBSLAM, ThDepth, double, 40.0, "Close/Far threshold. Baseline times.");
RTABMAP_PARAM(OdomORBSLAM, Fps, float, 0.0, "Camera FPS.");
RTABMAP_PARAM(OdomORBSLAM, MaxFeatures, int, 1000, "Maximum ORB features extracted per frame.");
RTABMAP_PARAM(OdomORBSLAM, MapSize, int, 3000, "Maximum size of the feature map (0 means infinite).");
// Odometry OKVIS
RTABMAP_PARAM_STR(OdomOKVIS, ConfigPath, "", "Path of OKVIS config file.");
@@ -574,7 +582,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, RefineIterations, int, 5, uFormat("[%s = 0] Number of iterations used to refine the transformation found by RANSAC. 0 means that the transformation is not refined.", kVisEstimationType().c_str()));
RTABMAP_PARAM(Vis, PnPReprojError, float, 2, uFormat("[%s = 1] PnP reprojection error.", kVisEstimationType().c_str()));
RTABMAP_PARAM(Vis, PnPFlags, int, 0, uFormat("[%s = 1] PnP flags: 0=Iterative, 1=EPNP, 2=P3P", kVisEstimationType().c_str()));
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2)
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM)
RTABMAP_PARAM(Vis, PnPRefineIterations, int, 0, uFormat("[%s = 1] Refine iterations. Set to 0 if \"%s\" is also used.", kVisEstimationType().c_str(), kVisBundleAdjustment().c_str()));
#else
RTABMAP_PARAM(Vis, PnPRefineIterations, int, 1, uFormat("[%s = 1] Refine iterations. Set to 0 if \"%s\" is also used.", kVisEstimationType().c_str(), kVisBundleAdjustment().c_str()));
@@ -588,9 +596,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, Iterations, int, 300, "Maximum iterations to compute the transform.");
#if CV_MAJOR_VERSION > 2 && !defined(HAVE_OPENCV_XFEATURES2D)
// OpenCV>2 without xFeatures2D module doesn't have BRIEF
RTABMAP_PARAM(Vis, FeatureType, int, 8, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY");
RTABMAP_PARAM(Vis, FeatureType, int, 8, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#else
RTABMAP_PARAM(Vis, FeatureType, int, 6, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY");
RTABMAP_PARAM(Vis, FeatureType, int, 6, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#endif
RTABMAP_PARAM(Vis, MaxFeatures, int, 1000, "0 no limits.");
RTABMAP_PARAM(Vis, MaxDepth, float, 0, "Max depth of the features (0 means no limit).");
@@ -605,20 +613,20 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, CorType, int, 0, "Correspondences computation approach: 0=Features Matching, 1=Optical Flow");
RTABMAP_PARAM(Vis, CorNNType, int, 1, uFormat("[%s=0] kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4, BruteForceCrossCheck=5, SuperGlue=6, GMS=7. Used for features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorNNDR, float, 0.8, uFormat("[%s=0] NNDR: nearest neighbor distance ratio. Used for knn features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessWinSize, int, 20, uFormat("[%s=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences. 0 means disabled.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessWinSize, int, 40, uFormat("[%s=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences. 0 means disabled.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessMatchToProjection, bool, false, uFormat("[%s=0] Match frame's corners to source's projected points (when guess transform is provided) instead of projected points to frame's corners.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowWinSize, int, 16, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowIterations, int, 30, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowEps, float, 0.01, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowMaxLevel, int, 3, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2)
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM)
RTABMAP_PARAM(Vis, BundleAdjustment, int, 1, "Optimization with bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
#else
RTABMAP_PARAM(Vis, BundleAdjustment, int, 0, "Optimization with bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
#endif
// Features matching approaches
RTABMAP_PARAM_STR(PyMatcher, Path, "", "Path to python script file (see available ones in rtabmap/corelib/src/pymatcher/*). See the header to see where the script should be copied.");
RTABMAP_PARAM_STR(PyMatcher, Path, "", "Path to python script file (see available ones in rtabmap/corelib/src/python/*). See the header to see where the script should be copied.");
RTABMAP_PARAM(PyMatcher, Iterations, int, 20, "Sinkhorn iterations. Used by SuperGlue.");
RTABMAP_PARAM(PyMatcher, Threshold, float, 0.2, "Used by SuperGlue.");
RTABMAP_PARAM(PyMatcher, Cuda, bool, true, "Used by SuperGlue.");
@@ -629,9 +637,14 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(GMS, ThresholdFactor, double, 6.0, "The higher, the less matches.");
// ICP registration parameters
#ifdef RTABMAP_POINTMATCHER
RTABMAP_PARAM(Icp, Strategy, int, 1, "ICP implementation: 0=Point Cloud Library, 1=libpointmatcher, 2=CCCoreLib (CloudCompare).");
#else
RTABMAP_PARAM(Icp, Strategy, int, 0, "ICP implementation: 0=Point Cloud Library, 1=libpointmatcher, 2=CCCoreLib (CloudCompare).");
#endif
RTABMAP_PARAM(Icp, MaxTranslation, float, 0.2, "Maximum ICP translation correction accepted (m).");
RTABMAP_PARAM(Icp, MaxRotation, float, 0.78, "Maximum ICP rotation correction accepted (rad).");
RTABMAP_PARAM(Icp, VoxelSize, float, 0.0, "Uniform sampling voxel size (0=disabled).");
RTABMAP_PARAM(Icp, VoxelSize, float, 0.05, "Uniform sampling voxel size (0=disabled).");
RTABMAP_PARAM(Icp, DownsamplingStep, int, 1, "Downsampling step size (1=no sampling). This is done before uniform sampling.");
RTABMAP_PARAM(Icp, RangeMin, float, 0, "Minimum range filtering (0=disabled).");
RTABMAP_PARAM(Icp, RangeMax, float, 0, "Maximum range filtering (0=disabled).");
@@ -643,6 +656,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Icp, Iterations, int, 30, "Max iterations.");
RTABMAP_PARAM(Icp, Epsilon, float, 0, "Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.");
RTABMAP_PARAM(Icp, CorrespondenceRatio, float, 0.1, "Ratio of matching correspondences to accept the transform.");
RTABMAP_PARAM(Icp, Force4DoF, bool, false, uFormat("Limit ICP to x, y, z and yaw DoF. Available if %s > 0.", kIcpStrategy().c_str()));
#ifdef RTABMAP_POINTMATCHER
RTABMAP_PARAM(Icp, PointToPlane, bool, true, "Use point to plane ICP.");
#else
@@ -653,18 +667,17 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Icp, PointToPlaneGroundNormalsUp, float, 0.0, "Invert normals on ground if they are pointing down (useful for ring-like 3D LiDARs). 0 means disabled, 1 means only normals perfectly aligned with -z axis. This is only done with 3D scans.");
RTABMAP_PARAM(Icp, PointToPlaneMinComplexity, float, 0.02, uFormat("Minimum structural complexity (0.0=low, 1.0=high) of the scan to do PointToPlane registration, otherwise PointToPoint registration is done instead and strategy from %s is used. This check is done only when %s=true.", kIcpPointToPlaneLowComplexityStrategy().c_str(), kIcpPointToPlane().c_str()));
RTABMAP_PARAM(Icp, PointToPlaneLowComplexityStrategy, int, 1, uFormat("If structural complexity is below %s: set to 0 to so that the transform is automatically rejected, set to 1 to limit ICP correction in axes with most constraints (e.g., for a corridor-like environment, the resulting transform will be limited in y and yaw, x will taken from the guess), set to 2 to accept \"as is\" the transform computed by PointToPoint.", kIcpPointToPlaneMinComplexity().c_str()));
RTABMAP_PARAM(Icp, OutlierRatio, float, 0.85, uFormat("Outlier ratio used with %s>0. For libpointmatcher, this parameter set TrimmedDistOutlierFilter/ratio for convenience when configuration file is not set. For CCCoreLib, this parameter set the \"finalOverlapRatio\". The value should be between 0 and 1.", kIcpStrategy().c_str()));
// libpointmatcher
#ifdef RTABMAP_POINTMATCHER
RTABMAP_PARAM(Icp, PM, bool, true, "Use libpointmatcher for ICP registration instead of PCL's implementation.");
#else
RTABMAP_PARAM(Icp, PM, bool, false, "Use libpointmatcher for ICP registration instead of PCL's implementation.");
#endif
RTABMAP_PARAM_STR(Icp, PMConfig, "", uFormat("Configuration file (*.yaml) used by libpointmatcher. Note that data filters set for libpointmatcher are done after filtering done by rtabmap (i.e., %s, %s), so make sure to disable those in rtabmap if you want to use only those from libpointmatcher. Parameters %s, %s and %s are also ignored if configuration file is set.", kIcpVoxelSize().c_str(), kIcpDownsamplingStep().c_str(), kIcpIterations().c_str(), kIcpEpsilon().c_str(), kIcpMaxCorrespondenceDistance().c_str()).c_str());
RTABMAP_PARAM(Icp, PMMatcherKnn, int, 1, "KDTreeMatcher/knn: number of nearest neighbors to consider it the reference. For convenience when configuration file is not set.");
RTABMAP_PARAM(Icp, PMMatcherEpsilon, float, 0.0, "KDTreeMatcher/epsilon: approximation to use for the nearest-neighbor search. For convenience when configuration file is not set.");
RTABMAP_PARAM(Icp, PMMatcherIntensity, bool, false, uFormat("KDTreeMatcher: among nearest neighbors, keep only the one with the most similar intensity. This only work with %s>1.", kIcpPMMatcherKnn().c_str()));
RTABMAP_PARAM(Icp, PMOutlierRatio, float, 0.95, "TrimmedDistOutlierFilter/ratio: For convenience when configuration file is not set. For kinect-like point cloud, use 0.65.");
RTABMAP_PARAM(Icp, CCSamplingLimit, unsigned int, 50000, "Maximum number of points per cloud (they are randomly resampled below this limit otherwise).");
RTABMAP_PARAM(Icp, CCFilterOutFarthestPoints, bool, false, "If true, the algorithm will automatically ignore farthest points from the reference, for better convergence.");
RTABMAP_PARAM(Icp, CCMaxFinalRMS, float, 0.2, "Maximum final RMS error.");
// Stereo disparity
RTABMAP_PARAM(Stereo, WinWidth, int, 15, "Window width.");
@@ -745,6 +758,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(GridGlobal, MinSize, float, 0.0, "Minimum map size (m).");
RTABMAP_PARAM(GridGlobal, Eroded, bool, false, "Erode obstacle cells.");
RTABMAP_PARAM(GridGlobal, MaxNodes, int, 0, "Maximum nodes assembled in the map starting from the last node (0=unlimited).");
RTABMAP_PARAM(GridGlobal, AltitudeDelta, float, 0, "Assemble only nodes that have the same altitude of +-delta meters of the current pose (0=disabled). This is used to generate 2D occupancy grid based on the current altitude (e.g., multi-floor building).");
RTABMAP_PARAM(GridGlobal, OccupancyThr, float, 0.5, "Occupancy threshold (value between 0 and 1).");
RTABMAP_PARAM(GridGlobal, ProbHit, float, 0.7, "Probability of a hit (value between 0.5 and 1).");
RTABMAP_PARAM(GridGlobal, ProbMiss, float, 0.4, "Probability of a miss (value between 0 and 0.5).");

View File

@@ -0,0 +1,41 @@
/*
* PythonInterface.h
*
* Created on: Jan. 14, 2021
* Author: mathieu
*/
#ifndef CORELIB_SRC_PYTHON_PYTHONINTERFACE_H_
#define CORELIB_SRC_PYTHON_PYTHONINTERFACE_H_
#include <string>
#include <rtabmap/utilite/UMutex.h>
#include <Python.h>
namespace rtabmap {
class PythonInterface
{
public:
PythonInterface();
virtual ~PythonInterface();
protected:
std::string getTraceback(); // should be called between lock() and unlock()
void lock();
void unlock();
private:
static UMutex mutex_;
static int refCount_;
protected:
static PyThreadState * mainThreadState_;
static unsigned long mainThreadID_;
PyThreadState * threadState_;
};
}
#endif /* CORELIB_SRC_PYTHON_PYTHONINTERFACE_H_ */

View File

@@ -56,6 +56,7 @@ protected:
virtual float getMinGeometryCorrespondencesRatioImpl() const {return _correspondenceRatio;}
private:
int _strategy;
float _maxTranslation;
float _maxRotation;
float _voxelSize;
@@ -66,19 +67,24 @@ private:
int _maxIterations;
float _epsilon;
float _correspondenceRatio;
bool _force4DoF;
bool _pointToPlane;
int _pointToPlaneK;
float _pointToPlaneRadius;
float _pointToPlaneGroundNormalsUp;
float _pointToPlaneMinComplexity;
int _pointToPlaneLowComplexityStrategy;
bool _libpointmatcher;
std::string _libpointmatcherConfig;
int _libpointmatcherKnn;
float _libpointmatcherEpsilon;
bool _libpointmatcherIntensity;
float _libpointmatcherOutlierRatio;
float _outlierRatio;
unsigned int _ccSamplingLimit;
bool _ccFilterOutFarthestPoints;
double _ccMaxFinalRMS;
void * _libpointmatcherICP;
void * _libpointmatcherICPFilters;
};
}

View File

@@ -37,7 +37,7 @@ namespace rtabmap {
class Feature2D;
#ifdef RTABMAP_PYMATCHER
#ifdef RTABMAP_PYTHON
class PyMatcher;
#endif
@@ -105,7 +105,7 @@ private:
Feature2D * _detectorFrom;
Feature2D * _detectorTo;
#ifdef RTABMAP_PYMATCHER
#ifdef RTABMAP_PYTHON
PyMatcher * _pyMatcher;
#endif
};

View File

@@ -199,12 +199,13 @@ public:
std::map<int, Transform> getNodesInRadius(const Transform & pose, float radius); // If radius=0, RGBD/LocalRadius is used. Can return landmarks.
std::map<int, Transform> getNodesInRadius(int nodeId, float radius); // If nodeId==0, return poses around latest node. If radius=0, RGBD/LocalRadius is used. Can return landmarks and use landmark id (negative) as request.
int detectMoreLoopClosures(
float clusterRadius = 0.5f,
float clusterRadiusMax = 0.5f,
float clusterAngle = M_PI/6.0f,
int iterations = 1,
bool intraSession = true,
bool interSession = true,
const ProgressState * state = 0);
const ProgressState * state = 0,
float clusterRadiusMin = 0.0f);
int refineLinks();
bool addLink(const Link & link);
cv::Mat getInformation(const cv::Mat & covariance) const;
@@ -281,6 +282,7 @@ private:
bool _proximityByTime;
bool _proximityBySpace;
bool _scanMatchingIdsSavedInLinks;
bool _loopClosureIdentityGuess;
float _localRadius;
float _localImmunizationRatio;
int _proximityMaxGraphDepth;
@@ -300,7 +302,7 @@ private:
int _pathStuckIterations;
float _pathLinearVelocity;
float _pathAngularVelocity;
bool _savedLocalizationIgnored;
bool _restartAtOrigin;
bool _loopCovLimited;
bool _loopGPS;
int _maxOdomCacheSize;

View File

@@ -140,6 +140,8 @@ private:
cv::Mat F_;
};
RTABMAP_EXP std::ostream& operator<<(std::ostream& os, const StereoCameraModel& model);
} // rtabmap
#endif /* STEREOCAMERAMODEL_H_ */

View File

@@ -0,0 +1,83 @@
/*
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#include "rtabmap/core/RtabmapExp.h" // DLL export/import defines
#include "rtabmap/core/StereoCameraModel.h"
#include "rtabmap/core/Camera.h"
#include "rtabmap/core/Version.h"
#ifdef RTABMAP_DEPTHAI
#ifndef DEPTHAI_OPENCV_SUPPORT
#define DEPTHAI_OPENCV_SUPPORT
#endif
#include <depthai/depthai.hpp>
#endif
namespace rtabmap
{
class RTABMAP_EXP CameraDepthAI :
public Camera
{
public:
static bool available();
public:
CameraDepthAI(
const std::string & deviceSerial = "",
int resolution = 1, // 0=720p, 1=800p, 2=400p
float imageRate=0.0f,
const Transform & localTransform = CameraModel::opticalRotation());
virtual ~CameraDepthAI();
void setOutputDepth(bool enabled, int confidence = 200);
virtual bool init(const std::string & calibrationFolder = ".", const std::string & cameraName = "");
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
private:
#ifdef RTABMAP_DEPTHAI
StereoCameraModel stereoModel_;
std::string deviceSerial_;
bool outputDepth_;
int depthConfidence_;
int resolution_;
std::shared_ptr<dai::Device> device_;
std::shared_ptr<dai::DataOutputQueue> leftQueue_;
std::shared_ptr<dai::DataOutputQueue> rightOrDepthQueue_;
#endif
};
} // namespace rtabmap

View File

@@ -36,6 +36,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <pcl/pcl_config.h>
#ifdef RTABMAP_REALSENSE2
#include <librealsense2/rs.hpp>
#include <librealsense2/hpp/rs_frame.hpp>
#endif
@@ -75,6 +76,7 @@ public:
void setEmitterEnabled(bool enabled);
void setIRFormat(bool enabled, bool useDepthInsteadOfRightImage);
void setResolution(int width, int height, int fps = 30);
void setDepthResolution(int width, int height, int fps = 30);
void setGlobalTimeSync(bool enabled);
void publishInterIMU(bool enabled);
void setDualMode(bool enabled, const Transform & extrinsics);
@@ -85,6 +87,7 @@ public:
#ifdef RTABMAP_REALSENSE2
private:
void close();
void imu_callback(rs2::frame frame);
void pose_callback(rs2::frame frame);
void frame_callback(rs2::frame frame);
@@ -102,14 +105,14 @@ protected:
private:
#ifdef RTABMAP_REALSENSE2
rs2::context * ctx_;
std::vector<rs2::device *> dev_;
rs2::context ctx_;
std::vector<rs2::device> dev_;
std::string deviceId_;
rs2::syncer * syncer_;
rs2::syncer syncer_;
float depth_scale_meters_;
rs2_intrinsics * depthIntrinsics_;
rs2_intrinsics * rgbIntrinsics_;
rs2_extrinsics * depthToRGBExtrinsics_;
rs2_intrinsics depthIntrinsics_;
rs2_intrinsics rgbIntrinsics_;
rs2_extrinsics depthToRGBExtrinsics_;
cv::Mat depthBuffer_;
cv::Mat rgbBuffer_;
CameraModel model_;
@@ -132,13 +135,15 @@ private:
int cameraWidth_;
int cameraHeight_;
int cameraFps_;
int cameraDepthWidth_;
int cameraDepthHeight_;
int cameraDepthFps_;
bool globalTimeSync_;
bool publishInterIMU_;
bool dualMode_;
Transform dualExtrinsics_;
std::string jsonConfig_;
bool closing_;
bool isL500_;
static Transform realsense2PoseRotation_;
static Transform realsense2PoseRotationInv_;

View File

@@ -70,6 +70,8 @@ public:
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
void setResolution(int width, int height) {_width=width, _height=height;}
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
@@ -84,6 +86,8 @@ private:
CameraVideo::Source src_;
int usbDevice_;
int usbDevice2_;
int _width;
int _height;
};
} // namespace rtabmap

View File

@@ -0,0 +1,83 @@
/*
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#include "rtabmap/core/RtabmapExp.h" // DLL export/import defines
#include "rtabmap/core/StereoCameraModel.h"
#include "rtabmap/core/Camera.h"
#include "rtabmap/core/Version.h"
namespace sl_oc {
namespace video {
class VideoCapture;
}
namespace sensors {
class SensorCapture;
}
}
namespace rtabmap
{
class ZedOCThread;
class RTABMAP_EXP CameraStereoZedOC :
public Camera
{
public:
static bool available();
public:
CameraStereoZedOC(
int deviceId,
int resolution = 3, // 0=HD2K, 1=HD1080, 2=HD720, 3=VGA
float imageRate=0.0f,
const Transform & localTransform = CameraModel::opticalRotation());
virtual ~CameraStereoZedOC();
virtual bool init(const std::string & calibrationFolder = ".", const std::string & cameraName = "");
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
private:
#ifdef RTABMAP_ZEDOC
sl_oc::video::VideoCapture * zed_;
sl_oc::sensors::SensorCapture * sensors_;
ZedOCThread * imuThread_;
StereoCameraModel stereoModel_;
int usbDevice_;
int resolution_;
uint64_t lastStamp_;
#endif
};
} // namespace rtabmap

View File

@@ -50,7 +50,6 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
const Signature & getMap() const {return *map_;}
const Signature & getLastFrame() const {return *lastFrame_;}
virtual bool canProcessIMU() const;
virtual Odometry::Type getType() {return Odometry::kTypeF2M;}
@@ -79,7 +78,6 @@ private:
Signature * lastFrame_;
int lastFrameOldestNewId_;
std::vector<std::pair<pcl::PointCloud<pcl::PointXYZINormal>::Ptr, pcl::IndicesPtr> > scansBuffer_;
bool initGravity_;
std::map<int, std::map<int, FeatureBA> > bundleWordReferences_; //<WordId, <FrameId, pt2D+depth>>
std::map<int, Transform> bundlePoses_;

View File

@@ -44,7 +44,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeMSCKF;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessIMU() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);

View File

@@ -25,41 +25,48 @@ ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef ODOMETRYORBSLAM2_H_
#define ODOMETRYORBSLAM2_H_
#ifndef ODOMETRYORBSLAM_H_
#define ODOMETRYORBSLAM_H_
#include <rtabmap/core/Odometry.h>
#if RTABMAP_ORB_SLAM == 3
namespace ORB_SLAM3 {
#else
namespace ORB_SLAM2 {
#endif
class System;
}
class ORBSLAM2System;
class ORBSLAMSystem;
namespace rtabmap {
class RTABMAP_EXP OdometryORBSLAM2 : public Odometry
class RTABMAP_EXP OdometryORBSLAM : public Odometry
{
public:
OdometryORBSLAM2(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryORBSLAM2();
OdometryORBSLAM(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryORBSLAM();
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeORBSLAM2;}
virtual Odometry::Type getType() {return Odometry::kTypeORBSLAM;}
virtual bool canProcessAsyncIMU() const;
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
private:
#ifdef RTABMAP_ORB_SLAM2
ORBSLAM2System * orbslam2_;
#ifdef RTABMAP_ORB_SLAM
ORBSLAMSystem * orbslam_;
bool firstFrame_;
Transform originLocalTransform_;
Transform previousPose_;
bool useIMU_;
Transform imuLocalTransform_;
#endif
};
}
#endif /* ODOMETRYORBSLAM2_H_ */
#endif /* ODOMETRYORBSLAM_H_ */

View File

@@ -46,7 +46,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeOkvis;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessIMU() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);

View File

@@ -1,5 +1,5 @@
/*
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
@@ -25,42 +25,42 @@ ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef OBJDELETIONHANDLER_H_
#define OBJDELETIONHANDLER_H_
#ifndef ODOMETRYOPENVINS_H_
#define ODOMETRYOPENVINS_H_
#include "rtabmap/utilite/UEventsHandler.h"
#include "rtabmap/utilite/UEvent.h"
#include <QtCore/QObject>
#include <rtabmap/core/Odometry.h>
class ObjDeletionHandler : public QObject, public UEventsHandler
namespace ov_msckf {
class VioManager;
}
namespace rtabmap {
class RTABMAP_EXP OdometryOpenVINS : public Odometry
{
Q_OBJECT
public:
ObjDeletionHandler(int watchedId, QObject * receiver = 0, const char * member = 0) : _watchedId(watchedId)
{
if(receiver && member)
{
connect(this, SIGNAL(objDeletionEventReceived(int)), receiver, member);
}
}
virtual ~ObjDeletionHandler() {}
OdometryOpenVINS(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryOpenVINS();
Q_SIGNALS:
void objDeletionEventReceived(int);
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeOpenVINS;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
protected:
virtual bool handleEvent(UEvent * event)
{
if(event->getClassName().compare("UObjDeletedEvent") == 0 &&
event->getCode() == _watchedId)
{
Q_EMIT objDeletionEventReceived(_watchedId);
}
return false;
}
private:
int _watchedId;
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
private:
#ifdef RTABMAP_OPENVINS
ov_msckf::VioManager * vioManager_;
bool initGravity_;
Transform previousPose_;
Transform previousLocalTransform_;
Transform imuLocalTransform_;
std::map<double, IMU> imuBuffer_;
#endif
};
#endif /* OBJDELETIONHANDLER_H_ */
}
#endif /* ODOMETRYOPENVINS_H_ */

View File

@@ -43,7 +43,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeVINS;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessIMU() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
@@ -51,7 +51,6 @@ private:
private:
#ifdef RTABMAP_VINS
VinsEstimator * vinsEstimator_;
int imagesProcessed_;
bool initGravity_;
Transform previousPose_;
Transform previousLocalTransform_;

View File

@@ -38,6 +38,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <rtabmap/core/SensorData.h>
#include <rtabmap/core/Parameters.h>
#include <opencv2/core/core.hpp>
#include <rtabmap/core/ProgressState.h>
#include <map>
#include <list>
@@ -198,35 +199,36 @@ pcl::PointCloud<pcl::PointXYZ> RTABMAP_EXP laserScanFromDepthImages(
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PCLPointCloud2 & cloud, bool filterNaNs = true, bool is2D = false, const Transform & transform = Transform());
// return CV_32FC3 (x,y,z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC6 (x,y,z,normal_x,normal_y,normal_z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC4 (x,y,z,rgb)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC4 (x,y,z,I)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC7 (x,y,z,rgb,normal_x,normal_y,normal_z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC7 (x,y,z,I,normal_x,normal_y,normal_z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC2 (x,y)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC3 (x,y,I)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC5 (x,y,normal_x, normal_y, normal_z)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC6 (x,y,I,normal_x, normal_y, normal_z)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
pcl::PCLPointCloud2::Ptr RTABMAP_EXP laserScanToPointCloud2(const LaserScan & laserScan, const Transform & transform = Transform());
// For 2d laserScan, z is set to null.
@@ -299,6 +301,33 @@ void RTABMAP_EXP fillProjectedCloudHoles(
bool verticalDirection,
bool fillToBorder);
/**
* For each point, return pixel of the best camera (NodeID->CameraIndex)
* looking at it based on the policy and parameters
*/
std::vector<std::pair< std::pair<int, int>, pcl::PointXY> > RTABMAP_EXP projectCloudToCameras (
const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud,
const std::map<int, Transform> & cameraPoses,
const std::map<int, std::vector<CameraModel> > & cameraModels,
float maxDistance = 0.0f,
float maxAngle = 0.0f,
const std::vector<float> & roiRatios = std::vector<float>(),
bool distanceToCamPolicy = false,
const ProgressState * state = 0);
/**
* For each point, return pixel of the best camera (NodeID->CameraIndex)
* looking at it based on the policy and parameters
*/
std::vector<std::pair< std::pair<int, int>, pcl::PointXY> > RTABMAP_EXP projectCloudToCameras (
const pcl::PointCloud<pcl::PointXYZINormal> & cloud,
const std::map<int, Transform> & cameraPoses,
const std::map<int, std::vector<CameraModel> > & cameraModels,
float maxDistance = 0.0f,
float maxAngle = 0.0f,
const std::vector<float> & roiRatios = std::vector<float>(),
bool distanceToCamPolicy = false,
const ProgressState * state = 0);
bool RTABMAP_EXP isFinite(const cv::Point3f & pt);
pcl::PointCloud<pcl::PointXYZ>::Ptr RTABMAP_EXP concatenateClouds(

View File

@@ -279,6 +279,20 @@ pcl::IndicesPtr RTABMAP_EXP cropBox(
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::IndicesPtr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::IndicesPtr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZ>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
const Eigen::Vector4f & min,
@@ -297,6 +311,12 @@ pcl::PointCloud<pcl::PointXYZRGB>::Ptr RTABMAP_EXP cropBox(
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZI>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZINormal>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const Eigen::Vector4f & min,
@@ -346,6 +366,8 @@ pcl::PointCloud<pcl::PointXYZRGB>::Ptr RTABMAP_EXP removeNaNFromPointCloud(
const pcl::PointCloud<pcl::PointXYZRGB>::Ptr & cloud);
pcl::PointCloud<pcl::PointXYZI>::Ptr RTABMAP_EXP removeNaNFromPointCloud(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud);
pcl::PCLPointCloud2::Ptr RTABMAP_EXP removeNaNFromPointCloud(
const pcl::PCLPointCloud2::Ptr & cloud);
pcl::PointCloud<pcl::PointNormal>::Ptr RTABMAP_EXP removeNaNNormalsFromPointCloud(
@@ -375,6 +397,14 @@ pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
float radiusSearch,
int minNeighborsInRadius);
pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
float radiusSearch,
int minNeighborsInRadius);
pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
float radiusSearch,
int minNeighborsInRadius);
/**
* @brief Wrapper of the pcl::RadiusOutlierRemoval class.
@@ -408,6 +438,16 @@ pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::IndicesPtr & indices,
float radiusSearch,
int minNeighborsInRadius);
pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float radiusSearch,
int minNeighborsInRadius);
pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float radiusSearch,
int minNeighborsInRadius);
/**
* For convenience.
@@ -590,6 +630,13 @@ pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float angleMax,
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const pcl::PointCloud<pcl::PointNormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
@@ -604,6 +651,13 @@ pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float angleMax,
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
/**
* For convenience.
@@ -661,6 +715,20 @@ std::vector<pcl::IndicesPtr> RTABMAP_EXP extractClusters(
int minClusterSize,
int maxClusterSize = std::numeric_limits<int>::max(),
int * biggestClusterIndex = 0);
std::vector<pcl::IndicesPtr> RTABMAP_EXP extractClusters(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float clusterTolerance,
int minClusterSize,
int maxClusterSize = std::numeric_limits<int>::max(),
int * biggestClusterIndex = 0);
std::vector<pcl::IndicesPtr> RTABMAP_EXP extractClusters(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float clusterTolerance,
int minClusterSize,
int maxClusterSize = std::numeric_limits<int>::max(),
int * biggestClusterIndex = 0);
pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
@@ -678,6 +746,14 @@ pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative);
pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative);
pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative);
pcl::PointCloud<pcl::PointXYZ>::Ptr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
@@ -700,6 +776,16 @@ pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr RTABMAP_EXP extractIndices(
const pcl::IndicesPtr & indices,
bool negative,
bool keepOrganized);
pcl::PointCloud<pcl::PointXYZI>::Ptr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative,
bool keepOrganized);
pcl::PointCloud<pcl::PointXYZINormal>::Ptr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative,
bool keepOrganized);
pcl::IndicesPtr extractPlane(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,

View File

@@ -99,6 +99,21 @@ RTABMAP_DEPRECATED(cv::Mat RTABMAP_EXP create2DMap(const std::map<int, Transform
float minMapSize = 0.0f,
float scanMaxRange = 0.0f), "Use interface with cv::Mat scans.");
/**
* Create 2d Occupancy grid (CV_8S)
* -1 = unknown
* 0 = empty space
* 100 = obstacle
* @param poses
* @param scans, should be CV_32FC2 type!
* @param viewpoints
* @param cellSize m
* @param unknownSpaceFilled if false no fill, otherwise a virtual laser sweeps the unknown space from each pose (stopping on detected obstacle)
* @param xMin
* @param yMin
* @param minMapSize minimum map size in meters
* @param scanMaxRange laser scan maximum range, would be set if unknownSpaceFilled=true
*/
cv::Mat RTABMAP_EXP create2DMap(const std::map<int, Transform> & poses,
const std::map<int, std::pair<cv::Mat, cv::Mat> > & scans, // <id, <hit, no hit> >, in /base_link frame
const std::map<int, cv::Point3f > & viewpoints, // /base_link -> /base_scan

View File

@@ -33,9 +33,11 @@ SET(SRC_FILES
camera/CameraStereoImages.cpp
camera/CameraStereoVideo.cpp
camera/CameraStereoZed.cpp
camera/CameraStereoZedOC.cpp
camera/CameraStereoTara.cpp
camera/CameraVideo.cpp
camera/CameraMyntEye.cpp
camera/CameraDepthAI.cpp
EpipolarGeometry.cpp
VisualWord.cpp
@@ -85,11 +87,13 @@ SET(SRC_FILES
odometry/OdometryViso2.cpp
odometry/OdometryDVO.cpp
odometry/OdometryOkvis.cpp
odometry/OdometryORBSLAM2.cpp
odometry/OdometryORBSLAM.cpp
odometry/OdometryLOAM.cpp
odometry/OdometryMSCKF.cpp
odometry/OdometryVINS.cpp
odometry/OdometryOpenVINS.cpp
IMU.cpp
IMUThread.cpp
IMUFilter.cpp
imufilter/ComplementaryFilter.cpp
@@ -195,11 +199,13 @@ IF(Python3_FOUND)
)
SET(SRC_FILES
${SRC_FILES}
pymatcher/PyMatcher.cpp
python/PythonInterface.cpp
python/PyMatcher.cpp
python/PyDetector.cpp
)
SET(INCLUDE_DIRS
${TORCH_INCLUDE_DIRS}
${CMAKE_CURRENT_SOURCE_DIR}/pymatcher
${CMAKE_CURRENT_SOURCE_DIR}/python
${INCLUDE_DIRS}
)
ENDIF(Python3_FOUND)
@@ -335,6 +341,14 @@ IF(mynteye_FOUND)
)
ENDIF(mynteye_FOUND)
IF(depthai_FOUND)
SET(LIBRARIES
${LIBRARIES}
depthai::depthai-core
depthai::depthai-opencv
)
ENDIF(depthai_FOUND)
IF(WITH_TORO)
SET(SRC_FILES
${SRC_FILES}
@@ -348,14 +362,29 @@ IF(WITH_TORO)
ENDIF(WITH_TORO)
IF(G2O_FOUND)
SET(INCLUDE_DIRS
IF(g2o_FOUND)
SET(LIBRARIES
${LIBRARIES}
g2o::core
g2o::solver_cholmod
g2o::solver_eigen
g2o::solver_pcg
g2o::solver_csparse
g2o::csparse_extension
g2o::types_slam2d
g2o::types_slam3d
g2o::types_sba
)
ELSE()
SET(INCLUDE_DIRS
${INCLUDE_DIRS}
${G2O_INCLUDE_DIRS}
)
SET(LIBRARIES
)
SET(LIBRARIES
${LIBRARIES}
${G2O_LIBRARIES}
)
)
ENDIF()
SET(SRC_FILES
${SRC_FILES}
optimizer/g2o/edge_se3_xyzprior.cpp
@@ -405,6 +434,13 @@ IF(libpointmatcher_FOUND)
)
ENDIF(libpointmatcher_FOUND)
IF(CCCoreLib_FOUND)
SET(LIBRARIES
${LIBRARIES}
CCCoreLib::CCCoreLib
)
ENDIF(CCCoreLib_FOUND)
IF(FastCV_FOUND)
SET(INCLUDE_DIRS
${INCLUDE_DIRS}
@@ -416,6 +452,25 @@ IF(FastCV_FOUND)
)
ENDIF(FastCV_FOUND)
IF(PDAL_FOUND)
SET(INCLUDE_DIRS
${INCLUDE_DIRS}
${PDAL_INCLUDE_DIRS}
)
SET(LIBRARIES
${LIBRARIES}
${PDAL_LIBRARIES}
)
SET(SRC_FILES
${SRC_FILES}
PDALWriter.cpp
)
IF(PDAL_VERSION VERSION_LESS "1.7")
add_definitions("-DRTABMAP_PDAL_16")
ENDIF(PDAL_VERSION VERSION_LESS "1.7")
ENDIF(PDAL_FOUND)
IF(loam_velodyne_FOUND)
SET(INCLUDE_DIRS
${INCLUDE_DIRS}
@@ -448,6 +503,19 @@ IF(ZED_FOUND)
ENDIF(CUDA_FOUND)
ENDIF(ZED_FOUND)
IF(ZEDOC_FOUND)
SET(INCLUDE_DIRS
${INCLUDE_DIRS}
${ZEDOC_INCLUDE_DIRS}
${HIDAPI_INCLUDE_DIRS}
)
SET(LIBRARIES
${LIBRARIES}
${ZEDOC_LIBRARIES}
${HIDAPI_LIBRARIES}
)
ENDIF(ZEDOC_FOUND)
IF(octomap_FOUND)
SET(INCLUDE_DIRS
${INCLUDE_DIRS}
@@ -542,16 +610,27 @@ IF(vins_FOUND)
)
ENDIF(vins_FOUND)
IF(ORB_SLAM2_FOUND)
IF(ov_msckf_FOUND)
SET(INCLUDE_DIRS
${ORB_SLAM2_INCLUDE_DIRS} #before so that g2o includes are taken from ORB_SLAM2 directory before the official g2o one
${ov_msckf_INCLUDE_DIRS}
${INCLUDE_DIRS}
)
SET(LIBRARIES
${ORB_SLAM2_LIBRARIES}
${ov_msckf_LIBRARIES}
${LIBRARIES}
)
ENDIF(ORB_SLAM2_FOUND)
ENDIF(ov_msckf_FOUND)
IF(ORB_SLAM_FOUND)
SET(INCLUDE_DIRS
${ORB_SLAM_INCLUDE_DIRS} #before so that g2o includes are taken from ORB_SLAM directory before the official g2o one
${INCLUDE_DIRS}
)
SET(LIBRARIES
${ORB_SLAM_LIBRARIES}
${LIBRARIES}
)
ENDIF(ORB_SLAM_FOUND)
IF(GTSAM_FOUND)
# Make sure GTSAM is built with system Eigen, not the included one in its package
@@ -608,8 +687,8 @@ foreach(arg ${RESOURCES})
set(RESOURCES_HEADERS "${RESOURCES_HEADERS}" "${CMAKE_CURRENT_BINARY_DIR}/${output}.h")
endforeach(arg ${RESOURCES})
MESSAGE(STATUS "RESOURCES = ${RESOURCES}")
MESSAGE(STATUS "RESOURCES_HEADERS = ${RESOURCES_HEADERS}")
#MESSAGE(STATUS "RESOURCES = ${RESOURCES}")
#MESSAGE(STATUS "RESOURCES_HEADERS = ${RESOURCES_HEADERS}")
IF(ANDROID)

View File

@@ -37,8 +37,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
namespace rtabmap {
CameraModel::CameraModel() :
localTransform_(0,0,1,0, -1,0,0,0, 0,-1,0,0)
CameraModel::CameraModel()
{
}
@@ -234,7 +233,7 @@ bool CameraModel::load(const std::string & filePath)
n = fs["camera_name"];
if(n.type() != cv::FileNode::NONE)
{
name_ = (int)n;
name_ = (std::string)n;
}
else
{
@@ -367,7 +366,11 @@ bool CameraModel::load(const std::string & directory, const std::string & camera
bool CameraModel::save(const std::string & directory) const
{
std::string filePath = directory+"/"+name_+".yaml";
if(name_.empty())
{
UWARN("Camera name is empty, will use general \"camera\" as name.");
}
std::string filePath = directory+"/"+(name_.empty()?"camera":name_)+".yaml";
if(!filePath.empty() && (!K_.empty() || !D_.empty() || !R_.empty() || !P_.empty()))
{
UINFO("Saving calibration to file \"%s\"", filePath.c_str());
@@ -767,7 +770,7 @@ bool CameraModel::inFrame(int u, int v) const
std::ostream& operator<<(std::ostream& os, const CameraModel& model)
{
os << "Name: " << model.name() << std::endl
os << "Name: " << model.name().c_str() << std::endl
<< "Size: " << model.imageWidth() << "x" << model.imageHeight() << std::endl
<< "K= " << model.K_raw() << std::endl
<< "D= " << model.D_raw() << std::endl

View File

@@ -67,7 +67,8 @@ CameraThread::CameraThread(Camera * camera, const ParametersMap & parameters) :
_bilateralFiltering(false),
_bilateralSigmaS(10),
_bilateralSigmaR(0.1),
_imuFilter(0)
_imuFilter(0),
_imuBaseFrameConversion(false)
{
UASSERT(_camera != 0);
}
@@ -117,10 +118,11 @@ void CameraThread::enableBilateralFiltering(float sigmaS, float sigmaR)
_bilateralSigmaR = sigmaR;
}
void CameraThread::enableIMUFiltering(int filteringStrategy, const ParametersMap & parameters)
void CameraThread::enableIMUFiltering(int filteringStrategy, const ParametersMap & parameters, bool baseFrameConversion)
{
delete _imuFilter;
_imuFilter = IMUFilter::create((IMUFilter::Type)filteringStrategy, parameters);
_imuBaseFrameConversion = baseFrameConversion;
}
void CameraThread::disableIMUFiltering()
@@ -174,7 +176,7 @@ void CameraThread::mainLoop()
CameraInfo info;
SensorData data = _camera->takeImage(&info);
if(!data.imageRaw().empty() || (dynamic_cast<DBReader*>(_camera) != 0 && data.id()>0)) // intermediate nodes could not have image set
if(!data.imageRaw().empty() || !data.laserScanRaw().empty() || (dynamic_cast<DBReader*>(_camera) != 0 && data.id()>0)) // intermediate nodes could not have image set
{
postUpdate(&data, &info);
@@ -406,9 +408,8 @@ void CameraThread::postUpdate(SensorData * dataPtr, CameraInfo * info) const
_scanRangeMin,
validIndices.get());
float maxPoints = (data.depthRaw().rows/_scanDownsampleStep)*(data.depthRaw().cols/_scanDownsampleStep);
cv::Mat scan;
LaserScan scan;
const Transform & baseToScan = data.cameraModels()[0].localTransform();
LaserScan::Format format = LaserScan::kXYZRGB;
if(validIndices->size())
{
if(_scanVoxelSize>0.0f)
@@ -433,7 +434,6 @@ void CameraThread::postUpdate(SensorData * dataPtr, CameraInfo * info) const
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloudNormals(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
pcl::concatenateFields(*cloud, *normals, *cloudNormals);
scan = util3d::laserScanFromPointCloud(*cloudNormals, baseToScan.inverse());
format = LaserScan::kXYZRGBNormal;
}
else
{
@@ -441,7 +441,7 @@ void CameraThread::postUpdate(SensorData * dataPtr, CameraInfo * info) const
}
}
}
data.setLaserScan(LaserScan(scan, (int)maxPoints, _scanRangeMax, format, baseToScan));
data.setLaserScan(LaserScan(scan, (int)maxPoints, _scanRangeMax, baseToScan));
if(info) info->timeScanFromDepth = timer.ticks();
}
else
@@ -472,21 +472,31 @@ void CameraThread::postUpdate(SensorData * dataPtr, CameraInfo * info) const
}
else
{
// Transform IMU data in base_link to correctly initialize yaw
IMU imu = data.imu();
if(_imuBaseFrameConversion)
{
UASSERT(!data.imu().localTransform().isNull());
imu.convertToBaseFrame();
}
_imuFilter->update(
data.imu().angularVelocity()[0],
data.imu().angularVelocity()[1],
data.imu().angularVelocity()[2],
data.imu().linearAcceleration()[0],
data.imu().linearAcceleration()[1],
data.imu().linearAcceleration()[2],
imu.angularVelocity()[0],
imu.angularVelocity()[1],
imu.angularVelocity()[2],
imu.linearAcceleration()[0],
imu.linearAcceleration()[1],
imu.linearAcceleration()[2],
data.stamp());
double qx,qy,qz,qw;
_imuFilter->getOrientation(qx,qy,qz,qw);
data.setIMU(IMU(
cv::Vec4d(qx,qy,qz,qw), cv::Mat::eye(3,3,CV_64FC1),
data.imu().angularVelocity(), data.imu().angularVelocityCovariance(),
data.imu().linearAcceleration(), data.imu().linearAccelerationCovariance(),
data.imu().localTransform()));
imu.angularVelocity(), imu.angularVelocityCovariance(),
imu.linearAcceleration(), imu.linearAccelerationCovariance(),
imu.localTransform()));
UDEBUG("%f %f %f %f (gyro=%f %f %f, acc=%f %f %f, %fs)",
data.imu().orientation()[0],
data.imu().orientation()[1],

View File

@@ -200,6 +200,18 @@ bool DBReader::init(
{
_calibrated = true;
}
else
{
Signature * s = _dbDriver->loadSignature(*_ids.begin());
_dbDriver->loadNodeData(s);
if( s->sensorData().imageCompressed().empty() &&
s->getWords().empty() &&
!s->sensorData().laserScanCompressed().empty())
{
_calibrated = true; // only scans
}
delete s;
}
}
}
else

View File

@@ -44,10 +44,14 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include "opencv/ORBextractor.h"
#endif
#ifdef RTABMAP_SUPERPOINT_TORCH
#ifdef RTABMAP_TORCH
#include "superpoint_torch/SuperPoint.h"
#endif
#ifdef RTABMAP_PYTHON
#include "python/PyDetector.h"
#endif
#if CV_MAJOR_VERSION < 3
#include "opencv/Orb.h"
#ifdef HAVE_OPENCV_GPU
@@ -298,7 +302,11 @@ void Feature2D::limitKeypoints(std::vector<cv::KeyPoint> & keypoints, std::vecto
int removed = (int)hessianMap.size()-maxKeypoints;
std::multimap<float, int>::reverse_iterator iter = hessianMap.rbegin();
std::vector<cv::KeyPoint> kptsTmp(maxKeypoints);
std::vector<cv::Point3f> kpts3DTmp(maxKeypoints);
std::vector<cv::Point3f> kpts3DTmp;
if(!keypoints3D.empty())
{
kpts3DTmp.resize(maxKeypoints);
}
cv::Mat descriptorsTmp;
if(descriptors.rows)
{
@@ -580,7 +588,7 @@ Feature2D * Feature2D::create(Feature2D::Type type, const ParametersMap & parame
}
#endif
#ifndef RTABMAP_SUPERPOINT_TORCH
#ifndef RTABMAP_TORCH
if(type == Feature2D::kFeatureSuperPointTorch)
{
UWARN("SupertPoint Torch feature cannot be used as RTAB-Map is not built with the option enabled. GFTT/ORB is used instead.");
@@ -624,7 +632,7 @@ Feature2D * Feature2D::create(Feature2D::Type type, const ParametersMap & parame
case Feature2D::kFeatureOrbOctree:
feature2D = new ORBOctree(parameters);
break;
#ifdef RTABMAP_SUPERPOINT_TORCH
#ifdef RTABMAP_TORCH
case Feature2D::kFeatureSuperPointTorch:
feature2D = new SuperPointTorch(parameters);
break;
@@ -638,6 +646,11 @@ Feature2D * Feature2D::create(Feature2D::Type type, const ParametersMap & parame
case Feature2D::kFeatureSurfDaisy:
feature2D = new SURF_DAISY(parameters);
break;
#ifdef RTABMAP_PYTHON
case Feature2D::kFeaturePyDetector:
feature2D = new PyDetector(parameters);
break;
#endif
#ifdef RTABMAP_NONFREE
default:
feature2D = new SURF(parameters);
@@ -2047,7 +2060,7 @@ void SuperPointTorch::parseParameters(const ParametersMap & parameters)
Feature2D::parseParameters(parameters);
std::string previousPath = path_;
#ifdef RTABMAP_SUPERPOINT_TORCH
#ifdef RTABMAP_TORCH
bool previousCuda = cuda_;
#endif
Parameters::parse(parameters, Parameters::kSuperPointModelPath(), path_);
@@ -2056,7 +2069,7 @@ void SuperPointTorch::parseParameters(const ParametersMap & parameters)
Parameters::parse(parameters, Parameters::kSuperPointNMSRadius(), minDistance_);
Parameters::parse(parameters, Parameters::kSuperPointCuda(), cuda_);
#ifdef RTABMAP_SUPERPOINT_TORCH
#ifdef RTABMAP_TORCH
if(superPoint_.get() == 0 || path_.compare(previousPath) != 0 || previousCuda != cuda_)
{
superPoint_ = cv::Ptr<SPDetector>(new SPDetector(path_, threshold_, nms_, minDistance_, cuda_));
@@ -2068,29 +2081,29 @@ void SuperPointTorch::parseParameters(const ParametersMap & parameters)
superPoint_->setMinDistance(minDistance_);
}
#else
UWARN("RTAB-Map is not built with SuperPoint Torch support so SuperPoint Torch feature cannot be used!");
UWARN("RTAB-Map is not built with Torch support so SuperPoint Torch feature cannot be used!");
#endif
}
std::vector<cv::KeyPoint> SuperPointTorch::generateKeypointsImpl(const cv::Mat & image, const cv::Rect & roi, const cv::Mat & mask)
{
#ifdef RTABMAP_SUPERPOINT_TORCH
#ifdef RTABMAP_TORCH
UASSERT(!image.empty() && image.channels() == 1 && image.depth() == CV_8U);
UASSERT_MSG(roi.x==0 && roi.y ==0, "Not supporting ROI");
return superPoint_->detect(image, mask);
#else
UWARN("RTAB-Map is not built with SuperPoint Torch support so SuperPoint Torch feature cannot be used!");
UWARN("RTAB-Map is not built with Torch support so SuperPoint Torch feature cannot be used!");
return std::vector<cv::KeyPoint>();
#endif
}
cv::Mat SuperPointTorch::generateDescriptorsImpl(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints) const
{
#ifdef RTABMAP_SUPERPOINT_TORCH
#ifdef RTABMAP_TORCH
UASSERT(!image.empty() && image.channels() == 1 && image.depth() == CV_8U);
return superPoint_->compute(keypoints);
#else
UWARN("RTAB-Map is not built with SuperPoint Torch support so SuperPoint Torch feature cannot be used!");
UWARN("RTAB-Map is not built with Torch support so SuperPoint Torch feature cannot be used!");
return cv::Mat();
#endif
}

View File

@@ -53,7 +53,7 @@ namespace graph {
bool exportPoses(
const std::string & filePath,
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame), 2=KITTI, 3=TORO, 4=g2o
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame, 11=10+ID), 2=KITTI, 3=TORO, 4=g2o
const std::map<int, Transform> & poses,
const std::multimap<int, Link> & constraints, // required for formats 3 and 4
const std::map<int, double> & stamps, // required for format 1
@@ -86,11 +86,11 @@ bool exportPoses(
tmpPath+=".txt";
}
if(format == 1 || format == 10)
if(format == 1 || format == 10 || format == 11)
{
if(stamps.size() != poses.size())
{
UERROR("When exporting poses to format 1 (RGBD-SLAM), stamps and poses maps should have the same size! stamps=%d psoes=%d",
UERROR("When exporting poses to format 1 (RGBD-SLAM), stamps and poses maps should have the same size! stamps=%d poses=%d",
(int)stamps.size(), (int)poses.size());
return false;
}
@@ -106,7 +106,7 @@ bool exportPoses(
{
for(std::map<int, Transform>::const_iterator iter=poses.begin(); iter!=poses.end(); ++iter)
{
if(format == 1 || format == 10) // rgbd-slam format
if(format == 1 || format == 10 || format == 11) // rgbd-slam format
{
Transform pose = iter->second;
if(format == 1)
@@ -125,8 +125,21 @@ bool exportPoses(
// Format: stamp x y z qx qy qz qw
Eigen::Quaternionf q = pose.getQuaternionf();
if(iter == poses.begin())
{
// header
if(format == 11)
{
fprintf(fout, "# timestamp x y z qx qy qz qw id\n");
}
else
{
fprintf(fout, "# timestamp x y z qx qy qz qw\n");
}
}
UASSERT(uContains(stamps, iter->first));
fprintf(fout, "%f %f %f %f %f %f %f %f\n",
fprintf(fout, "%f %f %f %f %f %f %f %f%s\n",
stamps.at(iter->first),
pose.x(),
pose.y(),
@@ -134,7 +147,8 @@ bool exportPoses(
q.x(),
q.y(),
q.z(),
q.w());
q.w(),
format == 11?(" "+uNumber2Str(iter->first)).c_str():"");
}
else // default / KITTI format
{
@@ -169,7 +183,7 @@ bool exportPoses(
bool importPoses(
const std::string & filePath,
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame), 2=KITTI, 3=TORO, 4=g2o, 5=NewCollege(t,x,y), 6=Malaga Urban GPS, 7=St Lucia INS, 8=Karlsruhe, 9=EuRoC MAV
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame, 11=10+ID), 2=KITTI, 3=TORO, 4=g2o, 5=NewCollege(t,x,y), 6=Malaga Urban GPS, 7=St Lucia INS, 8=Karlsruhe, 9=EuRoC MAV
std::map<int, Transform> & poses,
std::multimap<int, Link> * constraints, // optional for formats 3 and 4
std::map<int, double> * stamps) // optional for format 1 and 9
@@ -413,13 +427,18 @@ bool importPoses(
UERROR("Error parsing \"%s\" with NewCollege format (should have 3 values: stamp x y, found %d)", str.c_str(), (int)strList.size());
}
}
else if(format == 1 || format==10) // rgbd-slam format
else if(format == 1 || format==10 || format==11) // rgbd-slam format
{
std::list<std::string> strList = uSplit(str);
if(strList.size() == 8)
if((strList.size() == 8 && format!=11) || (strList.size() == 9 && format==11))
{
double stamp = uStr2Double(strList.front());
strList.pop_front();
if(format==11)
{
id = uStr2Int(strList.back());
strList.pop_back();
}
str = uJoin(strList, " ");
Transform pose = Transform::fromString(str);
if(pose.isNull())
@@ -450,7 +469,7 @@ bool importPoses(
}
else
{
UERROR("Error parsing \"%s\" with RGBD-SLAM format (should have 8 values: stamp x y z qw qx qy qz)", str.c_str());
UERROR("Error parsing \"%s\" with RGBD-SLAM format (should have 8 values (or 9 with id): stamp x y z qw qx qy qz [id])", str.c_str());
}
}
else // default / KITTI format
@@ -2328,6 +2347,33 @@ std::list<std::map<int, Transform> > getPaths(
return paths;
}
void computeMinMax(const std::map<int, Transform> & poses,
cv::Vec3f & min,
cv::Vec3f & max)
{
if(!poses.empty())
{
min[0] = max[0] = poses.begin()->second.x();
min[1] = max[1] = poses.begin()->second.y();
min[2] = max[2] = poses.begin()->second.z();
for(std::map<int, Transform>::const_iterator iter=poses.begin(); iter!=poses.end(); ++iter)
{
if(min[0] > iter->second.x())
min[0] = iter->second.x();
if(max[0] < iter->second.x())
max[0] = iter->second.x();
if(min[1] > iter->second.y())
min[1] = iter->second.y();
if(max[1] < iter->second.y())
max[1] = iter->second.y();
if(min[2] > iter->second.z())
min[2] = iter->second.z();
if(max[2] < iter->second.z())
max[2] = iter->second.z();
}
}
}
} /* namespace graph */
} /* namespace rtabmap */

74
corelib/src/IMU.cpp Normal file
View File

@@ -0,0 +1,74 @@
/*
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include <rtabmap/core/IMU.h>
namespace rtabmap {
void IMU::convertToBaseFrame()
{
if(!localTransform_.isNull() && !localTransform_.rotation().isIdentity())
{
cv::Mat rotationMatrix, rotationMatrixT;
localTransform_.rotationMatrix().convertTo(rotationMatrix, CV_64FC1);
cv::transpose(rotationMatrix, rotationMatrixT);
cv::Mat_<double> v = rotationMatrix * cv::Mat(linearAcceleration_);
linearAcceleration_ = cv::Vec3d(v(0,0), v(0,1), v(0,2));
if(!linearAccelerationCovariance_.empty())
{
linearAccelerationCovariance_ = rotationMatrix * linearAccelerationCovariance_ * rotationMatrixT;
}
v = rotationMatrix * cv::Mat(angularVelocity_);
angularVelocity_ = cv::Vec3d(v(0,0), v(0,1), v(0,2));
if(!angularVelocityCovariance_.empty())
{
angularVelocityCovariance_ = rotationMatrix * angularVelocityCovariance_ * rotationMatrixT;
}
if(!(orientation_[0] == 0.0 && orientation_[1] == 0.0 && orientation_[2] == 0.0))
{
// orientation includes roll and pitch but not yaw in local transform
Eigen::Quaterniond qTheta =
Eigen::AngleAxisd(0, Eigen::Vector3d::UnitX()) *
Eigen::AngleAxisd(0, Eigen::Vector3d::UnitY()) *
Eigen::AngleAxisd(localTransform_.theta(), Eigen::Vector3d::UnitZ());
Eigen::Quaterniond q = qTheta * Eigen::Quaterniond(orientation_[3], orientation_[0], orientation_[1], orientation_[2]) * localTransform_.getQuaterniond().inverse();
orientation_ = cv::Vec4d(q.x(),q.y(),q.z(),q.w());
if(!orientationCovariance_.empty())
{
orientationCovariance_ = rotationMatrix * orientationCovariance_ * rotationMatrixT;
}
}
localTransform_ = Transform(localTransform_.x(), localTransform_.y(), localTransform_.z(), 0,0,0);
}
}
} //namespace rtabmap

View File

@@ -209,42 +209,60 @@ LaserScan::LaserScan() :
{
}
LaserScan::LaserScan(
const LaserScan & scan,
int maxPoints,
float maxRange,
const Transform & localTransform)
{
UASSERT(scan.empty() || scan.format() != kUnknown);
init(scan.data(), scan.format(), 0, maxRange, 0, 0, 0, maxPoints, localTransform);
}
LaserScan::LaserScan(
const LaserScan & scan,
int maxPoints,
float maxRange,
Format format,
const Transform & localTransform)
{
init(scan.data(), format, 0, maxRange, 0, 0, 0, maxPoints, localTransform);
}
LaserScan::LaserScan(
const cv::Mat & data,
int maxPoints,
float maxRange,
Format format,
const Transform & localTransform) :
data_(data),
format_(format),
maxPoints_(maxPoints),
rangeMin_(0),
rangeMax_(maxRange),
angleMin_(0),
angleMax_(0),
angleIncrement_(0),
localTransform_(localTransform)
const Transform & localTransform)
{
UASSERT(data.empty() || data.rows == 1);
UASSERT(data.empty() || data.type() == CV_8UC1 || data.type() == CV_32FC2 || data.type() == CV_32FC3 || data.type() == CV_32FC(4) || data.type() == CV_32FC(5) || data.type() == CV_32FC(6) || data.type() == CV_32FC(7));
UASSERT(!localTransform.isNull());
init(data, format, 0, maxRange, 0, 0, 0, maxPoints, localTransform);
}
if(!data.empty() && !isCompressed())
{
if(format == kUnknown)
{
*this = backwardCompatibility(data_, maxPoints_, rangeMax_, localTransform_);
}
else // verify that format corresponds to expected number of channels
{
UASSERT_MSG(data.channels() != 2 || (data.channels() == 2 && format == kXY), uFormat("format=%s", LaserScan::formatName(format).c_str()).c_str());
UASSERT_MSG(data.channels() != 3 || (data.channels() == 3 && (format == kXYZ || format == kXYI)), uFormat("format=%s", LaserScan::formatName(format).c_str()).c_str());
UASSERT_MSG(data.channels() != 4 || (data.channels() == 4 && (format == kXYZI || format == kXYZRGB)), uFormat("format=%s", LaserScan::formatName(format).c_str()).c_str());
UASSERT_MSG(data.channels() != 5 || (data.channels() == 5 && (format == kXYNormal)), uFormat("format=%s", LaserScan::formatName(format).c_str()).c_str());
UASSERT_MSG(data.channels() != 6 || (data.channels() == 6 && (format == kXYINormal || format == kXYZNormal)), uFormat("format=%s", LaserScan::formatName(format).c_str()).c_str());
UASSERT_MSG(data.channels() != 7 || (data.channels() == 7 && (format == kXYZRGBNormal || format == kXYZINormal)), uFormat("format=%s", LaserScan::formatName(format).c_str()).c_str());
}
}
LaserScan::LaserScan(
const LaserScan & scan,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform)
{
UASSERT(scan.empty() || scan.format() != kUnknown);
init(scan.data(), scan.format(), minRange, maxRange, angleMin, angleMax, angleIncrement, 0, localTransform);
}
LaserScan::LaserScan(
const LaserScan & scan,
Format format,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform)
{
init(scan.data(), format, minRange, maxRange, angleMin, angleMax, angleIncrement, 0, localTransform);
}
LaserScan::LaserScan(
@@ -255,37 +273,77 @@ LaserScan::LaserScan(
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform) :
data_(data),
format_(format),
rangeMin_(minRange),
rangeMax_(maxRange),
angleMin_(angleMin),
angleMax_(angleMax),
angleIncrement_(angleIncrement),
localTransform_(localTransform)
const Transform & localTransform)
{
UASSERT(maxRange>minRange);
UASSERT(angleMax>angleMin);
UASSERT(angleIncrement != 0.0f);
maxPoints_ = std::ceil((angleMax - angleMin) / angleIncrement)+1;
init(data, format, minRange, maxRange, angleMin, angleMax, angleIncrement, 0, localTransform);
}
void LaserScan::init(
const cv::Mat & data,
Format format,
float rangeMin,
float rangeMax,
float angleMin,
float angleMax,
float angleIncrement,
int maxPoints,
const Transform & localTransform)
{
UASSERT(data.empty() || data.rows == 1);
UASSERT(data.empty() || data.type() == CV_8UC1 || data.type() == CV_32FC2 || data.type() == CV_32FC3 || data.type() == CV_32FC(4) || data.type() == CV_32FC(5) || data.type() == CV_32FC(6) || data.type() == CV_32FC(7));
UASSERT(!localTransform.isNull());
bool is2D = false;
if(angleIncrement != 0.0f)
{
// 2D scan
is2D = true;
UASSERT(rangeMax>rangeMin);
UASSERT((angleIncrement>0 && angleMax>angleMin) || (angleIncrement<0 && angleMax<angleMin));
maxPoints_ = std::ceil((angleMax - angleMin) / angleIncrement)+1;
}
else
{
// 3D scan
UASSERT(rangeMax>=rangeMin);
maxPoints_ = maxPoints;
}
data_ = data;
format_ = format;
rangeMin_ = rangeMin;
rangeMax_ = rangeMax;
angleMin_ = angleMin;
angleMax_ = angleMax;
angleIncrement_ = angleIncrement;
localTransform_ = localTransform;
if(!data.empty() && !isCompressed())
{
if(data_.cols > maxPoints_)
if(is2D && data_.cols > maxPoints_)
{
UWARN("The number of points (%d) in the scan is over the maximum "
"points (%d) defined by angle settings (min=%f max=%f inc=%f). "
"The scan info may be wrong!",
data_.cols, maxPoints_, angleMin_, angleMax_, angleIncrement_);
}
else if(!is2D && maxPoints_>0 && data_.cols > maxPoints_)
{
UDEBUG("The number of points (%d) in the scan is over the maximum "
"points (%d) defined by max points setting.",
data_.cols, maxPoints_);
}
if(format == kUnknown)
{
*this = backwardCompatibility(data_, rangeMin_, rangeMax_, angleMin_, angleMax_, angleIncrement_, localTransform_);
if(angleIncrement_ != 0)
{
*this = backwardCompatibility(data_, rangeMin_, rangeMax_, angleMin_, angleMax_, angleIncrement_, localTransform_);
}
else
{
*this = backwardCompatibility(data_, maxPoints_, rangeMax_, localTransform_);
}
}
else // verify that format corresponds to expected number of channels
{

View File

@@ -2059,7 +2059,29 @@ std::map<int, Transform> Memory::loadOptimizedPoses(Transform * lastlocalization
{
if(_dbDriver)
{
return _dbDriver->loadOptimizedPoses(lastlocalizationPose);
bool ok = true;
std::map<int, Transform> poses = _dbDriver->loadOptimizedPoses(lastlocalizationPose);
// Make sure optimized poses match the working directory! Otherwise return nothing.
for(std::map<int, Transform>::iterator iter=poses.begin(); iter!=poses.end() && ok; ++iter)
{
if(_workingMem.find(iter->first)==_workingMem.end())
{
ok = false;
}
}
if(!ok)
{
UWARN("Optimized poses (%d) and working memory "
"size (%d) don't match. Returning empty optimized "
"poses to force re-update. If you want to use the "
"saved optimized poses, set %s to true",
(int)poses.size(),
(int)_workingMem.size(),
Parameters::kMemInitWMWithAllNodes().c_str());
return std::map<int, Transform>();
}
return poses;
}
return std::map<int, Transform>();
}
@@ -3053,7 +3075,7 @@ Transform Memory::computeIcpTransformMulti(
Transform t;
if(!fromScan.isEmpty() && !toScan.isEmpty())
{
Transform guess = poses.at(fromId).inverse() * poses.at(toId);
Transform guess = poses.at(toId).inverse() * poses.at(fromId);
float guessNorm = guess.getNorm();
if(fromScan.rangeMax() > 0.0f && toScan.rangeMax() > 0.0f &&
guessNorm > fromScan.rangeMax() + toScan.rangeMax())
@@ -3144,7 +3166,7 @@ Transform Memory::computeIcpTransformMulti(
}
}
cv::Mat assembledScan;
LaserScan assembledScan;
if(assembledToNormalClouds->size())
{
assembledScan = fromScan.is2d()?util3d::laserScan2dFromPointCloud(*assembledToNormalClouds):util3d::laserScanFromPointCloud(*assembledToNormalClouds);
@@ -3183,17 +3205,20 @@ Transform Memory::computeIcpTransformMulti(
assembledScan = util3d::laserScanFromPointCloud(*assembledToRGBClouds);
}
}
UDEBUG("assembledScan=%d points", assembledScan.cols);
UDEBUG("assembledScan=%d points", assembledScan.size());
// scans are in base frame but for 2d scans, set the height so that correspondences matching works
assembledData.setLaserScan(
LaserScan(assembledScan,
fromScan.maxPoints()?fromScan.maxPoints():maxPoints,
maxPoints,
fromScan.rangeMax(),
toScan.format(),
fromScan.is2d()?Transform(0,0,fromScan.localTransform().z(),0,0,0):Transform::getIdentity()));
t = _registrationIcpMulti->computeTransformation(fromS->sensorData(), assembledData, guess, info);
t = _registrationIcpMulti->computeTransformation(assembledData, fromS->sensorData(), guess, info);
if(!t.isNull())
{
t = t.inverse();
}
}
return t;
@@ -3532,11 +3557,11 @@ unsigned long Memory::getMemoryUsed() const
}
memoryUsage += _landmarksIndex.size() * (sizeof(int)+sizeof(std::set<int>) + sizeof(std::map<int, std::set<int> >::iterator)) + sizeof(std::map<int, std::set<int> >);
memoryUsage += _landmarksInvertedIndex.size() * (sizeof(int)+sizeof(std::set<int>) + sizeof(std::map<int, std::set<int> >::iterator)) + sizeof(std::map<int, std::set<int> >);
for(std::map<int, std::set<int>>::const_iterator iter=_landmarksIndex.begin(); iter!=_landmarksIndex.end(); ++iter)
for(std::map<int, std::set<int> >::const_iterator iter=_landmarksIndex.begin(); iter!=_landmarksIndex.end(); ++iter)
{
memoryUsage+=iter->second.size()*(sizeof(int)+sizeof(std::set<int>::iterator)) + sizeof(std::set<int>);
}
for(std::map<int, std::set<int>>::const_iterator iter=_landmarksInvertedIndex.begin(); iter!=_landmarksInvertedIndex.end(); ++iter)
for(std::map<int, std::set<int> >::const_iterator iter=_landmarksInvertedIndex.begin(); iter!=_landmarksInvertedIndex.end(); ++iter)
{
memoryUsage+=iter->second.size()*(sizeof(int)+sizeof(std::set<int>::iterator)) + sizeof(std::set<int>);
}
@@ -4120,6 +4145,10 @@ Signature * Memory::createSignature(const SensorData & inputData, const Transfor
!pose.isNull())
{
UERROR("Camera calibration not valid, calibrate your camera!");
if(data.cameraModels().empty())
std::cout << data.stereoCameraModel() << std::endl;
else
std::cout << data.cameraModels()[0] << std::endl;
return 0;
}
UASSERT(_feature2D != 0);
@@ -4131,7 +4160,7 @@ Signature * Memory::createSignature(const SensorData & inputData, const Transfor
float t;
std::vector<cv::KeyPoint> keypoints;
cv::Mat descriptors;
bool isIntermediateNode = data.id() < 0 || (data.imageRaw().empty() && data.keypoints().empty());
bool isIntermediateNode = data.id() < 0 || (data.imageRaw().empty() && data.keypoints().empty() && data.laserScanRaw().empty());
int id = data.id();
if(_generateIds)
{
@@ -4205,6 +4234,7 @@ Signature * Memory::createSignature(const SensorData & inputData, const Transfor
"full calibration. If images are already rectified, set %s parameter back to true.",
(int)i,
Parameters::kRtabmapImagesAlreadyRectified().c_str());
std::cout << data.cameraModels()[i] << std::endl;
return 0;
}
}
@@ -5246,7 +5276,8 @@ Signature * Memory::createSignature(const SensorData & inputData, const Transfor
// Occupancy grid map stuff
if(_createOccupancyGrid && !isIntermediateNode)
{
if(!data.depthOrRightRaw().empty())
if( (_occupancy->isGridFromDepth() && !data.depthOrRightRaw().empty()) ||
(!_occupancy->isGridFromDepth() && !data.laserScanRaw().empty()))
{
cv::Mat ground, obstacles, empty;
float cellSize = 0.0f;

View File

@@ -286,8 +286,8 @@ void OccupancyGrid::createLocalMap(
cv::Mat & emptyCells,
cv::Point3f & viewPoint) const
{
UDEBUG("scan format=%d, occupancyFromDepth_=%d normalsSegmentation_=%d grid3D_=%d",
node.sensorData().laserScanRaw().isEmpty()?0:node.sensorData().laserScanRaw().format(), occupancyFromDepth_?1:0, normalsSegmentation_?1:0, grid3D_?1:0);
UDEBUG("scan format=%s, occupancyFromDepth_=%d normalsSegmentation_=%d grid3D_=%d",
node.sensorData().laserScanRaw().isEmpty()?"NA":node.sensorData().laserScanRaw().formatName().c_str(), occupancyFromDepth_?1:0, normalsSegmentation_?1:0, grid3D_?1:0);
if((node.sensorData().laserScanRaw().is2d()) && !occupancyFromDepth_)
{
@@ -354,7 +354,7 @@ void OccupancyGrid::createLocalMap(
}
else
{
UWARN("Cannot create local map, scan is empty (node=%d).", node.id());
UWARN("Cannot create local map, scan is empty (node=%d, %s=false).", node.id(), Parameters::kGridFromDepth().c_str());
}
}
else
@@ -407,7 +407,7 @@ void OccupancyGrid::createLocalMap(
const Transform & t = node.sensorData().stereoCameraModel().localTransform();
viewPoint = cv::Point3f(t.x(), t.y(), t.z());
}
createLocalMap(LaserScan(util3d::laserScanFromPointCloud(*cloud, indices), 0, 0.0f, LaserScan::kXYZRGB), node.getPose(), groundCells, obstacleCells, emptyCells, viewPoint);
createLocalMap(LaserScan(util3d::laserScanFromPointCloud(*cloud, indices), 0, 0.0f), node.getPose(), groundCells, obstacleCells, emptyCells, viewPoint);
}
}
}
@@ -445,8 +445,8 @@ void OccupancyGrid::createLocalMap(
UDEBUG("groundIndices=%d, obstaclesIndices=%d", (int)groundIndices->size(), (int)obstaclesIndices->size());
if(grid3D_)
{
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices);
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices);
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices).data();
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices).data();
}
else
{
@@ -460,8 +460,8 @@ void OccupancyGrid::createLocalMap(
UDEBUG("groundIndices=%d, obstaclesIndices=%d", (int)groundIndices->size(), (int)obstaclesIndices->size());
if(grid3D_)
{
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices);
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices);
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices).data();
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices).data();
}
else
{
@@ -475,8 +475,8 @@ void OccupancyGrid::createLocalMap(
UDEBUG("groundIndices=%d, obstaclesIndices=%d", (int)groundIndices->size(), (int)obstaclesIndices->size());
if(grid3D_)
{
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices);
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices);
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices).data();
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices).data();
}
else
{
@@ -490,8 +490,8 @@ void OccupancyGrid::createLocalMap(
UDEBUG("groundIndices=%d, obstaclesIndices=%d", (int)groundIndices->size(), (int)obstaclesIndices->size());
if(grid3D_)
{
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices);
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices);
groundCloud = util3d::laserScanFromPointCloud(*cloudSegmented, groundIndices).data();
obstaclesCloud = util3d::laserScanFromPointCloud(*cloudSegmented, obstaclesIndices).data();
}
else
{
@@ -543,17 +543,17 @@ void OccupancyGrid::createLocalMap(
UDEBUG("ground=%d obstacles=%d empty=%d", (int)groundIndices->size(), (int)obstaclesIndices->size(), (int)emptyIndices->size());
if(scan.hasRGB())
{
groundCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing, groundIndices, tinv);
obstacleCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing, obstaclesIndices, tinv);
emptyCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing, emptyIndices, tinv);
groundCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing, groundIndices, tinv).data();
obstacleCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing, obstaclesIndices, tinv).data();
emptyCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing, emptyIndices, tinv).data();
}
else
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloudWithRayTracing2(new pcl::PointCloud<pcl::PointXYZ>);
pcl::copyPointCloud(*cloudWithRayTracing, *cloudWithRayTracing2);
groundCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing2, groundIndices, tinv);
obstacleCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing2, obstaclesIndices, tinv);
emptyCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing2, emptyIndices, tinv);
groundCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing2, groundIndices, tinv).data();
obstacleCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing2, obstaclesIndices, tinv).data();
emptyCells = util3d::laserScanFromPointCloud(*cloudWithRayTracing2, emptyIndices, tinv).data();
}
}
}
@@ -669,6 +669,10 @@ cv::Mat OccupancyGrid::getProbMap(float & xMin, float & yMin) const
}
}
}
else
{
UWARN("Map info is empty, cannot generate probabilistic occupancy grid");
}
return map;
}
@@ -1244,6 +1248,7 @@ bool OccupancyGrid::update(const std::map<int, Transform> & posesIn)
ptBegin.y = 0;
if(ptEnd.y >= map.rows)
ptEnd.y = map.rows-1;
for(int i=ptBegin.x; i<ptEnd.x; ++i)
{
for(int j=ptBegin.y; j<ptEnd.y; ++j)
@@ -1282,6 +1287,7 @@ bool OccupancyGrid::update(const std::map<int, Transform> & posesIn)
info[0] = (float)kter->first;
info[1] = float(i) * cellSize_ + xMin;
info[2] = float(j) * cellSize_ + yMin;
info[3] = probClampingMin_;
cter->second.first+=1;
}
value = -2; // free space (footprint)

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