/* 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/core/odometry/OdometryDVO.h" #include "rtabmap/core/OdometryInfo.h" #include "rtabmap/core/util2d.h" #include "rtabmap/utilite/ULogger.h" #include "rtabmap/utilite/UTimer.h" #include "rtabmap/utilite/UStl.h" #include #ifdef RTABMAP_DVO #include #include #include #endif namespace rtabmap { OdometryDVO::OdometryDVO(const ParametersMap & parameters) : Odometry(parameters), #ifdef RTABMAP_DVO dvo_(0), reference_(0), camera_(0), lost_(false), #endif motionFromKeyFrame_(Transform::getIdentity()) { } OdometryDVO::~OdometryDVO() { #ifdef RTABMAP_DVO delete dvo_; delete reference_; delete camera_; #endif } void OdometryDVO::reset(const Transform & initialPose) { Odometry::reset(initialPose); #ifdef RTABMAP_DVO if(dvo_) { delete dvo_; dvo_ = 0; } if(reference_) { delete reference_; reference_ = 0; } if(camera_) { delete camera_; camera_ = 0; } lost_ = false; motionFromKeyFrame_.setIdentity(); previousLocalTransform_.setNull(); #endif } // return not null transform if odometry is correctly computed Transform OdometryDVO::computeTransform( SensorData & data, const Transform & guess, OdometryInfo * info) { Transform t; #ifdef RTABMAP_DVO UTimer timer; if(data.imageRaw().empty() || data.imageRaw().rows != data.depthOrRightRaw().rows || data.imageRaw().cols != data.depthOrRightRaw().cols) { UERROR("Not supported input!"); return t; } if(!(data.cameraModels().size() == 1 && data.cameraModels()[0].isValidForReprojection())) { UERROR("Invalid camera model! Only single RGB-D camera supported by DVO. Try another odometry approach."); return t; } if(dvo_ == 0) { dvo::DenseTracker::Config cfg = dvo::DenseTracker::getDefaultConfig(); dvo_ = new dvo::DenseTracker(cfg); } cv::Mat grey, grey_s16, depth_inpainted, depth_mask, depth_mono, depth_float; if(data.imageRaw().type() != CV_32FC1) { if(data.imageRaw().type() == CV_8UC3) { cv::cvtColor(data.imageRaw(), grey, CV_BGR2GRAY); } else { grey = data.imageRaw(); } grey.convertTo(grey_s16, CV_32F); } else { grey_s16 = data.imageRaw(); } // make sure all zeros are NAN if(data.depthRaw().type() == CV_32FC1) { depth_float = data.depthRaw(); for(int i=0; i(i,j); if(d == 0.0f) { d = NAN; } } } } else if(data.depthRaw().type() == CV_16UC1) { depth_float = cv::Mat(data.depthRaw().size(), CV_32FC1); for(int i=0; i(i,j))/1000.0f; depth_float.at(i, j) = d==0.0f?NAN:d; } } } else { UFATAL("Unknown depth format!"); } if(camera_ == 0) { dvo::core::IntrinsicMatrix intrinsics = dvo::core::IntrinsicMatrix::create( data.cameraModels()[0].fx(), data.cameraModels()[0].fy(), data.cameraModels()[0].cx(), data.cameraModels()[0].cy()); camera_ = new dvo::core::RgbdCameraPyramid( data.cameraModels()[0].imageWidth(), data.cameraModels()[0].imageHeight(), intrinsics); } dvo::core::RgbdImagePyramid * current = new dvo::core::RgbdImagePyramid(*camera_, grey_s16, depth_float); const Transform & localTransform = data.cameraModels()[0].localTransform(); cv::Mat covariance; if(reference_ == 0) { reference_ = current; if(!lost_) { t.setIdentity(); } covariance = cv::Mat::eye(6,6,CV_64FC1) * 9999.0; } else { dvo::DenseTracker::Result result; dvo_->match(*reference_, *current, result); t = Transform::fromEigen3d(result.Transformation); if(result.Information(0,0) > 0.0 && result.Information(0,0) != 1.0) { lost_ = false; cv::Mat information = cv::Mat::eye(6,6, CV_64FC1); memcpy(information.data, result.Information.data(), 36*sizeof(double)); //copy only diagonal to avoid g2o/gtsam errors on graph optimization covariance = cv::Mat::eye(6,6,CV_64FC1); covariance = information.inv().mul(covariance); //covariance *= 100.0; // to be in the same scale than loop closure detection Transform currentMotion = t; t = motionFromKeyFrame_.inverse() * t; // TODO make parameters? if(currentMotion.getNorm() > 0.01 || currentMotion.getAngle() > 0.01) { if(info) { info->keyFrameAdded = true; } // new keyframe delete reference_; reference_ = current; motionFromKeyFrame_.setIdentity(); } else { delete current; motionFromKeyFrame_ = currentMotion; } } else { lost_ = true; delete reference_; delete current; reference_ = 0; // this will make restart from the next frame motionFromKeyFrame_.setIdentity(); t.setNull(); previousLocalTransform_.setNull(); covariance = cv::Mat::eye(6,6,CV_64FC1) * 9999.0; UWARN("dvo failed to estimate motion, tracking will be reinitialized on next frame."); } if(!t.isNull() && !t.isIdentity() && !localTransform.isIdentity() && !localTransform.isNull()) { // from camera frame to base frame if(!previousLocalTransform_.isNull()) { t = previousLocalTransform_ * t * localTransform.inverse(); } else { t = localTransform * t * localTransform.inverse(); } previousLocalTransform_ = localTransform; } } if(info) { info->type = (int)kTypeDVO; info->reg.covariance = covariance; } UINFO("Odom update time = %fs", timer.elapsed()); #else UERROR("RTAB-Map is not built with DVO support! Select another visual odometry approach."); #endif return t; } } // namespace rtabmap