Files
rtabmap_ros/rtabmap_conversions/src/MsgConversion.cpp
T
matlabbe cf7d7ab958 Supporting image compression formats passthrough (#1461)
* Supporting ros depth compression formats passthrough

* Added image_compression_format (support jpg,png). Use Compression.h constants.

* Bridging gap with #1457

* CoreWrapper: decode_images_on_demand

* rgbd_sync->rgbd_split encoding/decoding test with image_transport validation. rgbd_split color passthrough

* more tests

* fixing ci on kilted+

* fixing test

* fixing lyrical tests

* fixing rolling ci

* Improved test coverage

* fixing some tf waitForTransform deadlocks when sim time is used in tests

* CI: build rtabmap_slam on rolling

rtabmap_slam builds without nav2_msgs, which is not on resolute yet: skip its
key instead of leaving the package out. Only rtabmap_costmap_plugins (and the
rtabmap_ros metapackage pulling it in) still need nav2.
2026-10-10 16:05:08 -07:00

4224 lines
140 KiB
C++

/*
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.
*/
#include <rtabmap_conversions/PointCloudConversion.h>
#include "rtabmap_conversions/MsgConversion.h"
#include <algorithm>
#include <cmath>
#include <cstring>
#include <limits>
#include <opencv2/highgui/highgui.hpp>
#include <zlib.h>
#include "rclcpp/rclcpp.hpp"
#include <rtabmap/core/util3d.h>
#include <rtabmap/core/util3d_transforms.h>
#include <rtabmap/core/util3d_filtering.h>
#include <rtabmap/core/Compression.h>
#include <rtabmap/utilite/UStl.h>
#include <rtabmap/utilite/ULogger.h>
#include <rtabmap/utilite/UTimer.h>
#include <pcl_conversions/pcl_conversions.h>
#ifdef PRE_ROS_IRON
#include <image_geometry/pinhole_camera_model.h>
#include <image_geometry/stereo_camera_model.h>
#else
#include <image_geometry/pinhole_camera_model.hpp>
#include <image_geometry/stereo_camera_model.hpp>
#endif
#include <sensor_msgs/image_encodings.hpp>
#include <sensor_msgs/msg/point_field.hpp>
#include <geometry_msgs/msg/transform.hpp>
#include <laser_geometry/laser_geometry.hpp>
#include <rtabmap/core/util3d_surface.h>
#ifdef PRE_ROS_HUMBLE
#include <tf2_eigen/tf2_eigen.h>
#include <tf2_geometry_msgs/tf2_geometry_msgs.hpp>
#else
#include <tf2_eigen/tf2_eigen.hpp>
#include <tf2_geometry_msgs/tf2_geometry_msgs.hpp>
#endif
namespace rtabmap_conversions {
namespace {
// PNG file signature. rtabmap's own depth layouts are in rtabmap/core/Compression.h.
const unsigned char kPngSignature[8] = {0x89, 'P', 'N', 'G', '\r', '\n', 0x1A, '\n'};
// compressed_depth_image_transport::ConfigHeader, at the start of the message data
struct CompressedDepthConfigHeader
{
int32_t format; // 0: INV_DEPTH
float depthParam[2];
};
static_assert(sizeof(CompressedDepthConfigHeader) == 12, "Unexpected compressedDepth header size");
bool hasSignature(const unsigned char * bytes, size_t size, const void * signature)
{
return size >= 8 && memcmp(bytes, signature, 8) == 0;
}
// compressed_image_transport's format of a JPEG or PNG image ("<encoding>; <codec>
// compressed <encoding>"), with the encoding read from its header. Only the codec name
// if the encoding cannot be read from it.
std::string compressedImageFormat(const unsigned char * d, size_t size)
{
std::string codec;
std::string encoding;
if(size > 25 && hasSignature(d, size, kPngSignature))
{
codec = "png";
// IHDR: bit depth, color type. OpenCV decodes color as BGR.
const bool depth16 = d[24] == 16;
switch(d[25])
{
case 0: encoding = depth16 ? sensor_msgs::image_encodings::MONO16 : sensor_msgs::image_encodings::MONO8; break;
case 2: encoding = depth16 ? sensor_msgs::image_encodings::BGR16 : sensor_msgs::image_encodings::BGR8; break;
case 6: encoding = depth16 ? sensor_msgs::image_encodings::BGRA16 : sensor_msgs::image_encodings::BGRA8; break;
default: break;
}
if(d[24] != 8 && !depth16)
{
encoding.clear(); // e.g., 1 bit per pixel, decoded as 8 bits by OpenCV
}
}
else if(size > 2 && d[0] == 0xFF && d[1] == 0xD8)
{
codec = "jpeg";
// Number of components in the start of frame segment
size_t i = 2;
while(i + 4 <= size && d[i] == 0xFF)
{
const unsigned char marker = d[i+1];
if(marker == 0xFF)
{
++i; // fill byte
continue;
}
if(marker == 0x01 || (marker >= 0xD0 && marker <= 0xD8))
{
i += 2; // no length
continue;
}
const size_t length = (size_t(d[i+2]) << 8) | d[i+3];
if(marker >= 0xC0 && marker <= 0xCF && marker != 0xC4 && marker != 0xC8 && marker != 0xCC)
{
if(i + 9 < size)
{
encoding = d[i+9] == 1 ? sensor_msgs::image_encodings::MONO8 :
d[i+9] == 3 ? sensor_msgs::image_encodings::BGR8 : "";
}
break;
}
i += 2 + length;
}
}
if(codec.empty() || encoding.empty())
{
return codec;
}
return encoding + "; " + codec + " compressed " + encoding;
}
std::string compressedImageFormat(const std::vector<unsigned char> & d)
{
return compressedImageFormat(d.data(), d.size());
}
// Encoding of a JPEG or PNG image read from its header, empty if unknown
std::string compressedImageEncoding(const cv::Mat & bytes)
{
const std::string format = compressedImageFormat(bytes.data, bytes.total());
const size_t split = format.find(';');
return split == std::string::npos ? std::string() : format.substr(0, split);
}
} // namespace
bool transformToTF(const rtabmap::Transform & transform, tf2::Transform & tfTransform)
{
if(transform.isNull())
{
// tf2::Transform cannot represent a null transform: it stores its rotation as a
// basis matrix, so there is no equivalent of the all-zero quaternion used by the
// geometry_msgs conversions. Fill it with NaN so that a caller ignoring the
// return value corrupts its results loudly instead of silently carrying on with
// an identity that looks legitimate.
const tf2Scalar nan = std::numeric_limits<tf2Scalar>::quiet_NaN();
tfTransform = tf2::Transform(
tf2::Matrix3x3(nan, nan, nan, nan, nan, nan, nan, nan, nan),
tf2::Vector3(nan, nan, nan));
return false;
}
geometry_msgs::msg::Transform msg;
transformToGeometryMsg(transform, msg);
tf2::fromMsg(msg, tfTransform);
return true;
}
rtabmap::Transform transformFromTF(const tf2::Transform & transform)
{
// transformToTF() poisons its output with NaN for a null transform, as tf2::Transform
// has no null representation of its own. Map that back to a null transform here so the
// two functions round-trip, and so a NaN coming from anywhere else does not silently
// propagate into the rest of the pipeline.
const tf2::Vector3 & origin = transform.getOrigin();
const tf2::Matrix3x3 & basis = transform.getBasis();
bool nan = std::isnan(origin.x()) || std::isnan(origin.y()) || std::isnan(origin.z());
for(int i=0; !nan && i<3; ++i)
{
nan = std::isnan(basis[i].x()) || std::isnan(basis[i].y()) || std::isnan(basis[i].z());
}
if(nan)
{
return rtabmap::Transform();
}
Eigen::Isometry3d eigenTf;
geometry_msgs::msg::Transform gm = tf2::toMsg(transform);
eigenTf = tf2::transformToEigen(gm);
return rtabmap::Transform::fromEigen3d(eigenTf);
}
void transformToGeometryMsg(const rtabmap::Transform & transform, geometry_msgs::msg::Transform & msg)
{
if(!transform.isNull())
{
msg = tf2::eigenToTransform(transform.toEigen3d()).transform;
// make sure the quaternion is normalized
long double recipNorm = 1.0 / sqrt(msg.rotation.x * msg.rotation.x + msg.rotation.y * msg.rotation.y + msg.rotation.z * msg.rotation.z + msg.rotation.w * msg.rotation.w);
msg.rotation.x *= recipNorm;
msg.rotation.y *= recipNorm;
msg.rotation.z *= recipNorm;
msg.rotation.w *= recipNorm;
}
else
{
msg = geometry_msgs::msg::Transform();
msg.rotation.w = 0; // null
}
}
rtabmap::Transform transformFromGeometryMsg(const geometry_msgs::msg::Transform & msg)
{
if(msg.rotation.w == 0 &&
msg.rotation.x == 0 &&
msg.rotation.y == 0 &&
msg.rotation.z ==0)
{
return rtabmap::Transform();
}
Eigen::Isometry3d tfTransform;
tfTransform = tf2::transformToEigen(msg);
return rtabmap::Transform::fromEigen3d(tfTransform);
}
void transformToPoseMsg(const rtabmap::Transform & transform, geometry_msgs::msg::Pose & msg)
{
if(!transform.isNull())
{
msg = tf2::toMsg(transform.toEigen3d());
}
else
{
msg = geometry_msgs::msg::Pose();
msg.orientation.w = 0; // null
}
}
rtabmap::Transform transformFromPoseMsg(const geometry_msgs::msg::Pose & msg, bool ignoreRotationIfNotSet)
{
if(msg.orientation.w == 0 &&
msg.orientation.x == 0 &&
msg.orientation.y == 0 &&
msg.orientation.z == 0)
{
if(ignoreRotationIfNotSet)
{
return rtabmap::Transform(msg.position.x, msg.position.y, msg.position.z, 0, 0, 0);
}
return rtabmap::Transform();
}
Eigen::Affine3d tfPose;
tf2::fromMsg(msg, tfPose);
return rtabmap::Transform::fromEigen3d(tfPose);
}
namespace {
// cv_bridge::toCvCopy() labels a decoded 16 bits image mono8/bgr8 (it only looks at the
// number of channels): fix the encoding so that it can be converted downstream.
cv_bridge::CvImagePtr toCvCopyCompressedImage(const sensor_msgs::msg::CompressedImage & msg)
{
cv_bridge::CvImagePtr ptr = cv_bridge::toCvCopy(msg);
if(ptr && ptr->image.depth() == CV_16U)
{
switch(ptr->image.channels())
{
case 1: ptr->encoding = sensor_msgs::image_encodings::MONO16; break;
case 3: ptr->encoding = sensor_msgs::image_encodings::BGR16; break;
case 4: ptr->encoding = sensor_msgs::image_encodings::BGRA16; break;
default: break;
}
}
return ptr;
}
} // namespace
void toCvCopy(const rtabmap_msgs::msg::RGBDImage & image, cv_bridge::CvImagePtr & rgb, cv_bridge::CvImagePtr & depth)
{
if(!image.rgb.data.empty())
{
rgb = cv_bridge::toCvCopy(image.rgb);
}
else if(!image.rgb_compressed.data.empty())
{
rgb = toCvCopyCompressedImage(image.rgb_compressed);
}
else
{
// empty
rgb = std::make_shared<cv_bridge::CvImage>();
}
if(!image.depth.data.empty())
{
depth = cv_bridge::toCvCopy(image.depth);
}
else if(!image.depth_compressed.data.empty())
{
depth = uncompressDepthImage(image.depth_compressed);
}
else
{
// empty
depth = std::make_shared<cv_bridge::CvImage>();
}
}
void toCvShare(const rtabmap_msgs::msg::RGBDImage::ConstSharedPtr & image, cv_bridge::CvImageConstPtr & rgb, cv_bridge::CvImageConstPtr & depth)
{
toCvShare(*image, image, rgb, depth);
}
void toCvShare(const rtabmap_msgs::msg::RGBDImage & image, const std::shared_ptr<void const>& trackedObject, cv_bridge::CvImageConstPtr & rgb, cv_bridge::CvImageConstPtr & depth)
{
try
{
if(!image.rgb.data.empty())
{
rgb = cv_bridge::toCvShare(image.rgb, trackedObject);
}
else if(!image.rgb_compressed.data.empty())
{
rgb = toCvCopyCompressedImage(image.rgb_compressed);
}
else
{
// empty
rgb = std::make_shared<cv_bridge::CvImage>();
}
if(!image.depth.data.empty())
{
depth = cv_bridge::toCvShare(image.depth, trackedObject);
}
else if(!image.depth_compressed.data.empty())
{
depth = uncompressDepthImage(image.depth_compressed);
}
else
{
// empty
depth = std::make_shared<cv_bridge::CvImage>();
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting rgbd image (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
}
void rgbdImageToROS(const rtabmap::SensorData & data, rtabmap_msgs::msg::RGBDImage & msg, const std::string & sensorFrameId, bool legacyDepthCompression)
{
std_msgs::msg::Header header;
header.frame_id = sensorFrameId;
header.stamp = timestampToROS(data.stamp());
rtabmap::Transform localTransform;
if(data.cameraModels().size()>1)
{
UERROR("Cannot convert multi-camera data to rgbd image");
return;
}
msg.header = header;
if(data.cameraModels().size() == 1)
{
//rgb+depth
rtabmap_conversions::cameraModelToROS(data.cameraModels().front(), msg.rgb_camera_info);
msg.rgb_camera_info.header = header;
localTransform = data.cameraModels().front().localTransform();
}
else if(data.stereoCameraModels().size() == 1)
{
//stereo
rtabmap_conversions::cameraModelToROS(data.stereoCameraModels()[0].left(), msg.rgb_camera_info);
rtabmap_conversions::cameraModelToROS(data.stereoCameraModels()[0].right(), msg.depth_camera_info);
msg.rgb_camera_info.header = header;
msg.depth_camera_info.header = header;
localTransform = data.stereoCameraModels()[0].localTransform();
}
if(!data.imageRaw().empty())
{
cv_bridge::CvImage cvImg;
cvImg.header = header;
cvImg.image = data.imageRaw();
UASSERT(data.imageRaw().type()==CV_8UC1 || data.imageRaw().type()==CV_8UC3);
cvImg.encoding = data.imageRaw().type()==CV_8UC1?sensor_msgs::image_encodings::MONO8:sensor_msgs::image_encodings::BGR8;
cvImg.toImageMsg(msg.rgb);
}
else if(!data.imageCompressed().empty())
{
// JPEG or PNG, read as is by compressed_image_transport
msg.rgb_compressed.header = header;
compressedMatToBytes(data.imageCompressed(), msg.rgb_compressed.data);
msg.rgb_compressed.format = compressedImageFormat(msg.rgb_compressed.data);
}
if(!data.depthOrRightRaw().empty())
{
cv_bridge::CvImage cvDepth;
cvDepth.header = header;
cvDepth.image = data.depthOrRightRaw();
UASSERT(data.depthOrRightRaw().type()==CV_8UC1 || data.depthOrRightRaw().type()==CV_16UC1 || data.depthOrRightRaw().type()==CV_32FC1);
cvDepth.encoding = data.depthOrRightRaw().type()==CV_8UC1?sensor_msgs::image_encodings::MONO8:data.depthOrRightRaw().type()==CV_16UC1?sensor_msgs::image_encodings::TYPE_16UC1:sensor_msgs::image_encodings::TYPE_32FC1;
cvDepth.toImageMsg(msg.depth);
}
else if(!data.depthOrRightCompressed().empty())
{
msg.depth_compressed.header = header;
if(!data.stereoCameraModels().empty())
{
// Right image: JPEG or PNG, read as is by compressed_image_transport
compressedMatToBytes(data.depthOrRightCompressed(), msg.depth_compressed.data);
msg.depth_compressed.format = compressedImageFormat(msg.depth_compressed.data);
}
else if(legacyDepthCompression)
{
// rtabmap's format, see uncompressDepthImage()
compressedMatToBytes(data.depthOrRightCompressed(), msg.depth_compressed.data);
msg.depth_compressed.format = rtabmap::compressedDepthFormat(data.depthOrRightCompressed()).substr(1);
}
else if(!rtabmapToCompressedDepthTransport(data.depthOrRightCompressed(), msg.depth_compressed, false))
{
// Legacy 32FC1 format (4 channels PNG), no compressedDepth equivalent
const cv::Mat depth = rtabmap::uncompressImage(data.depthOrRightCompressed());
if(depth.type() != CV_32FC1 || !compressDepthImage(depth, ".png", msg.depth_compressed))
{
UERROR("Could not convert compressed depth image (%d bytes) to compressedDepth format.",
(int)data.depthOrRightCompressed().total());
}
}
}
//convert features
if(!data.keypoints().empty())
{
rtabmap_conversions::keypointsToROS(data.keypoints(), msg.key_points);
}
if(!data.keypoints3D().empty())
{
rtabmap_conversions::points3fToROS(data.keypoints3D(), msg.points, localTransform.inverse());
}
if(!data.descriptors().empty())
{
msg.descriptors = rtabmap::compressData(data.descriptors());
}
if(!data.globalDescriptors().empty())
{
rtabmap_conversions::globalDescriptorToROS(data.globalDescriptors().front(), msg.global_descriptor);
msg.global_descriptor.header = header;
}
}
rtabmap::SensorData rgbdImageFromROS(const rtabmap_msgs::msg::RGBDImage::ConstSharedPtr & image)
{
rtabmap::SensorData data;
cv_bridge::CvImageConstPtr imageMsg;
cv_bridge::CvImageConstPtr depthMsg;
toCvShare(image, imageMsg, depthMsg);
rtabmap::StereoCameraModel stereoModel = stereoCameraModelFromROS(image->rgb_camera_info, image->depth_camera_info, rtabmap::Transform::getIdentity());
if(stereoModel.isValidForProjection())
{
cv_bridge::CvImageConstPtr imageRectLeft = imageMsg;
cv_bridge::CvImageConstPtr imageRectRight = depthMsg;
if(!(imageRectLeft->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) ==0 ||
imageRectLeft->encoding.compare(sensor_msgs::image_encodings::MONO8) ==0 ||
imageRectLeft->encoding.compare(sensor_msgs::image_encodings::MONO16) ==0 ||
imageRectLeft->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
imageRectLeft->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0) ||
!(imageRectRight->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) ==0 ||
imageRectRight->encoding.compare(sensor_msgs::image_encodings::MONO8) ==0 ||
imageRectRight->encoding.compare(sensor_msgs::image_encodings::MONO16) ==0 ||
imageRectRight->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
imageRectRight->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0))
{
UERROR("Input type must be image=mono8,mono16,rgb8,bgr8 (mono8 recommended), received types are %s (left) and %s (right)",
imageRectLeft->encoding.c_str(), imageRectRight->encoding.c_str());
return data;
}
if(!imageRectLeft->image.empty() && !imageRectRight->image.empty())
{
if(stereoModel.baseline() > 10.0)
{
static bool shown = false;
if(!shown)
{
UWARN("Detected baseline (%f m) is quite large! Is your "
"right camera_info P(0,3) correctly set? Note that "
"baseline=-P(0,3)/P(0,0). This warning is printed only once.",
stereoModel.baseline());
shown = true;
}
}
cv::Mat left, right;
try {
if( imageRectLeft->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
imageRectLeft->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0)
{
left = imageRectLeft->image;
}
else if(imageRectLeft->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0)
{
left = cv_bridge::cvtColor(imageRectLeft, "mono8")->image;
}
else
{
left = cv_bridge::cvtColor(imageRectLeft, "bgr8")->image;
}
if( imageRectRight->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
imageRectRight->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0)
{
right = imageRectRight->image;
}
else
{
right = cv_bridge::cvtColor(imageRectRight, "mono8")->image;
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting images (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
//
data = rtabmap::SensorData(
left,
right,
stereoModel,
0,
rtabmap_conversions::timestampFromROS(image->header.stamp));
}
else
{
UWARN("Odom: input images empty?!?");
}
}
else //depth
{
int imageWidth = imageMsg->image.cols;
int imageHeight = imageMsg->image.rows;
int depthWidth = depthMsg->image.cols;
int depthHeight = depthMsg->image.rows;
// The depth image is optional: a message can legitimately carry only the color
// image and its camera info. Compare the resolutions only when there is a depth
// image, otherwise the ratios divide by zero.
UASSERT_MSG(
depthMsg->image.empty() ||
imageWidth/depthWidth == imageHeight/depthHeight,
uFormat("rgb=%dx%d depth=%dx%d", imageWidth, imageHeight, depthWidth, depthHeight).c_str());
cv::Mat rgb;
cv::Mat depth;
rtabmap::CameraModel cameraModels;
if(!(imageMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) ==0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::MONO8) ==0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::MONO16) ==0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::BGRA8) == 0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::RGBA8) == 0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::BAYER_GRBG8) == 0) ||
!(depthMsg->image.empty() ||
depthMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_16UC1) == 0 ||
depthMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_32FC1) == 0 ||
depthMsg->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0))
{
UERROR("Input type must be image=mono8,mono16,rgb8,bgr8,bgra8,rgba8 and "
"image_depth=32FC1,16UC1,mono16. Current rgb=%s and depth=%s",
imageMsg->encoding.c_str(),
depthMsg->encoding.c_str());
return data;
}
cv_bridge::CvImageConstPtr ptrImage = imageMsg;
try {
if(imageMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1)==0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0 ||
imageMsg->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0)
{
// do nothing
}
else if(imageMsg->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0)
{
ptrImage = cv_bridge::cvtColor(imageMsg, "mono8");
}
else
{
ptrImage = cv_bridge::cvtColor(imageMsg, "bgr8");
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting image (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
cv_bridge::CvImageConstPtr ptrDepth = depthMsg;
data = rtabmap::SensorData(
ptrImage->image,
ptrDepth->image,
rtabmap_conversions::cameraModelFromROS(image->rgb_camera_info),
0,
rtabmap_conversions::timestampFromROS(image->header.stamp));
}
if(data.isValid())
{
// Features, in the camera frame like the local transform (identity here)
if(!image->key_points.empty())
{
data.setFeatures(
keypointsFromROS(image->key_points),
points3fFromROS(image->points),
rtabmap::uncompressData(image->descriptors));
}
if(!image->global_descriptor.data.empty())
{
data.addGlobalDescriptor(globalDescriptorFromROS(image->global_descriptor));
}
}
return data;
}
void compressedMatToBytes(const cv::Mat & compressed, std::vector<unsigned char> & bytes)
{
UASSERT(compressed.empty() || compressed.type() == CV_8UC1);
bytes.clear();
if(!compressed.empty())
{
bytes.resize(compressed.cols * compressed.rows);
memcpy(bytes.data(), compressed.data, bytes.size());
}
}
cv::Mat compressedMatFromBytes(const std::vector<unsigned char> & bytes, bool copy)
{
cv::Mat out;
if(bytes.size())
{
out = cv::Mat(1, bytes.size(), CV_8UC1, (void*)bytes.data());
if(copy)
{
out = out.clone();
}
}
return out;
}
cv::Mat compressedDepthTransportToRtabmap(const sensor_msgs::msg::CompressedImage & msg)
{
// Same parsing as compressed_depth_image_transport
const std::string & format = msg.format;
const size_t split = format.find(';');
const std::string encoding = format.substr(0, split);
const bool rvl = split != std::string::npos && format.find("compressedDepth rvl", split) != std::string::npos;
if(split != std::string::npos && !rvl &&
format.find("compressedDepth png", split) == std::string::npos &&
(format.find("compressedDepth", split) == std::string::npos || format.find("compressedDepth ", split) != std::string::npos))
{
UERROR("Unsupported compressedDepth format \"%s\".", format.c_str());
return cv::Mat();
}
const bool inverseDepth = encoding == sensor_msgs::image_encodings::TYPE_32FC1;
if(!inverseDepth &&
encoding != sensor_msgs::image_encodings::TYPE_16UC1 &&
encoding != sensor_msgs::image_encodings::MONO16)
{
UERROR("Unsupported compressedDepth encoding \"%s\" (format=\"%s\"), only 32FC1, 16UC1 and mono16 are supported.",
encoding.c_str(), format.c_str());
return cv::Mat();
}
// RVL payload starts with uint32 cols, uint32 rows
if(msg.data.size() <= sizeof(CompressedDepthConfigHeader) + (rvl?8:0))
{
UERROR("compressedDepth data is truncated (%d bytes).", (int)msg.data.size());
return cv::Mat();
}
CompressedDepthConfigHeader header;
memcpy(&header, msg.data.data(), sizeof(CompressedDepthConfigHeader));
if(inverseDepth && header.format != 0)
{
UERROR("Unsupported compressedDepth compression format %d (only 0=INV_DEPTH is supported).", header.format);
return cv::Mat();
}
const unsigned char * payload = msg.data.data() + sizeof(CompressedDepthConfigHeader);
const size_t payloadSize = msg.data.size() - sizeof(CompressedDepthConfigHeader);
cv::Mat bytes(1, (int)((inverseDepth?rtabmap::kCompressedDepthInvHeaderSize:0) + (rvl?8:0) + payloadSize), CV_8UC1);
unsigned char * out = bytes.data;
if(inverseDepth)
{
memcpy(out, rtabmap::kCompressedDepthInvSignature, 8);
memcpy(out+8, &header.depthParam[0], 4);
memcpy(out+12, &header.depthParam[1], 4);
out += rtabmap::kCompressedDepthInvHeaderSize;
}
if(rvl)
{
memcpy(out, rtabmap::kCompressedDepthRvlSignature, 8);
out += 8;
}
memcpy(out, payload, payloadSize);
return bytes;
}
bool rtabmapToCompressedDepthTransport(const cv::Mat & compressed, sensor_msgs::msg::CompressedImage & msg, bool logErrors)
{
UASSERT(compressed.empty() || compressed.type() == CV_8UC1);
const unsigned char * bytes = compressed.data;
size_t size = compressed.total();
CompressedDepthConfigHeader header;
header.format = 0; // INV_DEPTH, also set for 16UC1 by compressed_depth_image_transport
header.depthParam[0] = header.depthParam[1] = 0.0f;
std::string encoding = sensor_msgs::image_encodings::TYPE_16UC1;
if(hasSignature(bytes, size, rtabmap::kCompressedDepthInvSignature) && size > rtabmap::kCompressedDepthInvHeaderSize)
{
encoding = sensor_msgs::image_encodings::TYPE_32FC1;
memcpy(&header.depthParam[0], bytes+8, 4);
memcpy(&header.depthParam[1], bytes+12, 4);
bytes += rtabmap::kCompressedDepthInvHeaderSize;
size -= rtabmap::kCompressedDepthInvHeaderSize;
}
std::string codec;
std::vector<unsigned char> png;
if(hasSignature(bytes, size, rtabmap::kCompressedDepthRvlSignature) && size >= rtabmap::kCompressedDepthRvlHeaderSize)
{
#ifdef PRE_ROS_JAZZY
// compressed_depth_image_transport decodes RVL only since Jazzy: re-compress
// the 16 bits image as PNG, losslessly.
png = rtabmap::compressImage(rtabmap::uncompressImage(bytes, size), ".png");
bytes = png.data();
size = png.size();
codec = "png";
#else
codec = "rvl";
bytes += 8; // keep uint32 cols, uint32 rows, data
size -= 8;
#endif
}
else if(hasSignature(bytes, size, kPngSignature) && size > 25 &&
bytes[24] == 16 && bytes[25] == 0) // IHDR: 16 bits grayscale
{
codec = "png";
}
if(codec.empty() || size == 0)
{
if(logErrors)
{
UERROR("Compressed depth image (%d bytes) cannot be converted to compressedDepth format, "
"only 16UC1 depth images compressed in PNG or RVL and 32FC1 depth images "
"compressed in inverse depth format are supported (legacy 32FC1 PNG format "
"is not supported, see Mem/DepthCompressionFormat).", (int)compressed.total());
}
return false;
}
msg.format = encoding + "; compressedDepth " + codec;
msg.data.resize(sizeof(CompressedDepthConfigHeader) + size);
memcpy(msg.data.data(), &header, sizeof(CompressedDepthConfigHeader));
memcpy(msg.data.data() + sizeof(CompressedDepthConfigHeader), bytes, size);
return true;
}
std::string compressedImageTransportFormat(const std::vector<unsigned char> & data)
{
const std::string format = compressedImageFormat(data);
return format.find(';') == std::string::npos ? std::string() : format;
}
bool isValidImageCompressionFormat(const std::string & format)
{
return format == ".jpg" || format == ".png" || format == "jpeg" || format == "png";
}
bool toCompressedImageMsg(const cv_bridge::CvImage & image, const std::string & inputFormat, sensor_msgs::msg::CompressedImage & msg)
{
if(!isValidImageCompressionFormat(inputFormat))
{
UERROR("Unsupported compressed image format \"%s\" (should be \".jpg\", \".png\", \"jpeg\" or \"png\").", inputFormat.c_str());
return false;
}
// compressed_image_transport's names
const std::string format = inputFormat == ".jpg" || inputFormat == "jpeg" ? "jpeg" : "png";
try
{
image.toCompressedImageMsg(msg, format == "jpeg" ? cv_bridge::JPEG : cv_bridge::PNG);
}
catch(const std::exception & e)
{
UERROR("Could not compress image (encoding=\"%s\") as %s: %s", image.encoding.c_str(), format.c_str(), e.what());
return false;
}
if(msg.data.empty())
{
UERROR("Could not compress image (encoding=\"%s\") as %s.", image.encoding.c_str(), format.c_str());
return false;
}
// Encoding of what was compressed, see cv_bridge::CvImage::toCompressedImageMsg()
std::string encoding = image.encoding;
if(encoding != sensor_msgs::image_encodings::BGR8 &&
encoding != sensor_msgs::image_encodings::BGRA8 &&
encoding != sensor_msgs::image_encodings::MONO8 &&
encoding != sensor_msgs::image_encodings::MONO16)
{
encoding = sensor_msgs::image_encodings::hasAlpha(encoding) ?
sensor_msgs::image_encodings::BGRA8 : sensor_msgs::image_encodings::BGR8;
}
msg.format = encoding + "; " + format + " compressed " + encoding;
return true;
}
cv_bridge::CvImagePtr uncompressDepthImage(const sensor_msgs::msg::CompressedImage & msg)
{
cv_bridge::CvImagePtr ptr = std::make_shared<cv_bridge::CvImage>();
ptr->header = msg.header;
if(msg.data.empty())
{
return ptr;
}
if(msg.format.find("compressedDepth") != std::string::npos)
{
ptr->image = rtabmap::uncompressImage(compressedDepthTransportToRtabmap(msg));
}
else
{
// rtabmap's formats, or JPEG/PNG right image
ptr->image = rtabmap::uncompressImage(msg.data);
}
// Pick the encoding from what actually came out: the format string cannot tell
// a 16 bits depth PNG from a right image compressed as PNG.
switch(ptr->image.empty() ? -1 : ptr->image.type())
{
case CV_32FC1: ptr->encoding = sensor_msgs::image_encodings::TYPE_32FC1; break;
case CV_16UC1: ptr->encoding = sensor_msgs::image_encodings::TYPE_16UC1; break;
case CV_8UC1: ptr->encoding = sensor_msgs::image_encodings::MONO8; break;
case CV_8UC3: ptr->encoding = sensor_msgs::image_encodings::BGR8; break;
default:
ptr->image = cv::Mat();
break;
}
if(ptr->image.empty())
{
UERROR("Could not decompress the depth/right image (format=\"%s\", %d bytes).",
msg.format.c_str(), (int)msg.data.size());
}
return ptr;
}
namespace {
// rtabmap's format of "legacy" or "legacy:<format>", empty if @p format is not legacy
std::string legacyDepthCompressionFormat(const std::string & format)
{
if(format == "legacy")
{
return ".png";
}
if(format.compare(0, 7, "legacy:") == 0)
{
return format.substr(7);
}
return "";
}
} // namespace
void rgbdImageCompressedToRtabmap(const rtabmap_msgs::msg::RGBDImage & msg, cv::Mat & rgb, cv::Mat & depth)
{
rgb = msg.rgb.data.empty() && !msg.rgb_compressed.data.empty() ?
compressedMatFromBytes(msg.rgb_compressed.data) : cv::Mat();
depth = cv::Mat();
if(msg.depth.data.empty() && !msg.depth_compressed.data.empty())
{
depth = msg.depth_compressed.format.find("compressedDepth") != std::string::npos ?
compressedDepthTransportToRtabmap(msg.depth_compressed) :
compressedMatFromBytes(msg.depth_compressed.data);
}
}
bool isCompressedRGBDSupportedByRtabmap(const cv::Mat & rgb, const cv::Mat & depth, bool stereo)
{
if(rgb.empty() && depth.empty())
{
return false;
}
if(!rgb.empty())
{
UASSERT(rgb.type() == CV_8UC1);
const std::string encoding = compressedImageEncoding(rgb);
if(encoding != sensor_msgs::image_encodings::MONO8 && encoding != sensor_msgs::image_encodings::BGR8)
{
return false;
}
}
if(!depth.empty())
{
UASSERT(depth.type() == CV_8UC1);
if(stereo)
{
// Right image, used in gray
return compressedImageEncoding(depth) == sensor_msgs::image_encodings::MONO8;
}
const unsigned char * d = depth.data;
const size_t size = depth.total();
const bool rtabmapFormat =
hasSignature(d, size, rtabmap::kCompressedDepthRvlSignature) ||
hasSignature(d, size, rtabmap::kCompressedDepthInvSignature);
// IHDR: 16 bits gray (16UC1), or 8 bits RGBA (legacy 32FC1)
const bool png = size > 25 && hasSignature(d, size, kPngSignature) &&
((d[24] == 16 && d[25] == 0) || (d[24] == 8 && d[25] == 6));
if(!rtabmapFormat && !png)
{
return false;
}
}
return true;
}
bool isValidDepthCompressionFormat(const std::string & format)
{
const std::string legacy = legacyDepthCompressionFormat(format);
std::string codec;
float maxDepth, quantization;
return rtabmap::parseImageCompressionFormat(legacy.empty() ? format : legacy, codec, maxDepth, quantization) &&
(codec == ".png" || codec == ".rvl");
}
bool compressDepthImage(const cv::Mat & depth, const std::string & format, sensor_msgs::msg::CompressedImage & msg)
{
if(depth.type() != CV_16UC1 && depth.type() != CV_32FC1)
{
UERROR("Depth image should be 16UC1 or 32FC1 (type=%d).", depth.type());
return false;
}
if(!isValidDepthCompressionFormat(format))
{
UERROR("Invalid depth compression format \"%s\".", format.c_str());
return false;
}
const std::string legacy = legacyDepthCompressionFormat(format);
if(!legacy.empty())
{
// rtabmap's own format, as Mem/DepthCompressionFormat: 32FC1 without depth
// parameters losslessly as 4 channels PNG. Readable by rtabmap_ros before 0.24,
// except inverse depth.
std::vector<unsigned char> bytes = rtabmap::compressImage(depth, legacy);
if(bytes.empty())
{
UERROR("Could not compress depth image with format \"%s\".", format.c_str());
return false;
}
msg.format = rtabmap::compressedDepthFormat(bytes).substr(1);
msg.data = std::move(bytes);
return true;
}
std::string codec;
float maxDepth, quantization;
rtabmap::parseImageCompressionFormat(format, codec, maxDepth, quantization);
cv::Mat image = depth;
if(depth.type() == CV_32FC1 && maxDepth <= 0.0f)
{
// No inverse depth parameters: rounded to millimeters, 0 (invalid) over 65.535 m
image = cv::Mat(depth.size(), CV_16UC1);
for(int i=0; i<depth.rows; ++i)
{
const float * in = depth.ptr<float>(i);
uint16_t * out = image.ptr<uint16_t>(i);
for(int j=0; j<depth.cols; ++j)
{
const float mm = in[j] * 1000.0f + 0.5f;
out[j] = mm >= 1.0f && mm < 65536.0f ? (uint16_t)mm : 0; // false for NaN
}
}
}
const cv::Mat bytes = rtabmap::compressImage2(image, image.type() == CV_32FC1 ? format : codec);
sensor_msgs::msg::CompressedImage out;
if(bytes.empty() || !rtabmapToCompressedDepthTransport(bytes, out))
{
UERROR("Could not compress depth image with format \"%s\".", format.c_str());
return false;
}
msg.format = std::move(out.format);
msg.data = std::move(out.data);
return true;
}
void infoFromROS(const rtabmap_msgs::msg::Info & info, rtabmap::Statistics & stat)
{
stat.setExtended(true); // Extended
// rtabmap_ros::Info
stat.setRefImageId(info.ref_id);
stat.setLoopClosureId(info.loop_closure_id);
stat.setProximityDetectionId(info.proximity_detection_id);
stat.setStamp(timestampFromROS(info.header.stamp));
stat.setLoopClosureTransform(rtabmap_conversions::transformFromGeometryMsg(info.loop_closure_transform));
//wmState
stat.setWmState(info.wm_state);
//Posterior, likelihood, childCount
std::map<int, float> mapIntFloat;
for(unsigned int i=0; i<info.posterior_keys.size() && i<info.posterior_values.size(); ++i)
{
mapIntFloat.insert(std::pair<int, float>(info.posterior_keys.at(i), info.posterior_values.at(i)));
}
stat.setPosterior(mapIntFloat);
mapIntFloat.clear();
for(unsigned int i=0; i<info.likelihood_keys.size() && i<info.likelihood_values.size(); ++i)
{
mapIntFloat.insert(std::pair<int, float>(info.likelihood_keys.at(i), info.likelihood_values.at(i)));
}
stat.setLikelihood(mapIntFloat);
mapIntFloat.clear();
for(unsigned int i=0; i<info.raw_likelihood_keys.size() && i<info.raw_likelihood_values.size(); ++i)
{
mapIntFloat.insert(std::pair<int, float>(info.raw_likelihood_keys.at(i), info.raw_likelihood_values.at(i)));
}
stat.setRawLikelihood(mapIntFloat);
std::map<int, int> mapIntInt;
for(unsigned int i=0; i<info.weights_keys.size() && i<info.weights_values.size(); ++i)
{
mapIntInt.insert(std::pair<int, int>(info.weights_keys.at(i), info.weights_values.at(i)));
}
stat.setWeights(mapIntInt);
std::map<int, std::string> mapIntStr;
for(unsigned int i=0; i<info.labels_keys.size() && i<info.labels_values.size(); ++i)
{
mapIntStr.insert(std::pair<int, std::string>(info.labels_keys.at(i), info.labels_values.at(i)));
}
stat.setLabels(mapIntStr);
stat.setLocalPath(info.local_path);
stat.setCurrentGoalId(info.current_goal_id);
std::map<int, rtabmap::Transform> poses;
std::multimap<int, rtabmap::Link> constraints;
rtabmap::Transform t;
mapGraphFromROS(info.odom_cache, poses, constraints, t);
stat.setOdomCachePoses(poses);
stat.setOdomCacheConstraints(constraints);
// Statistics data
for(unsigned int i=0; i<info.stats_keys.size() && i<info.stats_values.size(); i++)
{
stat.addStatistic(info.stats_keys.at(i), info.stats_values.at(i));
}
}
void infoToROS(const rtabmap::Statistics & stats, rtabmap_msgs::msg::Info & info)
{
// Fall back to the statistics' own stamp when the caller left the header unstamped.
// Callers that already stamped it keep their value, which may be a publication time
// unrelated to the data, or the exact input stamp rather than this double-derived one.
if(info.header.stamp.sec == 0 && info.header.stamp.nanosec == 0)
{
info.header.stamp = timestampToROS(stats.stamp());
}
info.ref_id = stats.refImageId();
info.loop_closure_id = stats.loopClosureId();
info.proximity_detection_id = stats.proximityDetectionId();
info.landmark_id = static_cast<int>(uValue(stats.data(), rtabmap::Statistics::kLoopLandmark_detected(), 0.0f));
rtabmap_conversions::transformToGeometryMsg(stats.loopClosureTransform(), info.loop_closure_transform);
// Detailed info
if(stats.extended())
{
//wmState
info.wm_state = stats.wmState();
//Posterior, likelihood, childCount
info.posterior_keys = uKeys(stats.posterior());
info.posterior_values = uValues(stats.posterior());
info.likelihood_keys = uKeys(stats.likelihood());
info.likelihood_values = uValues(stats.likelihood());
info.raw_likelihood_keys = uKeys(stats.rawLikelihood());
info.raw_likelihood_values = uValues(stats.rawLikelihood());
info.weights_keys = uKeys(stats.weights());
info.weights_values = uValues(stats.weights());
info.labels_keys = uKeys(stats.labels());
info.labels_values = uValues(stats.labels());
info.local_path = stats.localPath();
info.current_goal_id = stats.currentGoalId();
mapGraphToROS(stats.odomCachePoses(), stats.odomCacheConstraints(), stats.mapCorrection(), info.odom_cache);
// Statistics data
info.stats_keys = uKeys(stats.data());
info.stats_values = uValues(stats.data());
}
}
rtabmap::Link linkFromROS(const rtabmap_msgs::msg::Link & msg)
{
cv::Mat information = cv::Mat(6,6,CV_64FC1, (void*)msg.information.data()).clone();
return rtabmap::Link(msg.from_id, msg.to_id, (rtabmap::Link::Type)msg.type, transformFromGeometryMsg(msg.transform), information);
}
void linkToROS(const rtabmap::Link & link, rtabmap_msgs::msg::Link & msg)
{
msg.from_id = link.from();
msg.to_id = link.to();
msg.type = link.type();
if(link.infMatrix().type() == CV_64FC1 && link.infMatrix().cols == 6 && link.infMatrix().rows == 6)
{
memcpy(msg.information.data(), link.infMatrix().data, 36*sizeof(double));
}
transformToGeometryMsg(link.transform(), msg.transform);
}
cv::KeyPoint keypointFromROS(const rtabmap_msgs::msg::KeyPoint & msg)
{
return cv::KeyPoint(msg.pt.x, msg.pt.y, msg.size, msg.angle, msg.response, msg.octave, msg.class_id);
}
void keypointToROS(const cv::KeyPoint & kpt, rtabmap_msgs::msg::KeyPoint & msg)
{
msg.angle = kpt.angle;
msg.class_id = kpt.class_id;
msg.octave = kpt.octave;
msg.pt.x = kpt.pt.x;
msg.pt.y = kpt.pt.y;
msg.response = kpt.response;
msg.size = kpt.size;
}
std::vector<cv::KeyPoint> keypointsFromROS(const std::vector<rtabmap_msgs::msg::KeyPoint> & msg)
{
std::vector<cv::KeyPoint> v(msg.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
v[i] = keypointFromROS(msg[i]);
}
return v;
}
void keypointsFromROS(const std::vector<rtabmap_msgs::msg::KeyPoint> & msg, std::vector<cv::KeyPoint> & kpts, int xShift)
{
size_t outCurrentIndex = kpts.size();
kpts.resize(kpts.size()+msg.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
kpts[outCurrentIndex+i] = keypointFromROS(msg[i]);
kpts[outCurrentIndex+i].pt.x += xShift;
}
}
void keypointsToROS(const std::vector<cv::KeyPoint> & kpts, std::vector<rtabmap_msgs::msg::KeyPoint> & msg)
{
msg.resize(kpts.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
keypointToROS(kpts[i], msg[i]);
}
}
rtabmap::GlobalDescriptor globalDescriptorFromROS(const rtabmap_msgs::msg::GlobalDescriptor & msg)
{
return rtabmap::GlobalDescriptor(msg.type, rtabmap::uncompressData(msg.data), rtabmap::uncompressData(msg.info));
}
void globalDescriptorToROS(const rtabmap::GlobalDescriptor & desc, rtabmap_msgs::msg::GlobalDescriptor & msg)
{
msg.type = desc.type();
msg.info = rtabmap::compressData(desc.info());
msg.data = rtabmap::compressData(desc.data());
}
std::vector<rtabmap::GlobalDescriptor> globalDescriptorsFromROS(const std::vector<rtabmap_msgs::msg::GlobalDescriptor> & msg)
{
if(!msg.empty())
{
std::vector<rtabmap::GlobalDescriptor> v(msg.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
v[i] = globalDescriptorFromROS(msg[i]);
}
return v;
}
return std::vector<rtabmap::GlobalDescriptor>();
}
void globalDescriptorsToROS(const std::vector<rtabmap::GlobalDescriptor> & desc, std::vector<rtabmap_msgs::msg::GlobalDescriptor> & msg)
{
msg.clear();
if(!desc.empty())
{
msg.resize(desc.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
globalDescriptorToROS(desc[i], msg[i]);
}
}
}
rtabmap::EnvSensor envSensorFromROS(const rtabmap_msgs::msg::EnvSensor & msg)
{
return rtabmap::EnvSensor((rtabmap::EnvSensor::Type)msg.type, msg.value, timestampFromROS(msg.header.stamp));
}
void envSensorToROS(const rtabmap::EnvSensor & sensor, rtabmap_msgs::msg::EnvSensor & msg)
{
msg.type = sensor.type();
msg.value = sensor.value();
msg.header.stamp = timestampToROS(sensor.stamp());
}
rtabmap::EnvSensors envSensorsFromROS(const std::vector<rtabmap_msgs::msg::EnvSensor> & msg)
{
rtabmap::EnvSensors v;
if(!msg.empty())
{
for(unsigned int i=0; i<msg.size(); ++i)
{
rtabmap::EnvSensor s = envSensorFromROS(msg[i]);
v.insert(std::make_pair(s.type(), envSensorFromROS(msg[i])));
}
}
return v;
}
void envSensorsToROS(const rtabmap::EnvSensors & sensors, std::vector<rtabmap_msgs::msg::EnvSensor> & msg)
{
msg.clear();
if(!sensors.empty())
{
msg.resize(sensors.size());
int i=0;
for(rtabmap::EnvSensors::const_iterator iter=sensors.begin(); iter!=sensors.end(); ++iter)
{
envSensorToROS(iter->second, msg[i++]);
}
}
}
cv::Point2f point2fFromROS(const rtabmap_msgs::msg::Point2f & msg)
{
return cv::Point2f(msg.x, msg.y);
}
void point2fToROS(const cv::Point2f & kpt, rtabmap_msgs::msg::Point2f & msg)
{
msg.x = kpt.x;
msg.y = kpt.y;
}
std::vector<cv::Point2f> points2fFromROS(const std::vector<rtabmap_msgs::msg::Point2f> & msg)
{
std::vector<cv::Point2f> v(msg.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
v[i] = point2fFromROS(msg[i]);
}
return v;
}
void points2fToROS(const std::vector<cv::Point2f> & kpts, std::vector<rtabmap_msgs::msg::Point2f> & msg)
{
msg.resize(kpts.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
point2fToROS(kpts[i], msg[i]);
}
}
cv::Point3f point3fFromROS(const rtabmap_msgs::msg::Point3f & msg)
{
return cv::Point3f(msg.x, msg.y, msg.z);
}
void point3fToROS(const cv::Point3f & pt, rtabmap_msgs::msg::Point3f & msg)
{
msg.x = pt.x;
msg.y = pt.y;
msg.z = pt.z;
}
std::vector<cv::Point3f> points3fFromROS(const std::vector<rtabmap_msgs::msg::Point3f> & msg, const rtabmap::Transform & transform)
{
bool transformPoints = !transform.isNull() && !transform.isIdentity();
std::vector<cv::Point3f> v(msg.size());
for(unsigned int i=0; i<msg.size(); ++i)
{
v[i] = point3fFromROS(msg[i]);
if(transformPoints)
{
v[i] = rtabmap::util3d::transformPoint(v[i], transform);
}
}
return v;
}
void points3fFromROS(const std::vector<rtabmap_msgs::msg::Point3f> & msg, std::vector<cv::Point3f> & points3, const rtabmap::Transform & transform)
{
size_t currentIndex = points3.size();
points3.resize(points3.size()+msg.size());
bool transformPoint = !transform.isNull() && !transform.isIdentity();
for(unsigned int i=0; i<msg.size(); ++i)
{
points3[currentIndex+i] = point3fFromROS(msg[i]);
if(transformPoint)
{
points3[currentIndex+i] = rtabmap::util3d::transformPoint(points3[currentIndex+i], transform);
}
}
}
void points3fToROS(const std::vector<cv::Point3f> & pts, std::vector<rtabmap_msgs::msg::Point3f> & msg, const rtabmap::Transform & transform)
{
msg.resize(pts.size());
bool transformPoints = !transform.isNull() && !transform.isIdentity();
for(unsigned int i=0; i<msg.size(); ++i)
{
if(transformPoints)
{
cv::Point3f pt = rtabmap::util3d::transformPoint(pts[i], transform);
point3fToROS(pt, msg[i]);
}
else
{
point3fToROS(pts[i], msg[i]);
}
}
}
rtabmap::CameraModel cameraModelFromROS(
const sensor_msgs::msg::CameraInfo & camInfo,
const rtabmap::Transform & localTransform)
{
// Note: k, r and p are fixed-size arrays in the ROS message, so they are never
// empty and their size is always right. An unset matrix is signalled by all-zero
// content instead: k[0] and p[0] hold the focal length, which is always non-zero
// for a valid calibration, and an unset rectification matrix is all zeros.
cv:: Mat K;
if(camInfo.k[0] != 0.0)
{
K = cv::Mat(3, 3, CV_64FC1);
memcpy(K.data, camInfo.k.data(), 9*sizeof(double));
}
cv::Mat D;
if(camInfo.d.size())
{
if(camInfo.d.size()>=4 &&
(uStrContains(camInfo.distortion_model, "fisheye") ||
uStrContains(camInfo.distortion_model, "equidistant") ||
uStrContains(camInfo.distortion_model, "Kannala Brandt4")))
{
D = cv::Mat::zeros(1, 6, CV_64FC1);
D.at<double>(0,0) = camInfo.d[0];
D.at<double>(0,1) = camInfo.d[1];
D.at<double>(0,4) = camInfo.d[2];
D.at<double>(0,5) = camInfo.d[3];
}
else
{
D = cv::Mat(1, camInfo.d.size(), CV_64FC1);
memcpy(D.data, camInfo.d.data(), D.cols*sizeof(double));
}
}
// R is a rotation matrix, so any of its elements can legitimately be zero: only
// an entirely zero matrix means "not set".
cv:: Mat R;
bool rIsSet = false;
for(size_t i=0; !rIsSet && i<camInfo.r.size(); ++i)
{
rIsSet = camInfo.r[i] != 0.0;
}
if(rIsSet)
{
R = cv::Mat(3, 3, CV_64FC1);
memcpy(R.data, camInfo.r.data(), 9*sizeof(double));
}
cv:: Mat P;
if(camInfo.p[0] != 0.0)
{
P = cv::Mat(3, 4, CV_64FC1);
memcpy(P.data, camInfo.p.data(), 12*sizeof(double));
}
return rtabmap::CameraModel(
"ros",
cv::Size(camInfo.width, camInfo.height),
K, D, R, P,
localTransform);
}
void cameraModelToROS(
const rtabmap::CameraModel & model,
sensor_msgs::msg::CameraInfo & camInfo)
{
UASSERT(model.K_raw().empty() || model.K_raw().total() == 9);
UASSERT(model.P().empty() || model.P().total() == 12);
if(!model.P().empty())
{
model.P().colRange(0,3).copyTo(cv::Mat(3,3,CV_64FC1, camInfo.k.data()));
}
else if(model.K_raw().empty())
{
memset(camInfo.k.data(), 0.0, 9*sizeof(double));
}
else
{
memcpy(camInfo.k.data(), model.K_raw().data, 9*sizeof(double));
}
if(!model.P().empty()) {
camInfo.d = std::vector<double>(model.D().cols);
memcpy(camInfo.d.data(), model.D().data, model.D().cols*sizeof(double));
camInfo.distortion_model = "plumb_bob";
}
else if(model.D_raw().total() == 6)
{
camInfo.d = std::vector<double>(4);
camInfo.d[0] = model.D_raw().at<double>(0,0);
camInfo.d[1] = model.D_raw().at<double>(0,1);
camInfo.d[2] = model.D_raw().at<double>(0,4);
camInfo.d[3] = model.D_raw().at<double>(0,5);
camInfo.distortion_model = "equidistant"; // fisheye
}
else
{
camInfo.d = std::vector<double>(model.D_raw().cols);
memcpy(camInfo.d.data(), model.D_raw().data, model.D_raw().cols*sizeof(double));
if(camInfo.d.size() > 5)
{
camInfo.distortion_model = "rational_polynomial";
}
else
{
camInfo.distortion_model = "plumb_bob";
}
}
UASSERT(model.R().empty() || model.R().total() == 9);
if(model.R().empty() || countNonZero(model.R()) == 0)
{
cv::Mat eye = cv::Mat::eye(3,3,CV_64FC1);
memcpy(camInfo.r.data(), eye.data, 9*sizeof(double));
}
else
{
memcpy(camInfo.r.data(), model.R().data, 9*sizeof(double));
}
if(model.P().empty())
{
memset(camInfo.p.data(), 0.0, 12*sizeof(double));
if(!model.K_raw().empty()) {
// P = [K | 0]: copying K already sets the homogeneous P(2,2)=1, and the
// fourth column (the Tx/Ty/Tz translation) stays zero for a single camera.
model.K_raw().copyTo(cv::Mat(3,4,CV_64FC1, camInfo.p.data()).colRange(0,3));
}
}
else
{
memcpy(camInfo.p.data(), model.P().data, 12*sizeof(double));
}
camInfo.binning_x = 1;
camInfo.binning_y = 1;
camInfo.roi.width = model.imageWidth();
camInfo.roi.height = model.imageHeight();
camInfo.width = model.imageWidth();
camInfo.height = model.imageHeight();
}
rtabmap::StereoCameraModel stereoCameraModelFromROS(
const sensor_msgs::msg::CameraInfo & leftCamInfo,
const sensor_msgs::msg::CameraInfo & rightCamInfo,
const rtabmap::Transform & localTransform,
const rtabmap::Transform & stereoTransform)
{
return rtabmap::StereoCameraModel(
"ros",
cameraModelFromROS(leftCamInfo, localTransform),
cameraModelFromROS(rightCamInfo, localTransform),
stereoTransform);
}
rtabmap::StereoCameraModel stereoCameraModelFromROS(
const sensor_msgs::msg::CameraInfo & leftCamInfo,
const sensor_msgs::msg::CameraInfo & rightCamInfo,
const std::string & frameId,
tf2_ros::Buffer & tfBuffer,
double waitForTransform)
{
rtabmap::Transform localTransform = getTransform(
frameId,
leftCamInfo.header.frame_id,
leftCamInfo.header.stamp,
tfBuffer,
waitForTransform);
if(localTransform.isNull())
{
return rtabmap::StereoCameraModel();
}
rtabmap::Transform stereoTransform = getTransform(
leftCamInfo.header.frame_id,
rightCamInfo.header.frame_id,
leftCamInfo.header.stamp,
tfBuffer,
waitForTransform);
if(stereoTransform.isNull())
{
return rtabmap::StereoCameraModel();
}
return stereoCameraModelFromROS(leftCamInfo, rightCamInfo, localTransform, stereoTransform);
}
void mapDataFromROS(
const rtabmap_msgs::msg::MapData & msg,
std::map<int, rtabmap::Transform> & poses,
std::multimap<int, rtabmap::Link> & links,
std::map<int, rtabmap::Signature> & signatures,
rtabmap::Transform & map_to_odom)
{
//optimized graph
mapGraphFromROS(msg.graph, poses, links, map_to_odom);
//Data
for(unsigned int i=0; i<msg.nodes.size(); ++i)
{
signatures.insert(std::make_pair(msg.nodes[i].id, nodeFromROS(msg.nodes[i])));
}
}
void mapDataToROS(
const std::map<int, rtabmap::Transform> & poses,
const std::multimap<int, rtabmap::Link> & links,
const std::map<int, rtabmap::Signature> & signatures,
const rtabmap::Transform & map_to_odom,
rtabmap_msgs::msg::MapData & msg)
{
//Optimized graph
mapGraphToROS(poses, links, map_to_odom, msg.graph);
//Data
msg.nodes.resize(signatures.size());
int index=0;
for(std::multimap<int, rtabmap::Signature>::const_iterator iter = signatures.begin();
iter!=signatures.end();
++iter)
{
nodeToROS(iter->second, msg.nodes[index++]);
}
}
void mapGraphFromROS(
const rtabmap_msgs::msg::MapGraph & msg,
std::map<int, rtabmap::Transform> & poses,
std::multimap<int, rtabmap::Link> & links,
rtabmap::Transform & map_to_odom)
{
//optimized graph
UASSERT(msg.poses_id.size() == msg.poses.size());
for(unsigned int i=0; i<msg.poses_id.size(); ++i)
{
poses.insert(std::make_pair(msg.poses_id[i], rtabmap_conversions::transformFromPoseMsg(msg.poses[i])));
}
for(unsigned int i=0; i<msg.links.size(); ++i)
{
rtabmap::Transform t = rtabmap_conversions::transformFromGeometryMsg(msg.links[i].transform);
links.insert(std::make_pair(msg.links[i].from_id, linkFromROS(msg.links[i])));
}
map_to_odom = transformFromGeometryMsg(msg.map_to_odom);
}
void mapGraphToROS(
const std::map<int, rtabmap::Transform> & poses,
const std::multimap<int, rtabmap::Link> & links,
const rtabmap::Transform & map_to_odom,
rtabmap_msgs::msg::MapGraph & msg)
{
//Optimized graph
msg.poses_id.resize(poses.size());
msg.poses.resize(poses.size());
int index = 0;
for(std::map<int, rtabmap::Transform>::const_iterator iter = poses.begin();
iter != poses.end();
++iter)
{
msg.poses_id[index] = iter->first;
transformToPoseMsg(iter->second, msg.poses[index]);
++index;
}
msg.links.resize(links.size());
index=0;
for(std::multimap<int, rtabmap::Link>::const_iterator iter = links.begin();
iter!=links.end();
++iter)
{
linkToROS(iter->second, msg.links[index++]);
}
transformToGeometryMsg(map_to_odom, msg.map_to_odom);
}
rtabmap::SensorData sensorDataFromROS(const rtabmap_msgs::msg::SensorData & msg)
{
rtabmap::SensorData s(
cv::Mat(),
0,
timestampFromROS(msg.header.stamp),
compressedMatFromBytes(msg.user_data));
std::vector<rtabmap::StereoCameraModel> stereoModels;
std::vector<rtabmap::CameraModel> models;
bool isStereo = !msg.right_camera_info.empty();
if(isStereo)
{
// stereo model
if(msg.left_camera_info.size() == msg.right_camera_info.size() &&
msg.local_transform.size() == msg.right_camera_info.size())
{
for(unsigned int i=0; i<msg.right_camera_info.size(); ++i)
{
stereoModels.push_back(stereoCameraModelFromROS(
msg.left_camera_info[i],
msg.right_camera_info[i],
transformFromGeometryMsg(msg.local_transform[i])
));
}
}
}
else
{
// multi-cameras model
if(msg.left_camera_info.size() &&
msg.local_transform.size() == msg.left_camera_info.size())
{
for(unsigned int i=0; i<msg.left_camera_info.size(); ++i)
{
models.push_back(cameraModelFromROS(
msg.left_camera_info[i],
transformFromGeometryMsg(msg.local_transform[i])));
}
}
}
// Image data
cv::Mat left, right;
if(!msg.left.data.empty())
{
std::shared_ptr<void const> trackedObject;
cv_bridge::CvImageConstPtr leftRawPtr = cv_bridge::toCvShare(msg.left, trackedObject);
if(!(leftRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) ==0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO8) ==0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO16) ==0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::BGRA8) == 0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::RGBA8) == 0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::BAYER_GRBG8)))
{
UERROR("Input type must be image=mono8,mono16,rgb8,bgr8 (mono8 recommended), received type is %s. Will return data without left/rgb raw image.",
leftRawPtr->encoding.c_str());
}
else
{
try {
if( leftRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
leftRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0)
{
left = leftRawPtr->image.clone();
}
else if(leftRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0)
{
left = cv_bridge::cvtColor(leftRawPtr, "mono8")->image;
}
else
{
left = cv_bridge::cvtColor(leftRawPtr, "bgr8")->image;
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting left image (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
}
}
if(!msg.right.data.empty())
{
std::shared_ptr<void const> trackedObject;
cv_bridge::CvImageConstPtr rightRawPtr = cv_bridge::toCvShare(msg.right, trackedObject);
if(!(rightRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) ==0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO8) ==0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO16) ==0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_16UC1) == 0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_32FC1) == 0))
{
UERROR("Input type must be image=mono8,mono16,rgb8,bgr8,32FC1,16UC1, received type is %s. Will return data without right/depth raw image.",
rightRawPtr->encoding.c_str());
}
else
{
try{
if( rightRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0 ||
(!isStereo &&
(rightRawPtr->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_16UC1) == 0 ||
rightRawPtr->encoding.compare(sensor_msgs::image_encodings::TYPE_32FC1) == 0)))
{
right = rightRawPtr->image.clone();
}
else
{
right = cv_bridge::cvtColor(rightRawPtr, "mono8")->image;
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting right image (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
}
}
if(isStereo)
{
s.setStereoImage(
compressedMatFromBytes(msg.left_compressed),
compressedMatFromBytes(msg.right_compressed),
stereoModels);
// Raw images override their compressed ones; an image without its raw
// version stays compressed only.
if(!left.empty() || !right.empty())
{
s.setStereoImage(left, right, stereoModels, false);
}
}
else
{
s.setRGBDImage(
compressedMatFromBytes(msg.left_compressed),
compressedMatFromBytes(msg.right_compressed),
models);
// Raw images override their compressed ones; an image without its raw
// version stays compressed only.
if(!left.empty() || !right.empty())
{
s.setRGBDImage(left, right, models, false);
}
}
// Laser scan data
if(!msg.laser_scan_compressed.empty())
{
s.setLaserScan(rtabmap::LaserScan(
compressedMatFromBytes(msg.laser_scan_compressed),
msg.laser_scan_max_pts,
msg.laser_scan_max_range,
(rtabmap::LaserScan::Format)msg.laser_scan_format,
transformFromGeometryMsg(msg.laser_scan_local_transform)));
}
if(!msg.laser_scan.data.empty())
{
pcl::PCLPointCloud2 cloud;
pcl_conversions::toPCL(msg.laser_scan, cloud);
s.setLaserScan(rtabmap::LaserScan(
rtabmap::util3d::laserScanFromPointCloud(cloud, true,
rtabmap::LaserScan::isScan2d((rtabmap::LaserScan::Format)msg.laser_scan_format)),
msg.laser_scan_max_pts,
msg.laser_scan_max_range,
transformFromGeometryMsg(msg.laser_scan_local_transform)),
false);
UASSERT((rtabmap::LaserScan::Format)msg.laser_scan_format == s.laserScanRaw().format());
}
//convert features
std::vector<cv::KeyPoint> keypoints;
std::vector<cv::Point3f> keypoints3D;
cv::Mat descriptors;
if(!msg.key_points.empty())
{
keypoints = rtabmap_conversions::keypointsFromROS(msg.key_points);
}
if(!msg.points.empty())
{
keypoints3D = rtabmap_conversions::points3fFromROS(msg.points);
}
if(!msg.descriptors.empty())
{
descriptors = rtabmap::uncompressData(msg.descriptors);
}
s.setFeatures(keypoints, keypoints3D, descriptors);
s.setGlobalDescriptors(rtabmap_conversions::globalDescriptorsFromROS(msg.global_descriptors));
s.setEnvSensors(rtabmap_conversions::envSensorsFromROS(msg.env_sensors));
s.setOccupancyGrid(
compressedMatFromBytes(msg.grid_ground),
compressedMatFromBytes(msg.grid_obstacles),
compressedMatFromBytes(msg.grid_empty_cells),
msg.grid_cell_size,
point3fFromROS(msg.grid_view_point));
s.setGPS(rtabmap::GPS(msg.gps.stamp, msg.gps.longitude, msg.gps.latitude, msg.gps.altitude, msg.gps.error, msg.gps.bearing));
s.setIMU(rtabmap_conversions::imuFromROS(msg.imu, transformFromGeometryMsg(msg.imu_local_transform)));
return s;
}
void sensorDataToROS(const rtabmap::SensorData & data, rtabmap_msgs::msg::SensorData & msg, const std::string & frameId, bool copyRawData)
{
// add data
msg.header.stamp = timestampToROS(data.stamp());
msg.header.frame_id = frameId;
transformToPoseMsg(data.groundTruth(), msg.ground_truth_pose);
msg.gps.stamp = data.gps().stamp();
msg.gps.longitude = data.gps().longitude();
msg.gps.latitude = data.gps().latitude();
msg.gps.altitude = data.gps().altitude();
msg.gps.error = data.gps().error();
msg.gps.bearing = data.gps().bearing();
//Calibration
if(data.cameraModels().size())
{
msg.left_camera_info.resize(data.cameraModels().size());
msg.local_transform.resize(data.cameraModels().size());
for(unsigned int i=0; i<data.cameraModels().size(); ++i)
{
cameraModelToROS(data.cameraModels()[i], msg.left_camera_info[i]);
transformToGeometryMsg(data.cameraModels()[i].localTransform(), msg.local_transform[i]);
}
}
else if(data.stereoCameraModels().size())
{
msg.left_camera_info.resize(data.stereoCameraModels().size());
msg.right_camera_info.resize(data.stereoCameraModels().size());
msg.local_transform.resize(data.stereoCameraModels().size());
for(unsigned int i=0; i<data.stereoCameraModels().size(); ++i)
{
cameraModelToROS(data.stereoCameraModels()[i].left(), msg.left_camera_info[i]);
cameraModelToROS(data.stereoCameraModels()[i].right(), msg.right_camera_info[i]);
transformToGeometryMsg(data.stereoCameraModels()[i].left().localTransform(), msg.local_transform[i]);
}
}
// Images
if(copyRawData)
{
if(!data.imageRaw().empty())
{
cv_bridge::CvImage cvImg;
cvImg.image = data.imageRaw();
UASSERT(data.imageRaw().type()==CV_8UC1 || data.imageRaw().type()==CV_8UC3);
cvImg.encoding = data.imageRaw().type()==CV_8UC1?sensor_msgs::image_encodings::MONO8:sensor_msgs::image_encodings::BGR8;
cvImg.toImageMsg(msg.left);
}
if(!data.depthOrRightRaw().empty())
{
cv_bridge::CvImage cvDepth;
cvDepth.image = data.depthOrRightRaw();
UASSERT(data.depthOrRightRaw().type()==CV_8UC1 || data.depthOrRightRaw().type()==CV_16UC1 || data.depthOrRightRaw().type()==CV_32FC1);
cvDepth.encoding = data.depthOrRightRaw().type()==CV_8UC1?sensor_msgs::image_encodings::MONO8:data.depthOrRightRaw().type()==CV_16UC1?sensor_msgs::image_encodings::TYPE_16UC1:sensor_msgs::image_encodings::TYPE_32FC1;
cvDepth.toImageMsg(msg.right);
}
}
compressedMatToBytes(data.imageCompressed(), msg.left_compressed);
compressedMatToBytes(data.depthOrRightCompressed(), msg.right_compressed);
// Laser scan
if(copyRawData && !data.laserScanRaw().empty())
{
pcl::PCLPointCloud2::Ptr cloud = rtabmap::util3d::laserScanToPointCloud2(data.laserScanRaw());
pcl_conversions::moveFromPCL(*cloud, msg.laser_scan);
// Describe the scan we just serialized: reading these from laserScanCompressed()
// zeroes them whenever only the raw scan is set, and sensorDataFromROS() then
// fails its format assertion.
msg.laser_scan_max_pts = data.laserScanRaw().maxPoints();
msg.laser_scan_max_range = data.laserScanRaw().rangeMax();
msg.laser_scan_format = data.laserScanRaw().format();
transformToGeometryMsg(data.laserScanRaw().localTransform(), msg.laser_scan_local_transform);
}
if(!data.laserScanCompressed().empty())
{
compressedMatToBytes(data.laserScanCompressed().data(), msg.laser_scan_compressed);
msg.laser_scan_max_pts = data.laserScanCompressed().maxPoints();
msg.laser_scan_max_range = data.laserScanCompressed().rangeMax();
msg.laser_scan_format = data.laserScanCompressed().format();
transformToGeometryMsg(data.laserScanCompressed().localTransform(), msg.laser_scan_local_transform);
}
// user data
if(!data.userDataCompressed().empty())
{
compressedMatToBytes(data.userDataCompressed(), msg.user_data);
}
else if(copyRawData && !data.userDataRaw().empty())
{
compressedMatToBytes(rtabmap::compressData2(data.userDataRaw()), msg.user_data);
}
// oocupancy grid
if(!data.gridGroundCellsCompressed().empty())
{
compressedMatToBytes(data.gridGroundCellsCompressed(), msg.grid_ground);
}
else if(copyRawData && !data.gridGroundCellsRaw().empty())
{
compressedMatToBytes(rtabmap::compressData2(data.gridGroundCellsRaw()), msg.grid_ground);
}
if(!data.gridObstacleCellsCompressed().empty())
{
compressedMatToBytes(data.gridObstacleCellsCompressed(), msg.grid_obstacles);
}
else if(copyRawData && !data.gridObstacleCellsRaw().empty())
{
compressedMatToBytes(rtabmap::compressData2(data.gridObstacleCellsRaw()), msg.grid_obstacles);
}
if(!data.gridEmptyCellsCompressed().empty())
{
compressedMatToBytes(data.gridEmptyCellsCompressed(), msg.grid_empty_cells);
}
else if(copyRawData && !data.gridEmptyCellsRaw().empty())
{
compressedMatToBytes(rtabmap::compressData2(data.gridEmptyCellsRaw()), msg.grid_empty_cells);
}
point3fToROS(data.gridViewPoint(), msg.grid_view_point);
msg.grid_cell_size = data.gridCellSize();
//convert features
if(!data.keypoints().empty())
{
rtabmap_conversions::keypointsToROS(data.keypoints(), msg.key_points);
}
if(!data.keypoints3D().empty())
{
rtabmap_conversions::points3fToROS(data.keypoints3D(), msg.points);
}
if(!data.descriptors().empty())
{
msg.descriptors = rtabmap::compressData(data.descriptors());
}
if(!data.globalDescriptors().empty())
{
rtabmap_conversions::globalDescriptorsToROS(data.globalDescriptors(), msg.global_descriptors);
}
rtabmap_conversions::globalDescriptorsToROS(data.globalDescriptors(), msg.global_descriptors);
rtabmap_conversions::envSensorsToROS(data.envSensors(), msg.env_sensors);
rtabmap_conversions::imuToROS(data.imu(), msg.imu);
transformToGeometryMsg(data.imu().localTransform(), msg.imu_local_transform);
}
rtabmap::Signature nodeFromROS(const rtabmap_msgs::msg::Node & msg)
{
//Features stuff...
std::multimap<int, int> words;
std::vector<cv::KeyPoint> wordsKpts;
std::vector<cv::Point3f> words3D;
cv::Mat wordsDescriptors = rtabmap::uncompressData(msg.word_descriptors);
if(msg.word_id_keys.size() != msg.word_id_values.size())
{
UERROR("Word ID keys and values should be the same size (%d, %d)!", (int)msg.word_id_keys.size(), (int)msg.word_id_values.size());
}
if(!msg.word_kpts.empty() && msg.word_kpts.size() != msg.word_id_keys.size())
{
UERROR("Word IDs and 2D keypoints should be the same size (%d, %d)!", (int)msg.word_id_keys.size(), (int)msg.word_kpts.size());
}
if(!msg.word_pts.empty() && msg.word_pts.size() != msg.word_id_keys.size())
{
UERROR("Word IDs and 3D points should be the same size (%d, %d)!", (int)msg.word_id_keys.size(), (int)msg.word_pts.size());
}
if(!wordsDescriptors.empty() && wordsDescriptors.rows != (int)msg.word_id_keys.size())
{
UERROR("Word IDs and descriptors should be the same size (%d, %d)!", (int)msg.word_id_keys.size(), wordsDescriptors.rows);
wordsDescriptors = cv::Mat();
}
rtabmap::Signature s(
msg.id,
msg.map_id,
msg.weight,
msg.stamp,
msg.label,
transformFromPoseMsg(msg.pose),
transformFromPoseMsg(msg.data.ground_truth_pose));
if(msg.word_id_keys.size() == msg.word_id_values.size())
{
for(unsigned int i=0; i<msg.word_id_keys.size(); ++i)
{
words.insert(std::make_pair(msg.word_id_keys.at(i), msg.word_id_values.at(i))); // ID to index
if(msg.word_id_keys.size() == msg.word_kpts.size())
{
if(wordsKpts.empty())
{
wordsKpts.reserve(msg.word_kpts.size());
}
wordsKpts.push_back(keypointFromROS(msg.word_kpts.at(i)));
}
if(msg.word_id_keys.size() == msg.word_pts.size())
{
if(words3D.empty())
{
words3D.reserve(msg.word_pts.size());
}
words3D.push_back(point3fFromROS(msg.word_pts[i]));
}
}
}
s.setWords(words, wordsKpts, words3D, wordsDescriptors);
s.sensorData() = sensorDataFromROS(msg.data);
s.sensorData().setId(msg.id);
return s;
}
void nodeToROS(const rtabmap::Signature & signature, rtabmap_msgs::msg::Node & msg)
{
// add data
msg.id = signature.id();
msg.map_id = signature.mapId();
msg.weight = signature.getWeight();
msg.stamp = signature.getStamp();
msg.label = signature.getLabel();
transformToPoseMsg(signature.getPose(), msg.pose);
//Features stuff...
if(!signature.getWordsKpts().empty() &&
signature.getWords().size() != signature.getWordsKpts().size())
{
UERROR("Word IDs and 2D keypoints must have the same size (%d vs %d)!",
(int)signature.getWords().size(),
(int)signature.getWordsKpts().size());
}
if(!signature.getWords3().empty() &&
signature.getWords().size() != signature.getWords3().size())
{
UERROR("Word IDs and 3D points must have the same size (%d vs %d)!",
(int)signature.getWords().size(),
(int)signature.getWords3().size());
}
int i=0;
msg.word_id_keys.resize(signature.getWords().size());
msg.word_id_values.resize(signature.getWords().size());
for(std::multimap<int, int>::const_iterator iter=signature.getWords().begin();
iter!=signature.getWords().end();
++iter)
{
msg.word_id_keys.at(i) = iter->first;
msg.word_id_values.at(i) = iter->second;
if(signature.getWordsKpts().size() == signature.getWords().size())
{
if(msg.word_kpts.empty())
{
msg.word_kpts.resize(signature.getWords().size());
}
keypointToROS(signature.getWordsKpts().at(i), msg.word_kpts.at(i));
}
if(signature.getWords3().size() == signature.getWords().size())
{
if(msg.word_pts.empty())
{
msg.word_pts.resize(signature.getWords().size());
}
point3fToROS(signature.getWords3().at(i), msg.word_pts.at(i));
}
++i;
}
if(!signature.getWordsDescriptors().empty())
{
if(signature.getWordsDescriptors().rows == (int)signature.getWords().size())
{
msg.word_descriptors = rtabmap::compressData(signature.getWordsDescriptors());
}
else
{
UERROR("Word IDs and descriptors must have the same size (%d vs %d)!",
(int)signature.getWords().size(),
signature.getWordsDescriptors().rows);
}
}
sensorDataToROS(signature.sensorData(), msg.data);
transformToPoseMsg(signature.getGroundTruthPose(), msg.data.ground_truth_pose);
}
rtabmap::Signature nodeDataFromROS(const rtabmap_msgs::msg::Node & msg)
{
return nodeFromROS(msg);
}
void nodeDataToROS(const rtabmap::Signature & signature, rtabmap_msgs::msg::Node & msg)
{
nodeToROS(signature, msg);
}
rtabmap::Signature nodeInfoFromROS(const rtabmap_msgs::msg::Node & msg)
{
rtabmap::Signature s(
msg.id,
msg.map_id,
msg.weight,
msg.stamp,
msg.label,
transformFromPoseMsg(msg.pose),
transformFromPoseMsg(msg.data.ground_truth_pose));
return s;
}
void nodeInfoToROS(const rtabmap::Signature & signature, rtabmap_msgs::msg::Node & msg)
{
// add data
msg.id = signature.id();
msg.map_id = signature.mapId();
msg.weight = signature.getWeight();
msg.stamp = signature.getStamp();
msg.label = signature.getLabel();
transformToPoseMsg(signature.getPose(), msg.pose);
transformToPoseMsg(signature.getGroundTruthPose(), msg.data.ground_truth_pose);
}
std::map<std::string, float> odomInfoToStatistics(const rtabmap::OdometryInfo & info)
{
std::map<std::string, float> stats;
stats.insert(std::make_pair("Odometry/TimeRegistration/ms", info.reg.totalTime*1000.0f));
stats.insert(std::make_pair("Odometry/RAM_usage/MB", info.memoryUsage));
// Based on rtabmap/MainWindow.cpp
stats.insert(std::make_pair("Odometry/Features/", info.features));
stats.insert(std::make_pair("Odometry/Matches/", info.reg.matches));
stats.insert(std::make_pair("Odometry/MatchesRatio/", info.features<=0?0.0f:float(info.reg.inliers)/float(info.features)));
stats.insert(std::make_pair("Odometry/Inliers/", info.reg.inliers));
stats.insert(std::make_pair("Odometry/InliersMeanDistance/m", info.reg.inliersMeanDistance));
stats.insert(std::make_pair("Odometry/InliersDistribution/", info.reg.inliersDistribution));
stats.insert(std::make_pair("Odometry/InliersRatio/", info.reg.inliers));
stats.insert(std::make_pair("Odometry/ICPInliersRatio/", info.reg.icpInliersRatio));
stats.insert(std::make_pair("Odometry/ICPRotation/rad", info.reg.icpRotation));
stats.insert(std::make_pair("Odometry/icp_translation/m", info.reg.icpTranslation));
stats.insert(std::make_pair("Odometry/ICPStructuralComplexity/", info.reg.icpStructuralComplexity));
stats.insert(std::make_pair("Odometry/ICPStructuralDistribution/", info.reg.icpStructuralDistribution));
stats.insert(std::make_pair("Odometry/ICPCorrespondences/", info.reg.icpCorrespondences));
// RegistrationInfo leaves covariance empty by default, so only read it when the
// expected 6x6 matrix is actually there.
if(info.reg.covariance.type() == CV_64FC1 &&
info.reg.covariance.rows == 6 &&
info.reg.covariance.cols == 6)
{
stats.insert(std::make_pair("Odometry/StdDevLin/", sqrt((float)info.reg.covariance.at<double>(0,0))));
stats.insert(std::make_pair("Odometry/StdDevAng/", sqrt((float)info.reg.covariance.at<double>(5,5))));
stats.insert(std::make_pair("Odometry/VarianceLin/", (float)info.reg.covariance.at<double>(0,0)));
stats.insert(std::make_pair("Odometry/VarianceAng/", (float)info.reg.covariance.at<double>(5,5)));
}
stats.insert(std::make_pair("Odometry/TimeEstimation/ms", info.timeEstimation*1000.0f));
stats.insert(std::make_pair("Odometry/TimeFiltering/ms", info.timeParticleFiltering*1000.0f));
stats.insert(std::make_pair("Odometry/LocalMapSize/", info.localMapSize));
stats.insert(std::make_pair("Odometry/LocalScanMapSize/", info.localScanMapSize));
stats.insert(std::make_pair("Odometry/LocalKeyFrames/", info.localKeyFrames));
stats.insert(std::make_pair("Odometry/LocalBundleOutliers/", info.localBundleOutliers));
stats.insert(std::make_pair("Odometry/LocalBundleConstraints/", info.localBundleConstraints));
stats.insert(std::make_pair("Odometry/LocalBundleTime/ms", info.localBundleTime*1000.0f));
stats.insert(std::make_pair("Odometry/localBundleAvgInlierDistance/pix", info.localBundleAvgInlierDistance));
stats.insert(std::make_pair("Odometry/localBundleMaxKeyFramesForInlier/", info.localBundleMaxKeyFramesForInlier));
stats.insert(std::make_pair("Odometry/KeyFrameAdded/", info.keyFrameAdded?1.0f:0.0f));
stats.insert(std::make_pair("Odometry/Interval/ms", (float)info.interval));
stats.insert(std::make_pair("Odometry/Distance/m", info.distanceTravelled));
float x,y,z,roll,pitch,yaw;
float dist = 0.0f, speed=0.0f;
if(!info.transform.isNull())
{
info.transform.getTranslationAndEulerAngles(x,y,z,roll,pitch,yaw);
dist = info.transform.getNorm();
stats.insert(std::make_pair("Odometry/T/m", dist));
stats.insert(std::make_pair("Odometry/Tx/m", x));
stats.insert(std::make_pair("Odometry/Ty/m", y));
stats.insert(std::make_pair("Odometry/Tz/m", z));
stats.insert(std::make_pair("Odometry/Troll/deg", roll*180.0/CV_PI));
stats.insert(std::make_pair("Odometry/Tpitch/deg", pitch*180.0/CV_PI));
stats.insert(std::make_pair("Odometry/Tyaw/deg", yaw*180.0/CV_PI));
if(info.interval>0.0)
{
speed = dist/info.interval;
stats.insert(std::make_pair("Odometry/Speed/kph", speed*3.6));
stats.insert(std::make_pair("Odometry/Speed/mph", speed*2.237));
stats.insert(std::make_pair("Odometry/Speed/mps", speed));
}
}
if(!info.transformGroundTruth.isNull())
{
if(!info.transform.isNull())
{
stats.insert(std::make_pair("Odometry/TG_error_lin/m", info.transformGroundTruth.getDistance(info.transform)));
stats.insert(std::make_pair("Odometry/TG_error_ang/deg", info.transformGroundTruth.getAngle(info.transform)*180.0/CV_PI));
}
info.transformGroundTruth.getTranslationAndEulerAngles(x,y,z,roll,pitch,yaw);
dist = info.transformGroundTruth.getNorm();
stats.insert(std::make_pair("Odometry/TG/m", dist));
stats.insert(std::make_pair("Odometry/TGx/m", x));
stats.insert(std::make_pair("Odometry/TGy/m", y));
stats.insert(std::make_pair("Odometry/TGz/m", z));
stats.insert(std::make_pair("Odometry/TGroll/deg", roll*180.0/CV_PI));
stats.insert(std::make_pair("Odometry/TGpitch/deg", pitch*180.0/CV_PI));
stats.insert(std::make_pair("Odometry/TGyaw/deg", yaw*180.0/CV_PI));
if(info.interval>0.0)
{
speed = dist/info.interval;
stats.insert(std::make_pair("Odometry/SpeedG/kph", speed*3.6));
stats.insert(std::make_pair("Odometry/SpeedG/mph", speed*2.237));
stats.insert(std::make_pair("Odometry/SpeedG/mps", speed));
}
}
return stats;
}
rtabmap::OdometryInfo odomInfoFromROS(const rtabmap_msgs::msg::OdomInfo & msg, bool ignoreData)
{
rtabmap::OdometryInfo info;
info.lost = msg.lost;
info.reg.matches = msg.matches;
info.reg.inliers = msg.inliers;
info.reg.icpInliersRatio = msg.icp_inliers_ratio;
info.reg.icpRotation = msg.icp_rotation;
info.reg.icpTranslation = msg.icp_translation;
info.reg.icpStructuralComplexity = msg.icp_structural_complexity;
info.reg.icpStructuralDistribution = msg.icp_structural_distribution;
info.reg.icpCorrespondences = msg.icp_correspondences;
info.reg.covariance = cv::Mat(6,6,CV_64FC1, (void*)msg.covariance.data()).clone();
info.features = msg.features;
info.localMapSize = msg.local_map_size;
info.localScanMapSize = msg.local_scan_map_size;
info.localKeyFrames = msg.local_key_frames;
info.localBundleOutliers = msg.local_bundle_outliers;
info.localBundleConstraints = msg.local_bundle_constraints;
info.localBundleTime = msg.local_bundle_time;
info.localBundleAvgInlierDistance = msg.local_bundle_avg_inlier_distance;
info.localBundleMaxKeyFramesForInlier = msg.local_bundle_max_key_frames_for_inlier;
info.keyFrameAdded = msg.key_frame_added;
info.timeEstimation = msg.time_estimation;
info.timeParticleFiltering = msg.time_particle_filtering;
info.stamp = msg.stamp;
info.interval = msg.interval;
info.distanceTravelled = msg.distance_travelled;
info.memoryUsage = msg.memory_usage;
info.gravityRollError = msg.gravity_roll_error;
info.gravityPitchError = msg.gravity_pitch_error;
info.type = msg.type;
info.reg.matchesIDs = msg.word_matches;
info.reg.inliersIDs = msg.word_inliers;
if(!ignoreData)
{
UASSERT(msg.local_bundle_models.size() == msg.local_bundle_ids.size());
UASSERT(msg.local_bundle_models.size() == msg.local_bundle_poses.size());
for(size_t i=0; i<msg.local_bundle_ids.size(); ++i)
{
std::vector<rtabmap::CameraModel> models;
for(size_t j=0; j<msg.local_bundle_models[i].models.size(); ++j)
{
models.push_back(cameraModelFromROS(msg.local_bundle_models[i].models[j].camera_info, transformFromGeometryMsg(msg.local_bundle_models[i].models[j].local_transform)));
}
info.localBundleModels.insert(std::make_pair(msg.local_bundle_ids[i], models));
info.localBundlePoses.insert(std::make_pair(msg.local_bundle_ids[i], transformFromPoseMsg(msg.local_bundle_poses[i])));
}
UASSERT(msg.words_keys.size() == msg.words_values.size());
for(unsigned int i=0; i<msg.words_keys.size(); ++i)
{
info.words.insert(std::make_pair(msg.words_keys[i], keypointFromROS(msg.words_values[i])));
}
info.refCorners = points2fFromROS(msg.ref_corners);
info.newCorners = points2fFromROS(msg.new_corners);
info.cornerInliers = msg.corner_inliers;
info.transform = transformFromGeometryMsg(msg.transform);
info.transformFiltered = transformFromGeometryMsg(msg.transform_filtered);
info.transformGroundTruth = transformFromGeometryMsg(msg.transform_ground_truth);
info.guess = transformFromGeometryMsg(msg.guess);
UASSERT(msg.local_map_keys.size() == msg.local_map_values.size());
for(unsigned int i=0; i<msg.local_map_keys.size(); ++i)
{
info.localMap.insert(std::make_pair(msg.local_map_keys[i], point3fFromROS(msg.local_map_values[i])));
}
pcl::PCLPointCloud2 cloud;
pcl_conversions::toPCL(msg.local_scan_map, cloud);
info.localScanMap = rtabmap::util3d::laserScanFromPointCloud(cloud);
}
return info;
}
void odomInfoToROS(const rtabmap::OdometryInfo & info, rtabmap_msgs::msg::OdomInfo & msg, bool ignoreData)
{
msg.lost = info.lost;
msg.matches = info.reg.matches;
msg.inliers = info.reg.inliers;
msg.icp_inliers_ratio = info.reg.icpInliersRatio;
msg.icp_rotation = info.reg.icpRotation;
msg.icp_translation = info.reg.icpTranslation;
msg.icp_structural_complexity = info.reg.icpStructuralComplexity;
msg.icp_structural_distribution = info.reg.icpStructuralDistribution;
msg.icp_correspondences = info.reg.icpCorrespondences;
if(info.reg.covariance.type() == CV_64FC1 && info.reg.covariance.cols == 6 && info.reg.covariance.rows == 6)
{
memcpy(msg.covariance.data(), info.reg.covariance.data, 36*sizeof(double));
}
msg.features = info.features;
msg.local_map_size = info.localMapSize;
msg.local_scan_map_size = info.localScanMapSize;
msg.local_key_frames = info.localKeyFrames;
msg.local_bundle_outliers = info.localBundleOutliers;
msg.local_bundle_constraints = info.localBundleConstraints;
msg.local_bundle_time = info.localBundleTime;
msg.local_bundle_avg_inlier_distance = info.localBundleAvgInlierDistance;
msg.local_bundle_max_key_frames_for_inlier = info.localBundleMaxKeyFramesForInlier;
UASSERT(info.localBundleModels.size() == info.localBundlePoses.size());
for(std::map<int, std::vector<rtabmap::CameraModel> >::const_iterator iter=info.localBundleModels.begin();
iter!=info.localBundleModels.end();
++iter)
{
msg.local_bundle_ids.push_back(iter->first);
UASSERT(info.localBundlePoses.find(iter->first)!=info.localBundlePoses.end());
geometry_msgs::msg::Pose pose;
transformToPoseMsg(info.localBundlePoses.at(iter->first), pose);
msg.local_bundle_poses.push_back(pose);
rtabmap_msgs::msg::CameraModels models;
for(size_t i=0; i<iter->second.size(); ++i)
{
rtabmap_msgs::msg::CameraModel modelMsg;
cameraModelToROS(iter->second[i], modelMsg.camera_info);
transformToGeometryMsg(iter->second[i].localTransform(), modelMsg.local_transform);
models.models.push_back(modelMsg);
}
msg.local_bundle_models.push_back(models);
}
msg.key_frame_added = info.keyFrameAdded;
msg.time_estimation = info.timeEstimation;
msg.time_particle_filtering = info.timeParticleFiltering;
msg.stamp = info.stamp;
msg.interval = info.interval;
msg.distance_travelled = info.distanceTravelled;
msg.memory_usage = info.memoryUsage;
msg.gravity_roll_error = info.gravityRollError;
msg.gravity_pitch_error = info.gravityPitchError;
msg.type = info.type;
transformToGeometryMsg(info.transform, msg.transform);
transformToGeometryMsg(info.transformFiltered, msg.transform_filtered);
transformToGeometryMsg(info.transformGroundTruth, msg.transform_ground_truth);
transformToGeometryMsg(info.guess, msg.guess);
if(!ignoreData)
{
msg.words_keys = uKeys(info.words);
keypointsToROS(uValues(info.words), msg.words_values);
msg.word_matches = info.reg.matchesIDs;
msg.word_inliers = info.reg.inliersIDs;
points2fToROS(info.refCorners, msg.ref_corners);
points2fToROS(info.newCorners, msg.new_corners);
msg.corner_inliers = info.cornerInliers;
msg.local_map_keys = uKeys(info.localMap);
points3fToROS(uValues(info.localMap), msg.local_map_values);
pcl_conversions::moveFromPCL(*rtabmap::util3d::laserScanToPointCloud2(info.localScanMap, info.localScanMap.localTransform()), msg.local_scan_map);;
}
}
cv::Mat userDataFromROS(const rtabmap_msgs::msg::UserData & dataMsg)
{
cv::Mat data;
if(!dataMsg.data.empty())
{
if(dataMsg.cols > 0 && dataMsg.rows > 0)
{
data = cv::Mat(dataMsg.rows, dataMsg.cols, dataMsg.type, (void*)dataMsg.data.data()).clone();
}
else
{
if(dataMsg.cols != dataMsg.data.size() || dataMsg.rows != 1 || dataMsg.type != CV_8UC1)
{
UERROR("cols, rows and type fields of the user_data msg "
"are not correctly set (cols=%d, rows=%d, type=%d)! We assume that the data "
"is compressed (cols=%d, rows=1, type=%d(CV_8UC1)).",
dataMsg.cols, dataMsg.rows, dataMsg.type, (int)dataMsg.data.size(), CV_8UC1);
}
data = cv::Mat(1, dataMsg.data.size(), CV_8UC1, (void*)dataMsg.data.data()).clone();
}
}
return data;
}
void userDataToROS(const cv::Mat & data, rtabmap_msgs::msg::UserData & dataMsg, bool compress)
{
if(!data.empty())
{
if(compress)
{
dataMsg.data = rtabmap::compressData(data);
dataMsg.rows = 1;
dataMsg.cols = dataMsg.data.size();
dataMsg.type = CV_8UC1;
}
else
{
dataMsg.data.resize(data.step[0] * data.rows); // use step for non-contiguous matrices
memcpy(dataMsg.data.data(), data.data, dataMsg.data.size());
dataMsg.rows = data.rows;
dataMsg.cols = data.cols;
dataMsg.type = data.type();
}
}
}
rtabmap::IMU imuFromROS(const sensor_msgs::msg::Imu & msg, const rtabmap::Transform & localTransform)
{
return rtabmap::IMU(
cv::Vec4d(msg.orientation.x, msg.orientation.y, msg.orientation.z, msg.orientation.w),
cv::Mat(3,3,CV_64FC1,(void*)msg.orientation_covariance.data()).clone(),
cv::Vec3d(msg.angular_velocity.x, msg.angular_velocity.y, msg.angular_velocity.z),
cv::Mat(3,3,CV_64FC1,(void*)msg.angular_velocity_covariance.data()).clone(),
cv::Vec3d(msg.linear_acceleration.x, msg.linear_acceleration.y, msg.linear_acceleration.z),
cv::Mat(3,3,CV_64FC1,(void*)msg.linear_acceleration_covariance.data()).clone(),
localTransform);
}
void imuToROS(const rtabmap::IMU & imu, sensor_msgs::msg::Imu & msg)
{
msg.orientation.x = imu.orientation()[0];
msg.orientation.y = imu.orientation()[1];
msg.orientation.z = imu.orientation()[2];
msg.orientation.w = imu.orientation()[3];
if(!imu.orientationCovariance().empty())
{
memcpy((void*)msg.orientation_covariance.data(), imu.orientationCovariance().data, 9*sizeof(double));
}
msg.angular_velocity.x = imu.angularVelocity()[0];
msg.angular_velocity.y = imu.angularVelocity()[1];
msg.angular_velocity.z = imu.angularVelocity()[2];
if(!imu.angularVelocityCovariance().empty())
{
memcpy((void*)msg.angular_velocity_covariance.data(), imu.angularVelocityCovariance().data, 9*sizeof(double));
}
msg.linear_acceleration.x = imu.linearAcceleration()[0];
msg.linear_acceleration.y = imu.linearAcceleration()[1];
msg.linear_acceleration.z = imu.linearAcceleration()[2];
if(!imu.linearAccelerationCovariance().empty())
{
memcpy((void*)msg.linear_acceleration_covariance.data(), imu.linearAccelerationCovariance().data, 9*sizeof(double));
}
}
rtabmap::Landmarks landmarksFromROS(
const std::map<int, std::pair<geometry_msgs::msg::PoseWithCovarianceStamped, float> > & tags,
const std::string & frameId,
const std::string & odomFrameId,
const rclcpp::Time & odomStamp,
tf2_ros::Buffer & tfBuffer,
double waitForTransform,
double defaultLinVariance,
double defaultAngVariance)
{
//tag detections
rtabmap::Landmarks landmarks;
for(std::map<int, std::pair<geometry_msgs::msg::PoseWithCovarianceStamped, float> >::const_iterator iter=tags.begin(); iter!=tags.end(); ++iter)
{
if(iter->first <=0)
{
UERROR("Invalid landmark received! IDs should be > 0 (it is %d). Ignoring this landmark.", iter->first);
continue;
}
rtabmap::Transform baseToCamera = rtabmap_conversions::getTransform(
frameId,
iter->second.first.header.frame_id,
iter->second.first.header.stamp,
tfBuffer,
waitForTransform);
if(baseToCamera.isNull())
{
UERROR("Cannot transform tag pose from \"%s\" frame to \"%s\" frame!",
iter->second.first.header.frame_id.c_str(), frameId.c_str());
continue;
}
rtabmap::Transform baseToTag = baseToCamera * transformFromPoseMsg(iter->second.first.pose.pose);
if(!baseToTag.isNull())
{
// Correction of the global pose accounting the odometry movement since we received it
rtabmap::Transform correction = rtabmap_conversions::getMovingTransform(
frameId,
odomFrameId,
odomStamp,
iter->second.first.header.stamp,
tfBuffer,
waitForTransform);
if(!correction.isNull())
{
baseToTag = correction * baseToTag;
}
else
{
UWARN("Could not adjust tag pose accordingly to latest odometry pose. "
"If odometry is small since it received the tag pose and "
"covariance is large, this should not be a problem.");
}
cv::Mat covariance = cv::Mat(6,6, CV_64FC1, (void*)iter->second.first.pose.covariance.data()).clone();
if(covariance.empty() || !uIsFinite(covariance.at<double>(0,0)) || covariance.at<double>(0,0)<=0.0f)
{
covariance = cv::Mat::eye(6,6,CV_64FC1);
covariance(cv::Range(0,3), cv::Range(0,3)) *= defaultLinVariance;
covariance(cv::Range(3,6), cv::Range(3,6)) *= defaultAngVariance;
}
landmarks.insert(std::make_pair(iter->first, rtabmap::Landmark(iter->first, iter->second.second, baseToTag, covariance)));
}
}
return landmarks;
}
rtabmap::Transform getTransform(
const std::string & fromFrameId,
const std::string & toFrameId,
const rclcpp::Time & stamp,
tf2_ros::Buffer & tfBuffer,
double waitForTransform)
{
// TF ready?
rtabmap::Transform transform;
try
{
geometry_msgs::msg::TransformStamped tmp;
tmp = tfBuffer.lookupTransform(fromFrameId, toFrameId, tf2_ros::fromMsg(stamp), tf2::durationFromSec(waitForTransform));
transform = rtabmap_conversions::transformFromGeometryMsg(tmp.transform);
}
catch(tf2::TransformException & ex)
{
UWARN("(getting transform \"%s\" -> \"%s\") %s (wait_for_transform=%f)", fromFrameId.c_str(), toFrameId.c_str(), ex.what(), waitForTransform);
}
return transform;
}
// get moving transform accordingly to a fixed frame. For example get
// transform between moving /base_link between two stamps accordingly to /odom frame.
rtabmap::Transform getMovingTransform(
const std::string & movingFrame,
const std::string & fixedFrame,
const rclcpp::Time & stampFrom,
const rclcpp::Time & stampTo,
tf2_ros::Buffer & tfBuffer,
double waitForTransform)
{
// TF ready?
rtabmap::Transform transform;
try
{
geometry_msgs::msg::TransformStamped tmp;
tmp = tfBuffer.lookupTransform(movingFrame, tf2_ros::fromMsg(stampFrom), movingFrame, tf2_ros::fromMsg(stampTo), fixedFrame, tf2::durationFromSec(waitForTransform));
transform = rtabmap_conversions::transformFromGeometryMsg(tmp.transform);
}
catch(tf2::TransformException & ex)
{
UWARN("(getting transform movement of %s according to fixed %s) %s", movingFrame.c_str(), fixedFrame.c_str(), ex.what());
}
return transform;
}
bool convertRGBDMsgs(
const std::vector<cv_bridge::CvImageConstPtr> & imageMsgs,
const std::vector<cv_bridge::CvImageConstPtr> & depthMsgs,
const std::vector<sensor_msgs::msg::CameraInfo> & cameraInfoMsgs,
const std::vector<sensor_msgs::msg::CameraInfo> & depthCameraInfoMsgs,
const std::string & frameId,
const std::string & odomFrameId,
const rclcpp::Time & odomStamp,
cv::Mat & rgb,
cv::Mat & depth,
std::vector<rtabmap::CameraModel> & cameraModels,
std::vector<rtabmap::StereoCameraModel> & stereoCameraModels,
tf2_ros::Buffer & tfBuffer,
double waitForTransform,
bool alreadRectifiedImages,
const std::vector<std::vector<rtabmap_msgs::msg::KeyPoint> > & localKeyPointsMsgs,
const std::vector<std::vector<rtabmap_msgs::msg::Point3f> > & localPoints3dMsgs,
const std::vector<cv::Mat> & localDescriptorsMsgs,
std::vector<cv::KeyPoint> * localKeyPoints,
std::vector<cv::Point3f> * localPoints3d,
cv::Mat * localDescriptors)
{
UASSERT(!cameraInfoMsgs.empty() &&
(cameraInfoMsgs.size() == imageMsgs.size() || imageMsgs.empty()) &&
(cameraInfoMsgs.size() == depthMsgs.size() || depthMsgs.empty()) &&
(cameraInfoMsgs.size() == depthCameraInfoMsgs.size() || depthCameraInfoMsgs.empty()));
// An RGBDImage of a camera without depth (e.g., from rgb_sync) has an empty depth
// slot, which reaches here as empty depth images: convert the frame as color only,
// rather than as a stereo pair missing its right image.
if(!depthMsgs.empty() &&
std::all_of(depthMsgs.begin(), depthMsgs.end(),
[](const cv_bridge::CvImageConstPtr & msg) { return msg.get() == 0 || msg->image.empty(); }))
{
return convertRGBDMsgs(
imageMsgs,
std::vector<cv_bridge::CvImageConstPtr>(),
cameraInfoMsgs,
std::vector<sensor_msgs::msg::CameraInfo>(),
frameId,
odomFrameId,
odomStamp,
rgb,
depth,
cameraModels,
stereoCameraModels,
tfBuffer,
waitForTransform,
alreadRectifiedImages,
localKeyPointsMsgs,
localPoints3dMsgs,
localDescriptorsMsgs,
localKeyPoints,
localPoints3d,
localDescriptors);
}
int imageWidth = imageMsgs.size()?imageMsgs[0]->image.cols:cameraInfoMsgs[0].width;
int imageHeight = imageMsgs.size()?imageMsgs[0]->image.rows:cameraInfoMsgs[0].height;
int depthWidth = depthMsgs.size()?depthMsgs[0]->image.cols:0;
int depthHeight = depthMsgs.size()?depthMsgs[0]->image.rows:0;
// Without a decoded depth/right image (e.g., left compressed, see
// CommonDataSubscriber::imagesDecodedOnDemand()), the camera infos tell: a stereo pair
// has its baseline in P(0,3) of one of them.
bool isDepth = depthMsgs.empty() ?
!(depthCameraInfoMsgs.size() == cameraInfoMsgs.size() &&
(cameraInfoMsgs[0].p[3] != 0.0 || depthCameraInfoMsgs[0].p[3] != 0.0)) :
(depthMsgs[0].get() != 0 && (
depthMsgs[0]->encoding.compare(sensor_msgs::image_encodings::TYPE_16UC1) == 0 ||
depthMsgs[0]->encoding.compare(sensor_msgs::image_encodings::TYPE_32FC1) == 0 ||
depthMsgs[0]->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0));
// Note that right image can be also MONO16, check the camera info if Tx is set, if so assume it is stereo instead
if(isDepth &&
!depthMsgs.empty() &&
depthMsgs[0]->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0 &&
cameraInfoMsgs.size() == depthCameraInfoMsgs.size())
{
isDepth = cameraInfoMsgs[0].p[3] == 0.0 && depthCameraInfoMsgs[0].p[3] == 0.0;
static bool warned = false;
if(!warned && isDepth)
{
UWARN("Input depth/left image has encoding \"mono16\" and "
"camera info P[3] is null for both cameras, thus image is "
"considered a depth image. If the depth image is in "
"fact the right image, please convert the right image to "
"\"mono8\". This warning is shown only once.");
warned = true;
}
}
if(isDepth && !depthMsgs.empty())
{
UASSERT_MSG(
imageWidth/depthWidth == imageHeight/depthHeight,
uFormat("rgb=%dx%d depth=%dx%d", imageWidth, imageHeight, depthWidth, depthHeight).c_str());
}
int cameraCount = cameraInfoMsgs.size();
for(unsigned int i=0; i<cameraInfoMsgs.size(); ++i)
{
if(!imageMsgs.empty())
{
if(!(imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO8) ==0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO16) ==0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BGRA8) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::RGBA8) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BAYER_GRBG8) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BAYER_RGGB8) == 0))
{
UERROR("Input rgb/left type must be image=mono8,mono16,rgb8,bgr8,bgra8,rgba8. Current rgb/left=%s",
imageMsgs[i]->encoding.c_str());
return false;
}
UASSERT_MSG(imageMsgs[i]->image.cols == imageWidth && imageMsgs[i]->image.rows == imageHeight,
uFormat("imageWidth=%d vs %d imageHeight=%d vs %d",
imageWidth,
imageMsgs[i]->image.cols,
imageHeight,
imageMsgs[i]->image.rows).c_str());
}
if(!depthMsgs.empty())
{
if(isDepth &&
!(depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::TYPE_16UC1) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::TYPE_32FC1) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0))
{
UERROR("Input depth type must be image_depth=32FC1,16UC1,mono16. Current depth=%s",
depthMsgs[i]->encoding.c_str());
return false;
}
else if(!isDepth &&
!(depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BGRA8) == 0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::RGBA8) == 0))
{
UERROR("Input right type must be image=mono8,mono16,rgb8,bgr8,bgra8,rgba8. Current right=%s",
depthMsgs[i]->encoding.c_str());
return false;
}
}
rclcpp::Time stamp;
if(isDepth && !depthMsgs.empty())
{
UASSERT_MSG(depthMsgs[i]->image.cols == depthWidth && depthMsgs[i]->image.rows == depthHeight,
uFormat("depthWidth=%d vs %d imageHeight=%d vs %d",
depthWidth,
depthMsgs[i]->image.cols,
depthHeight,
depthMsgs[i]->image.rows).c_str());
stamp = depthMsgs[i]->header.stamp;
}
else if(!imageMsgs.empty())
{
stamp = imageMsgs[i]->header.stamp;
}
else
{
stamp = cameraInfoMsgs[i].header.stamp;
}
// use depth's stamp so that geometry is sync to odom, use rgb frame as we assume depth is registered (normally depth msg should have same frame than rgb)
rtabmap::Transform localTransform = rtabmap_conversions::getTransform(frameId, !imageMsgs.empty()?imageMsgs[i]->header.frame_id:cameraInfoMsgs[i].header.frame_id, stamp, tfBuffer, waitForTransform);
if(localTransform.isNull())
{
UERROR("TF of received image for camera %d at time %fs is not set!", i, stamp.seconds());
return false;
}
// sync with odometry stamp
if(!odomFrameId.empty() && odomStamp != stamp)
{
rtabmap::Transform sensorT = getMovingTransform(
frameId,
odomFrameId,
odomStamp,
stamp,
tfBuffer,
waitForTransform);
if(sensorT.isNull())
{
UWARN("Could not get odometry value for image stamp (%fs). Latest odometry "
"stamp is %fs. The image pose will not be synchronized with odometry.", timestampFromROS(stamp), timestampFromROS(odomStamp));
}
else
{
//UWARN("RGBD correction = %s (time diff=%fs)", sensorT.prettyPrint().c_str(), fabs(stamp.toSec()-odomStamp.toSec()));
localTransform = sensorT * localTransform;
}
}
if(!imageMsgs.empty())
{
cv_bridge::CvImageConstPtr ptrImage = imageMsgs[i];
try {
if(imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1)==0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0 ||
imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0)
{
// do nothing
}
else if(imageMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0)
{
ptrImage = cv_bridge::cvtColor(imageMsgs[i], "mono8");
}
else
{
ptrImage = cv_bridge::cvtColor(imageMsgs[i], "bgr8");
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting image (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
// initialize
if(rgb.empty())
{
rgb = cv::Mat(imageHeight, imageWidth*cameraCount, ptrImage->image.type());
}
if(ptrImage->image.type() == rgb.type())
{
ptrImage->image.copyTo(cv::Mat(rgb, cv::Rect(i*imageWidth, 0, imageWidth, imageHeight)));
}
else
{
UERROR("Some RGB/left images are not the same type!");
return false;
}
}
if(!depthMsgs.empty())
{
if(isDepth)
{
cv_bridge::CvImageConstPtr ptrDepth = depthMsgs[i];
cv::Mat subDepth = ptrDepth->image;
if(depth.empty())
{
depth = cv::Mat(depthHeight, depthWidth*cameraCount, subDepth.type());
}
if(subDepth.type() == depth.type())
{
subDepth.copyTo(cv::Mat(depth, cv::Rect(i*depthWidth, 0, depthWidth, depthHeight)));
}
else
{
UERROR("Some Depth images are not the same type!");
return false;
}
}
else
{
cv_bridge::CvImageConstPtr ptrImage = depthMsgs[i];
if( depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1)==0 ||
depthMsgs[i]->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0)
{
// do nothing
}
else
{
try{
ptrImage = cv_bridge::cvtColor(depthMsgs[i], "mono8");
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting image (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
}
// initialize
if(depth.empty())
{
depth = cv::Mat(depthHeight, depthWidth*cameraCount, ptrImage->image.type());
}
if(ptrImage->image.type() == depth.type())
{
ptrImage->image.copyTo(cv::Mat(depth, cv::Rect(i*depthWidth, 0, depthWidth, depthHeight)));
}
else
{
UERROR("Some right images are not the same type!");
return false;
}
}
}
if(isDepth)
{
cameraModels.push_back(rtabmap_conversions::cameraModelFromROS(cameraInfoMsgs[i], localTransform));
}
else //stereo
{
UASSERT(cameraInfoMsgs.size() == depthCameraInfoMsgs.size());
rtabmap::Transform stereoTransform;
if(!alreadRectifiedImages)
{
if(depthCameraInfoMsgs[i].header.frame_id.empty() || cameraInfoMsgs[i].header.frame_id.empty())
{
if(depthCameraInfoMsgs[i].p[3] == 0.0 && cameraInfoMsgs[i].p[3] == 0)
{
UERROR("Parameter %s is false but the frame_id in one of the camera_info "
"topic is empty, so TF between the cameras cannot be computed!",
rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str());
return false;
}
else
{
static bool warned = false;
if(!warned)
{
UWARN("Parameter %s is false but the frame_id in one of the "
"camera_info topic is empty, so TF between the cameras cannot be "
"computed! However, the baseline can be computed from the calibration, "
"we will use this one instead of TF. This message is only printed once...",
rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str());
warned = true;
}
}
}
else
{
stereoTransform = getTransform(
depthCameraInfoMsgs[i].header.frame_id,
cameraInfoMsgs[i].header.frame_id,
cameraInfoMsgs[i].header.stamp,
tfBuffer,
waitForTransform);
if(stereoTransform.isNull())
{
UERROR("Parameter %s is false but we cannot get TF between the two cameras!", rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str());
return false;
}
else if(stereoTransform.isIdentity())
{
UERROR("Parameter %s is false but we cannot get a valid TF between the two cameras! "
"Identity transform returned between left and right cameras. Verify that if TF between "
"the cameras is valid: \"rosrun tf tf_echo %s %s\".",
rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str(),
depthCameraInfoMsgs[i].header.frame_id.c_str(),
cameraInfoMsgs[i].header.frame_id.c_str());
return false;
}
}
}
rtabmap::StereoCameraModel stereoModel = rtabmap_conversions::stereoCameraModelFromROS(cameraInfoMsgs[i], depthCameraInfoMsgs[i], localTransform, stereoTransform);
if(stereoModel.baseline() > 10.0)
{
static bool shown = false;
if(!shown)
{
UWARN("Detected baseline (%f m) is quite large! Is your "
"right camera_info P(0,3) correctly set? Note that "
"baseline=-P(0,3)/P(0,0). You may need to calibrate your camera. "
"This warning is printed only once.",
stereoModel.baseline());
shown = true;
}
}
else if(stereoModel.baseline() == 0 && alreadRectifiedImages)
{
rtabmap::Transform stereoTransform;
if( !cameraInfoMsgs[i].header.frame_id.empty() &&
!depthCameraInfoMsgs[i].header.frame_id.empty())
{
stereoTransform = getTransform(
cameraInfoMsgs[i].header.frame_id,
depthCameraInfoMsgs[i].header.frame_id,
cameraInfoMsgs[i].header.stamp,
tfBuffer,
waitForTransform);
}
if(stereoTransform.isNull() || stereoTransform.x()<=0)
{
if(cameraInfoMsgs[i].header.frame_id.empty() || depthCameraInfoMsgs[i].header.frame_id.empty())
{
UWARN("We cannot estimated the baseline of the rectified images with tf! (camera_info topics have empty frame_id)");
}
else
{
UWARN("We cannot estimated the baseline of the rectified images with tf! (%s->%s = %s)",
depthCameraInfoMsgs[i].header.frame_id.c_str(), cameraInfoMsgs[i].header.frame_id.c_str(), stereoTransform.prettyPrint().c_str());
}
}
else
{
static bool warned = false;
if(!warned)
{
UWARN("Right camera info doesn't have Tx set but we are assuming that stereo images are already rectified (see %s parameter). While not "
"recommended, we used TF to get the baseline (%s->%s = %fm) for convenience (e.g., D400 ir stereo issue). It is preferred to feed "
"a valid right camera info if stereo images are already rectified. This message is only printed once...",
rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str(),
depthCameraInfoMsgs[i].header.frame_id.c_str(), cameraInfoMsgs[i].header.frame_id.c_str(), stereoTransform.x());
warned = true;
}
stereoModel = rtabmap::StereoCameraModel(
stereoModel.left().fx(),
stereoModel.left().fy(),
stereoModel.left().cx(),
stereoModel.left().cy(),
stereoTransform.x(),
stereoModel.localTransform(),
stereoModel.left().imageSize());
}
}
stereoCameraModels.push_back(stereoModel);
}
if(localKeyPoints && localKeyPointsMsgs.size() == cameraInfoMsgs.size())
{
rtabmap_conversions::keypointsFromROS(localKeyPointsMsgs[i], *localKeyPoints, imageWidth*i);
}
if(localPoints3d && localPoints3dMsgs.size() == cameraInfoMsgs.size())
{
// Points should be in base frame
rtabmap_conversions::points3fFromROS(localPoints3dMsgs[i], *localPoints3d, localTransform);
}
if(localDescriptors && localDescriptorsMsgs.size() == cameraInfoMsgs.size())
{
localDescriptors->push_back(localDescriptorsMsgs[i]);
}
}
return true;
}
bool convertStereoMsg(
const cv_bridge::CvImageConstPtr& leftImageMsg,
const cv_bridge::CvImageConstPtr& rightImageMsg,
const sensor_msgs::msg::CameraInfo& leftCamInfoMsg,
const sensor_msgs::msg::CameraInfo& rightCamInfoMsg,
const std::string & frameId,
const std::string & odomFrameId,
const rclcpp::Time & odomStamp,
cv::Mat & left,
cv::Mat & right,
rtabmap::StereoCameraModel & stereoModel,
tf2_ros::Buffer & tfBuffer,
double waitForTransform,
bool alreadyRectified)
{
UASSERT(leftImageMsg.get() && rightImageMsg.get());
if(!(leftImageMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::BGRA8) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::RGBA8) == 0) ||
!(rightImageMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::BGR8) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::RGB8) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::BGRA8) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::RGBA8) == 0))
{
UERROR("Input type must be image=mono8,mono16,rgb8,bgr8,bgra8,rgba8");
UERROR("Input type must be image=mono8,mono16,rgb8,bgr8,bgra8,rgba8 Current left=%s and right=%s",
leftImageMsg->encoding.c_str(),
rightImageMsg->encoding.c_str());
return false;
}
try{
if( leftImageMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
leftImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0)
{
left = leftImageMsg->image.clone();
}
else if(leftImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO16) == 0)
{
left = cv_bridge::cvtColor(leftImageMsg, "mono8")->image;
}
else
{
left = cv_bridge::cvtColor(leftImageMsg, "bgr8")->image;
}
if( rightImageMsg->encoding.compare(sensor_msgs::image_encodings::TYPE_8UC1) == 0 ||
rightImageMsg->encoding.compare(sensor_msgs::image_encodings::MONO8) == 0)
{
right = rightImageMsg->image.clone();
}
else
{
right = cv_bridge::cvtColor(rightImageMsg, "mono8")->image;
}
}
catch(cv::Exception& e) {
UFATAL("Fatal error while converting images (do you have multiple opencv versions? if so, make sure cv_bridge is loading the right opencv libraries on runtime): %s", e.what());
}
rtabmap::Transform localTransform = getTransform(frameId, leftImageMsg->header.frame_id, leftImageMsg->header.stamp, tfBuffer, waitForTransform);
if(localTransform.isNull())
{
return false;
}
// sync with odometry stamp
if(!odomFrameId.empty() && odomStamp != leftImageMsg->header.stamp)
{
rtabmap::Transform sensorT = getMovingTransform(
frameId,
odomFrameId,
odomStamp,
leftImageMsg->header.stamp,
tfBuffer,
waitForTransform);
if(sensorT.isNull())
{
UWARN("Could not get odometry value for stereo msg stamp (%fs). Latest odometry "
"stamp is %fs. The stereo image pose will not be synchronized with odometry.", timestampFromROS(leftImageMsg->header.stamp), odomStamp.seconds());
}
else
{
localTransform = sensorT * localTransform;
}
}
rtabmap::Transform stereoTransform;
if(!alreadyRectified)
{
stereoTransform = getTransform(
rightCamInfoMsg.header.frame_id,
leftCamInfoMsg.header.frame_id,
leftCamInfoMsg.header.stamp,
tfBuffer,
waitForTransform);
if(stereoTransform.isNull())
{
UERROR("Parameter %s is false but we cannot get TF between the two cameras!", rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str());
return false;
}
}
stereoModel = rtabmap_conversions::stereoCameraModelFromROS(leftCamInfoMsg, rightCamInfoMsg, localTransform, stereoTransform);
if(stereoModel.baseline() > 10.0)
{
static bool shown = false;
if(!shown)
{
UWARN("Detected baseline (%f m) is quite large! Is your "
"right camera_info P(0,3) correctly set? Note that "
"baseline=-P(0,3)/P(0,0). You may need to calibrate your camera. "
"This warning is printed only once.",
stereoModel.baseline());
shown = true;
}
}
else if(stereoModel.baseline() == 0 && alreadyRectified)
{
rtabmap::Transform stereoTransform = getTransform(
leftCamInfoMsg.header.frame_id,
rightCamInfoMsg.header.frame_id,
leftCamInfoMsg.header.stamp,
tfBuffer,
waitForTransform);
if(stereoTransform.isNull() || stereoTransform.x()<=0)
{
UWARN("We cannot estimated the baseline of the rectified images with tf! (%s->%s = %s)",
rightCamInfoMsg.header.frame_id.c_str(), leftCamInfoMsg.header.frame_id.c_str(), stereoTransform.prettyPrint().c_str());
}
else
{
static bool warned = false;
if(!warned)
{
UWARN("Right camera info doesn't have Tx set but we are assuming that stereo images are already rectified (see %s parameter). While not "
"recommended, we used TF to get the baseline (%s->%s = %fm) for convenience (e.g., D400 ir stereo issue). It is preferred to feed "
"a valid right camera info if stereo images are already rectified. This message is only printed once...",
rtabmap::Parameters::kRtabmapImagesAlreadyRectified().c_str(),
rightCamInfoMsg.header.frame_id.c_str(), leftCamInfoMsg.header.frame_id.c_str(), stereoTransform.x());
warned = true;
}
stereoModel = rtabmap::StereoCameraModel(
stereoModel.left().fx(),
stereoModel.left().fy(),
stereoModel.left().cx(),
stereoModel.left().cy(),
stereoTransform.x(),
stereoModel.localTransform(),
stereoModel.left().imageSize());
}
}
return true;
}
bool convertScanMsg(
const sensor_msgs::msg::LaserScan& scan2dMsg,
const std::string & frameId,
const std::string & odomFrameId,
const rclcpp::Time & odomStamp,
rtabmap::LaserScan & scan,
tf2_ros::Buffer & tfBuffer,
double waitForTransform,
bool outputInFrameId)
{
// scan message validation check
if(scan2dMsg.angle_increment == 0.0f) {
UERROR("convertScanMsg: angle_increment should not be 0!");
return false;
}
if(scan2dMsg.range_min > scan2dMsg.range_max) {
UERROR("convertScanMsg: range_min (%f) should be smaller than range_max (%f)!", scan2dMsg.range_min, scan2dMsg.range_max);
return false;
}
if(scan2dMsg.angle_increment > 0 && scan2dMsg.angle_max < scan2dMsg.angle_min) {
UERROR("convertScanMsg: Angle increment (%f) should be negative if angle_min(%f) > angle_max(%f)!", scan2dMsg.angle_increment, scan2dMsg.angle_min, scan2dMsg.angle_max);
return false;
}
else if (scan2dMsg.angle_increment < 0 && scan2dMsg.angle_max > scan2dMsg.angle_min) {
UERROR("convertScanMsg: Angle increment (%f) should positive if angle_min(%f) < angle_max(%f)!", scan2dMsg.angle_increment, scan2dMsg.angle_min, scan2dMsg.angle_max);
return false;
}
// make sure the frame of the laser is updated during the whole scan time
const rclcpp::Time scanStart(scan2dMsg.header.stamp);
const rclcpp::Time scanEnd = scanStart + rclcpp::Duration::from_seconds((scan2dMsg.ranges.empty()?0:scan2dMsg.ranges.size()-1)*scan2dMsg.time_increment);
std::string fixedFrameId = odomFrameId.empty()?frameId:odomFrameId;
rtabmap::Transform tmpT;
if(fixedFrameId == frameId || tfBuffer._frameExists(fixedFrameId)) // don't wait for a frame never published
{
tmpT = getMovingTransform(
scan2dMsg.header.frame_id,
fixedFrameId,
scanStart,
scanEnd,
tfBuffer,
waitForTransform);
}
if(tmpT.isNull() && fixedFrameId != frameId)
{
// Odometry not in TF: use the scan as it is rather than dropping it.
static bool warned = false;
if(!warned)
{
UWARN("Could not get laser frame \"%s\" relative to odometry frame \"%s\" over the scan "
"(%fs to %fs). Laser scans are used without deskewing nor synchronization with "
"odometry. Publish odometry on TF to have them deskewed. This message is only shown once.",
scan2dMsg.header.frame_id.c_str(), odomFrameId.c_str(), scanStart.seconds(), scanEnd.seconds());
warned = true;
}
fixedFrameId = frameId;
tmpT = getMovingTransform(
scan2dMsg.header.frame_id,
fixedFrameId,
scanStart,
scanEnd,
tfBuffer,
waitForTransform);
}
if(tmpT.isNull())
{
return false;
}
rtabmap::Transform scanLocalTransform = getTransform(
frameId,
scan2dMsg.header.frame_id,
scan2dMsg.header.stamp,
tfBuffer,
waitForTransform);
if(scanLocalTransform.isNull())
{
return false;
}
//transform in frameId_ frame
sensor_msgs::msg::PointCloud2 scanOut;
laser_geometry::LaserProjection projection;
projection.transformLaserScanToPointCloud(fixedFrameId, scan2dMsg, scanOut, tfBuffer);
//transform back in laser frame
rtabmap::Transform laserToOdom = getTransform(
scan2dMsg.header.frame_id,
fixedFrameId,
scan2dMsg.header.stamp,
tfBuffer,
waitForTransform);
if(laserToOdom.isNull())
{
return false;
}
// sync with odometry stamp
if(fixedFrameId != frameId && odomStamp != scan2dMsg.header.stamp)
{
rtabmap::Transform sensorT = getMovingTransform(
frameId,
odomFrameId,
odomStamp,
scan2dMsg.header.stamp,
tfBuffer,
waitForTransform);
if(sensorT.isNull())
{
UWARN("Could not get odometry value for laser scan stamp (%fs). Latest odometry "
"stamp is %fs. The laser scan pose will not be synchronized with odometry.", timestampFromROS(scan2dMsg.header.stamp), odomStamp.seconds());
}
else
{
//UWARN("scan correction = %s (time diff=%fs)", sensorT.prettyPrint().c_str(), fabs(scan2dMsg.header.stamp.toSec()-odomStamp.toSec()));
scanLocalTransform = sensorT * scanLocalTransform;
}
}
if(outputInFrameId)
{
laserToOdom *= scanLocalTransform;
}
bool hasIntensity = false;
for(unsigned int i=0; i<scanOut.fields.size(); ++i)
{
if(scanOut.fields[i].name.compare("intensity") == 0)
{
if(scanOut.fields[i].datatype == sensor_msgs::msg::PointField::FLOAT32)
{
hasIntensity = true;
}
else
{
static bool warningShown = false;
if(!warningShown)
{
UWARN("The input scan cloud has an \"intensity\" field "
"but the datatype (%d) is not supported. Intensity will be ignored. "
"This message is only shown once.", scanOut.fields[i].datatype);
warningShown = true;
}
}
}
}
rtabmap::LaserScan::Format format;
cv::Mat data;
if(hasIntensity)
{
pcl::PointCloud<pcl::PointXYZI>::Ptr pclScan(new pcl::PointCloud<pcl::PointXYZI>);
rtabmap_conversions::fromPointCloud2Msg(scanOut, *pclScan);
pclScan->is_dense = true;
data = rtabmap::util3d::laserScan2dFromPointCloud(*pclScan, laserToOdom).data(); // put back in laser frame
format = rtabmap::LaserScan::kXYI;
}
else
{
pcl::PointCloud<pcl::PointXYZ>::Ptr pclScan(new pcl::PointCloud<pcl::PointXYZ>);
rtabmap_conversions::fromPointCloud2Msg(scanOut, *pclScan);
pclScan->is_dense = true;
data = rtabmap::util3d::laserScan2dFromPointCloud(*pclScan, laserToOdom).data(); // put back in laser frame
format = rtabmap::LaserScan::kXY;
}
rtabmap::Transform zAxis(0,0,1,0,0,0);
if((scanLocalTransform.rotation()*zAxis).z() < 0)
{
cv::Mat flipScan;
cv::flip(data, flipScan, 1);
data = flipScan;
}
scan = rtabmap::LaserScan(
data,
format,
scan2dMsg.range_min,
scan2dMsg.range_max,
scan2dMsg.angle_min,
scan2dMsg.angle_max,
scan2dMsg.angle_increment,
outputInFrameId?rtabmap::Transform::getIdentity():scanLocalTransform);
return true;
}
bool convertScan3dMsg(
const sensor_msgs::msg::PointCloud2 & scan3dMsg,
const std::string & frameId,
const std::string & odomFrameId,
const rclcpp::Time & odomStamp,
rtabmap::LaserScan & scan,
tf2_ros::Buffer & tfBuffer,
double waitForTransform,
int maxPoints,
float maxRange,
bool is2D)
{
UASSERT_MSG(scan3dMsg.data.size() == scan3dMsg.row_step*scan3dMsg.height,
uFormat("data=%d row_step=%d height=%d", scan3dMsg.data.size(), scan3dMsg.row_step, scan3dMsg.height).c_str());
rtabmap::Transform scanLocalTransform = getTransform(frameId, scan3dMsg.header.frame_id, scan3dMsg.header.stamp, tfBuffer, waitForTransform);
if(scanLocalTransform.isNull())
{
UERROR("TF of received scan cloud at time %fs is not set, aborting rtabmap update.", timestampFromROS(scan3dMsg.header.stamp));
return false;
}
// sync with odometry stamp
if(!odomFrameId.empty() && odomStamp != scan3dMsg.header.stamp)
{
rtabmap::Transform sensorT = getMovingTransform(
frameId,
odomFrameId,
odomStamp,
scan3dMsg.header.stamp,
tfBuffer,
waitForTransform);
if(sensorT.isNull())
{
UWARN("Could not get odometry value for laser scan stamp (%fs). Latest odometry "
"stamp is %fs. The 3d laser scan pose will not be synchronized with odometry.", timestampFromROS(scan3dMsg.header.stamp), odomStamp.seconds());
}
else
{
scanLocalTransform = sensorT * scanLocalTransform;
}
}
scan = rtabmap::util3d::laserScanFromPointCloud(scan3dMsg, true, is2D);
scan = rtabmap::LaserScan(scan, maxPoints, maxRange, scanLocalTransform);
return true;
}
bool deskew_impl(
const sensor_msgs::msg::PointCloud2 & input,
sensor_msgs::msg::PointCloud2 & output,
const std::string & fixedFrameId,
tf2_ros::Buffer * tfBuffer,
double waitForTransform,
bool slerp,
const rtabmap::Transform & velocity)
{
if(tfBuffer != 0)
{
if(input.header.frame_id.empty())
{
UERROR("Input cloud has empty frame_id!");
return false;
}
if(fixedFrameId.empty())
{
UERROR("fixedFrameId parameter should be set!");
return false;
}
}
else
{
if(!slerp)
{
UERROR("slerp should be true when constant velocity model is used!");
return false;
}
if(velocity.isNull())
{
UERROR("velocity should be valid when constant velocity model is used!");
return false;
}
}
int offsetTime = -1;
int offsetX = -1;
int offsetY = -1;
int offsetZ = -1;
int timeDatatype = 6;
for(size_t i=0; i<input.fields.size(); ++i)
{
if(input.fields[i].name.compare("t") == 0 ||
input.fields[i].name.compare("time") == 0 ||
input.fields[i].name.compare("stamps") == 0 ||
input.fields[i].name.compare("timestamp") == 0)
{
if(offsetTime != -1)
{
UWARN("The input cloud should have only one of these fields: t, time, stamps or timestamp. Overriding with %s.", input.fields[i].name.c_str());
}
offsetTime = input.fields[i].offset;
timeDatatype = input.fields[i].datatype;
}
else if(input.fields[i].name.compare("x") == 0)
{
UASSERT(input.fields[i].datatype==7);
offsetX = input.fields[i].offset;
}
else if(input.fields[i].name.compare("y") == 0)
{
UASSERT(input.fields[i].datatype==7);
offsetY = input.fields[i].offset;
}
else if(input.fields[i].name.compare("z") == 0)
{
UASSERT(input.fields[i].datatype==7);
offsetZ = input.fields[i].offset;
}
}
if(offsetTime < 0)
{
UERROR("Input cloud doesn't have \"t\", \"time\", \"stamps\" or \"timestamp\" field!");
std::string fieldsReceived;
for(size_t i=0; i<input.fields.size(); ++i)
{
fieldsReceived += input.fields[i].name + " ";
}
UERROR("Input cloud has these fields: %s", fieldsReceived.c_str());
return false;
}
if(offsetX < 0)
{
UERROR("Input cloud doesn't have \"x\" field!");
return false;
}
if(offsetY < 0)
{
UERROR("Input cloud doesn't have \"y\" field!");
return false;
}
if(offsetZ < 0)
{
UERROR("Input cloud doesn't have \"z\" field!");
return false;
}
if(input.height == 0)
{
UERROR("Input cloud height is zero!");
return false;
}
if(input.width == 0)
{
UERROR("Input cloud width is zero!");
return false;
}
bool timeOnColumns = input.width > input.height;
// Get latest timestamp
rclcpp::Time firstStamp;
rclcpp::Time lastStamp;
if(timeDatatype == 6) // UINT32
{
unsigned int nsecFirst = *((const unsigned int*)(&input.data[0]+offsetTime));
unsigned int nsecLast = *((const unsigned int*)(&input.data[(input.width-1)*input.point_step + input.row_step*(input.height-1)]+offsetTime));
if(nsecFirst > nsecLast)
{
// scans are not ordered, we need to search min/max
static bool warned = false;
if(!warned) {
UWARN("Timestamp channel is not ordered, we will have to parse every scans to "
"determinate first and last time offsets. This will add slightly computation "
"time. This warning is only shown once.");
warned = true;
}
if(timeOnColumns)
{
for(size_t i=0; i<input.width; ++i)
{
unsigned int nsec = *((const unsigned int*)(&input.data[(i)*input.point_step]+offsetTime));
if(nsec < nsecFirst)
{
nsecFirst = nsec;
}
else if(nsec > nsecLast)
{
nsecLast = nsec;
}
}
}
else
{
for(size_t i=0; i<input.height; ++i)
{
unsigned int nsec = *((const unsigned int*)(&input.data[input.row_step*(i)]+offsetTime));
if(nsec < nsecFirst)
{
nsecFirst = nsec;
}
else if(nsec > nsecLast)
{
nsecLast = nsec;
}
}
}
}
firstStamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration(0, nsecFirst);
lastStamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration(0, nsecLast);
}
else if(timeDatatype == 7) // FLOAT32
{
float secFirst = *((const float*)(&input.data[0]+offsetTime));
float secLast = *((const float*)(&input.data[(input.width-1)*input.point_step + input.row_step*(input.height-1)]+offsetTime));
if(secFirst > secLast)
{
// scans are not ordered, we need to search min/max
static bool warned = false;
if(!warned) {
UWARN("Timestamp channel is not ordered, we will have to parse every scans to "
"determinate first and last time offsets. This will add slightly computation "
"time. This warning is only shown once.");
warned = true;
}
if(timeOnColumns)
{
for(size_t i=0; i<input.width; ++i)
{
float sec = *((const float*)(&input.data[(i)*input.point_step]+offsetTime));
if(sec < secFirst)
{
secFirst = sec;
}
else if(sec > secLast)
{
secLast = sec;
}
}
}
else
{
for(size_t i=0; i<input.height; ++i)
{
float sec = *((const float*)(&input.data[input.row_step*(i)]+offsetTime));
if(sec < secFirst)
{
secFirst = sec;
}
else if(sec > secLast)
{
secLast = sec;
}
}
}
}
firstStamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration::from_seconds(secFirst);
lastStamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration::from_seconds(secLast);
}
else if(timeDatatype == 8) // FLOAT64
{
double secFirst = *((const double*)(&input.data[0]+offsetTime));
double secLast = *((const double*)(&input.data[(input.width-1)*input.point_step + input.row_step*(input.height-1)]+offsetTime));
if(secFirst > secLast)
{
// scans are not ordered, we need to search min/max
static bool warned = false;
if(!warned) {
UWARN("Timestamp channel is not ordered, we will have to parse every scans to "
"determinate first and last time offsets. This will add slightly computation "
"time. This warning is only shown once.");
warned = true;
}
if(timeOnColumns)
{
for(size_t i=0; i<input.width; ++i)
{
double sec = *((const double*)(&input.data[(i)*input.point_step]+offsetTime));
if(sec < secFirst)
{
secFirst = sec;
}
else if(sec > secLast)
{
secLast = sec;
}
}
}
else
{
for(size_t i=0; i<input.height; ++i)
{
double sec = *((const double*)(&input.data[input.row_step*(i)]+offsetTime));
if(sec < secFirst)
{
secFirst = sec;
}
else if(sec > secLast)
{
secLast = sec;
}
}
}
}
if(secFirst > 1.e18)
{
// convert nanoseconds to seconds
secFirst /= 1.e9;
secLast /= 1.e9;
}
else if(secFirst > 1.e15)
{
// convert microseconds to seconds
secFirst /= 1.e6;
secLast /= 1.e6;
}
else if(secFirst > 1.e12)
{
// convert milliseconds to seconds
secFirst /= 1.e3;
secLast /= 1.e3;
}
firstStamp = timestampToROS(secFirst);
lastStamp = timestampToROS(secLast);
}
else
{
UERROR("Not supported time datatype %d!", timeDatatype);
return false;
}
if(!(timeDatatype >=6 && timeDatatype<=8))
{
UERROR("Only lidar timestamp channel data type 6, 7 or 8 is supported! (received %d)", timeDatatype);
return false;
}
if(lastStamp < firstStamp)
{
UERROR("Last stamp (%f) is smaller than first stamp (%f) (header=%f)!", timestampFromROS(lastStamp), timestampFromROS(firstStamp), timestampFromROS(input.header.stamp));
return false;
}
else if(lastStamp == firstStamp)
{
// There is no time spread across the scan, so there is nothing to correct. This
// happens when the driver doesn't fill the per-point time channel, and also when
// the cloud has already been deskewed: deskewing zeroes that channel to mark it.
// Pass the cloud through unchanged so that deskewing twice is a no-op rather than
// a failure that makes the caller drop the frame.
static bool warned = false;
if(!warned)
{
UWARN("First and last stamps in the scan are the same (%f) (header=%f), the "
"cloud is returned unchanged. Either the time channel is not filled by "
"the driver, or the cloud has already been deskewed. This warning is "
"only shown once.",
timestampFromROS(lastStamp), timestampFromROS(input.header.stamp));
warned = true;
}
output = input;
return true;
}
std::string errorMsg;
if(tfBuffer != 0 &&
waitForTransform>0.0 &&
!tfBuffer->canTransform(
input.header.frame_id,
firstStamp,
input.header.frame_id,
lastStamp,
fixedFrameId,
rclcpp::Duration::from_seconds(waitForTransform),
&errorMsg))
{
UERROR("Could not estimate motion of %s accordingly to fixed frame %s between stamps %f and %f! (%s)",
input.header.frame_id.c_str(),
fixedFrameId.c_str(),
timestampFromROS(firstStamp),
timestampFromROS(lastStamp),
errorMsg.c_str());
return false;
}
rtabmap::Transform firstPose;
rtabmap::Transform lastPose;
double scanTime = 0;
if(slerp)
{
if(tfBuffer != 0)
{
firstPose = rtabmap_conversions::getMovingTransform(
input.header.frame_id,
fixedFrameId,
input.header.stamp,
firstStamp,
*tfBuffer,
0);
lastPose = rtabmap_conversions::getMovingTransform(
input.header.frame_id,
fixedFrameId,
input.header.stamp,
lastStamp,
*tfBuffer,
0);
}
else
{
float vx,vy,vz, vroll,vpitch,vyaw;
velocity.getTranslationAndEulerAngles(vx,vy,vz, vroll,vpitch,vyaw);
// Integrate the velocity directly from the stamp of the msg, which is the
// frame the deskewed cloud is expressed in. Going through a third, earlier
// reference pose and composing it away would give the same answer for a pure
// translation, but not for a rotation: Transform() scales roll/pitch/yaw
// linearly instead of using the twist exponential, so the composition only
// cancels in the small-angle limit. Keeping dt bounded by the scan duration
// is where that approximation is at its best.
double dt1 = timestampFromROS(firstStamp) - timestampFromROS(input.header.stamp);
double dt3 = timestampFromROS(lastStamp) - timestampFromROS(input.header.stamp);
// First and last poses are relative to stamp of the msg
firstPose = rtabmap::Transform(vx*dt1, vy*dt1, vz*dt1, vroll*dt1, vpitch*dt1, vyaw*dt1);
lastPose = rtabmap::Transform(vx*dt3, vy*dt3, vz*dt3, vroll*dt3, vpitch*dt3, vyaw*dt3);
}
if(firstPose.isNull())
{
UERROR("Could not get transform of %s accordingly to %s between stamps %f and %f!",
input.header.frame_id.c_str(),
fixedFrameId.empty()?"velocity":fixedFrameId.c_str(),
timestampFromROS(firstStamp),
timestampFromROS(input.header.stamp));
return false;
}
if(lastPose.isNull())
{
UERROR("Could not get transform of %s accordingly to %s between stamps %f and %f!",
input.header.frame_id.c_str(),
fixedFrameId.empty()?"velocity":fixedFrameId.c_str(),
timestampFromROS(lastStamp),
timestampFromROS(input.header.stamp));
return false;
}
scanTime = timestampFromROS(lastStamp) - timestampFromROS(firstStamp);
}
//else tf will be used to get more accurate transforms
output = input;
rclcpp::Time stamp;
bool clampWarned = false; // reported once per cloud, see the clamp below
UTimer processingTime;
if(timeOnColumns)
{
// ouster point cloud:
// t1 t2 ...
// ring1 ring1 ...
// ring2 ring2 ...
// ring3 ring4 ...
// ring4 ring3 ...
for(size_t u=0; u<output.width; ++u)
{
if(timeDatatype == 6) // UINT32
{
unsigned int nsec = *((const unsigned int*)(&output.data[u*output.point_step]+offsetTime));
stamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration(0, nsec);
}
else if(timeDatatype == 7) //float 32
{
float sec = *((const float*)(&output.data[u*output.point_step]+offsetTime));
stamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration::from_seconds(sec);
}
else if(timeDatatype == 8) //float64
{
double sec = *((const double*)(&output.data[u*output.point_step]+offsetTime));
if(sec > 1.e18)
{
// convert nanoseconds to seconds
sec /= 1.e9;
}
else if(sec > 1.e15)
{
// convert microseconds to seconds
sec /= 1.e6;
}
else if(sec > 1.e12)
{
// sec milliseconds to seconds
sec /= 1.e3;
}
stamp = timestampToROS(sec);
}
rtabmap::Transform transform;
if(slerp)
{
// The ordering check only compares the first and last samples, so a stamp
// outside [firstStamp, lastStamp] can slip through. Clamp it: extrapolating
// would throw the point far beyond the sweep.
double ratio = (stamp-firstStamp).seconds() / scanTime;
if(ratio < 0.0 || ratio > 1.0)
{
// Warned once per cloud rather than once per process: the timestamp
// channel is corrupted, which is a serious upstream problem worth
// reporting on every affected scan, but not once per point.
if(!clampWarned)
{
UWARN("A point has a stamp (%f) outside the first (%f) and last (%f) "
"stamps of the scan, its correction is clamped to the closest end "
"of the sweep. The timestamp channel of the input cloud is likely "
"corrupted. Only the first such point of this cloud is reported.",
timestampFromROS(stamp), timestampFromROS(firstStamp), timestampFromROS(lastStamp));
clampWarned = true;
}
ratio = ratio<0.0?0.0:1.0;
}
transform = firstPose.interpolate(float(ratio), lastPose);
}
else
{
transform = rtabmap_conversions::getMovingTransform(
output.header.frame_id,
fixedFrameId,
output.header.stamp,
stamp,
*tfBuffer,
0);
if(transform.isNull())
{
UERROR("Could not get transform of %s accordingly to %s between stamps %f and %f!",
output.header.frame_id.c_str(),
fixedFrameId.c_str(),
timestampFromROS(stamp),
timestampFromROS(output.header.stamp));
return false;
}
}
for(size_t v=0; v<input.height; ++v)
{
unsigned char * dataPtr = &output.data[v*output.row_step + u*output.point_step];
float & x = *((float*)(dataPtr+offsetX));
float & y = *((float*)(dataPtr+offsetY));
float & z = *((float*)(dataPtr+offsetZ));
pcl::PointXYZ pt(x,y,z);
pt = rtabmap::util3d::transformPoint(pt, transform);
x = pt.x;
y = pt.y;
z = pt.z;
// set delta stamp to zero so that on downstream they know the cloud is deskewed
if(timeDatatype == 6) // UINT32
{
*((unsigned int*)(dataPtr+offsetTime)) = 0;
}
else if(timeDatatype == 7)
{
*((float*)(dataPtr+offsetTime)) = 0;
}
else if(timeDatatype == 8)
{
*((double*)(dataPtr+offsetTime)) = 0;
}
}
}
}
else // time on rows
{
// velodyne point cloud:
// t1 ring1 ring2 ring3 ring4
// t2 ring1 ring2 ring3 ring4
// t3 ring1 ring2 ring3 ring4
// t4 ring1 ring2 ring3 ring4
// ... ... ... ... ...
for(size_t v=0; v<output.height; ++v)
{
if(timeDatatype == 6) // UINT32
{
unsigned int nsec = *((const unsigned int*)(&output.data[v*output.row_step]+offsetTime));
stamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration(0, nsec);
}
else if(timeDatatype == 7) //float 32
{
float sec = *((const float*)(&output.data[v*output.row_step]+offsetTime));
stamp = rclcpp::Time(input.header.stamp)+rclcpp::Duration::from_seconds(sec);
}
else if(timeDatatype == 8)
{
double sec = *((const double*)(&output.data[v*output.row_step]+offsetTime));
if(sec > 1.e18)
{
// convert nanoseconds to seconds
sec /= 1.e9;
}
else if(sec > 1.e15)
{
// convert microseconds to seconds
sec /= 1.e6;
}
else if(sec > 1.e12)
{
// sec milliseconds to seconds
sec /= 1.e3;
}
stamp = timestampToROS(sec);
}
rtabmap::Transform transform;
if(slerp)
{
// The ordering check only compares the first and last samples, so a stamp
// outside [firstStamp, lastStamp] can slip through. Clamp it: extrapolating
// would throw the point far beyond the sweep.
double ratio = (stamp-firstStamp).seconds() / scanTime;
if(ratio < 0.0 || ratio > 1.0)
{
// Warned once per cloud rather than once per process: the timestamp
// channel is corrupted, which is a serious upstream problem worth
// reporting on every affected scan, but not once per point.
if(!clampWarned)
{
UWARN("A point has a stamp (%f) outside the first (%f) and last (%f) "
"stamps of the scan, its correction is clamped to the closest end "
"of the sweep. The timestamp channel of the input cloud is likely "
"corrupted. Only the first such point of this cloud is reported.",
timestampFromROS(stamp), timestampFromROS(firstStamp), timestampFromROS(lastStamp));
clampWarned = true;
}
ratio = ratio<0.0?0.0:1.0;
}
transform = firstPose.interpolate(float(ratio), lastPose);
}
else
{
transform = rtabmap_conversions::getMovingTransform(
output.header.frame_id,
fixedFrameId,
output.header.stamp,
stamp,
*tfBuffer,
0);
if(transform.isNull())
{
UERROR("Could not get transform of %s accordingly to %s between stamps %f and %f!",
output.header.frame_id.c_str(),
fixedFrameId.c_str(),
timestampFromROS(stamp),
timestampFromROS(output.header.stamp));
return false;
}
}
for(size_t u=0; u<input.width; ++u)
{
unsigned char * dataPtr = &output.data[v*output.row_step + u*output.point_step];
float & x = *((float*)(dataPtr+offsetX));
float & y = *((float*)(dataPtr+offsetY));
float & z = *((float*)(dataPtr+offsetZ));
pcl::PointXYZ pt(x,y,z);
pt = rtabmap::util3d::transformPoint(pt, transform);
x = pt.x;
y = pt.y;
z = pt.z;
// set delta stamp to zero so that on downstream they know the cloud is deskewed
if(timeDatatype == 6) // UINT32
{
*((unsigned int*)(dataPtr+offsetTime)) = 0;
}
else if(timeDatatype == 7)
{
*((float*)(dataPtr+offsetTime)) = 0;
}
else if(timeDatatype == 8)
{
*((double*)(dataPtr+offsetTime)) = 0;
}
}
}
}
UDEBUG("Lidar deskewing time=%fs (slerp=%s waitForTransform=%f)", processingTime.elapsed(), slerp?"true":"false", waitForTransform);
return true;
}
bool deskew(
const sensor_msgs::msg::PointCloud2 & input,
sensor_msgs::msg::PointCloud2 & output,
const std::string & fixedFrameId,
tf2_ros::Buffer & tfBuffer,
double waitForTransform,
bool slerp)
{
return deskew_impl(input, output, fixedFrameId, &tfBuffer, waitForTransform, slerp, rtabmap::Transform());
}
bool deskew(
const sensor_msgs::msg::PointCloud2 & input,
sensor_msgs::msg::PointCloud2 & output,
const rtabmap::Transform & velocity)
{
return deskew_impl(input, output, "", 0, 0, true, velocity);
}
void
transformPointCloud (
const Eigen::Matrix4f &transform,
const sensor_msgs::msg::PointCloud2 &in,
sensor_msgs::msg::PointCloud2 &out)
{
// Get X-Y-Z indices
int x_idx = pcl::getFieldIndex (in, "x");
int y_idx = pcl::getFieldIndex (in, "y");
int z_idx = pcl::getFieldIndex (in, "z");
if (x_idx == -1 || y_idx == -1 || z_idx == -1)
{
UERROR ("Input dataset has no X-Y-Z coordinates! Cannot convert to Eigen format.");
return;
}
if (in.fields[x_idx].datatype != sensor_msgs::msg::PointField::FLOAT32 ||
in.fields[y_idx].datatype != sensor_msgs::msg::PointField::FLOAT32 ||
in.fields[z_idx].datatype != sensor_msgs::msg::PointField::FLOAT32)
{
UERROR ("X-Y-Z coordinates not floats. Currently only floats are supported.");
return;
}
// Check if distance is available
int dist_idx = pcl::getFieldIndex (in, "distance");
// Copy the other data
if (&in != &out)
{
out.header = in.header;
out.height = in.height;
out.width = in.width;
out.fields = in.fields;
out.is_bigendian = in.is_bigendian;
out.point_step = in.point_step;
out.row_step = in.row_step;
out.is_dense = in.is_dense;
out.data.resize (in.data.size ());
// Copy everything as it's faster than copying individual elements
memcpy (&out.data[0], &in.data[0], in.data.size ());
}
Eigen::Array4i xyz_offset (in.fields[x_idx].offset, in.fields[y_idx].offset, in.fields[z_idx].offset, 0);
for (size_t i = 0; i < in.width * in.height; ++i)
{
Eigen::Vector4f pt (*(float*)&in.data[xyz_offset[0]], *(float*)&in.data[xyz_offset[1]], *(float*)&in.data[xyz_offset[2]], 1);
Eigen::Vector4f pt_out;
bool max_range_point = false;
// Only touch in.fields[dist_idx] when the "distance" field actually exists:
// indexing with -1 is out of bounds and aborts on a hardened libstdc++.
int distance_ptr_offset = 0;
float* distance_ptr = NULL;
if (dist_idx >= 0)
{
distance_ptr_offset = i*in.point_step + in.fields[dist_idx].offset;
distance_ptr = (float*)(&in.data[distance_ptr_offset]);
}
if (!std::isfinite (pt[0]) || !std::isfinite (pt[1]) || !std::isfinite (pt[2]))
{
if (distance_ptr==NULL || !std::isfinite(*distance_ptr)) // Invalid point
{
pt_out = pt;
}
else // max range point
{
pt[0] = *distance_ptr; // Replace x with the x value saved in distance
pt_out = transform * pt;
max_range_point = true;
//std::cout << pt[0]<<","<<pt[1]<<","<<pt[2]<<" => "<<pt_out[0]<<","<<pt_out[1]<<","<<pt_out[2]<<"\n";
}
}
else
{
pt_out = transform * pt;
}
if (max_range_point)
{
// Save x value in distance again
*(float*)(&out.data[distance_ptr_offset]) = pt_out[0];
pt_out[0] = std::numeric_limits<float>::quiet_NaN();
}
memcpy (&out.data[xyz_offset[0]], &pt_out[0], sizeof (float));
memcpy (&out.data[xyz_offset[1]], &pt_out[1], sizeof (float));
memcpy (&out.data[xyz_offset[2]], &pt_out[2], sizeof (float));
xyz_offset += in.point_step;
}
// Check if the viewpoint information is present
int vp_idx = pcl::getFieldIndex (in, "vp_x");
if (vp_idx != -1)
{
// Transform the viewpoint info too
for (size_t i = 0; i < out.width * out.height; ++i)
{
float *pstep = (float*)&out.data[i * out.point_step + out.fields[vp_idx].offset];
// Assume vp_x, vp_y, vp_z are consecutive
Eigen::Vector4f vp_in (pstep[0], pstep[1], pstep[2], 1);
Eigen::Vector4f vp_out = transform * vp_in;
pstep[0] = vp_out[0];
pstep[1] = vp_out[1];
pstep[2] = vp_out[2];
}
}
}
}