/* 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/OdometryInfo.h" #include "rtabmap/core/Signature.h" #include "rtabmap/core/RegistrationVis.h" #include "rtabmap/core/util3d.h" #include "rtabmap/core/util3d_transforms.h" #include "rtabmap/core/util3d_registration.h" #include "rtabmap/core/util3d_motion_estimation.h" #include "rtabmap/core/util3d_filtering.h" #include "rtabmap/core/util3d_surface.h" #include "rtabmap/core/Optimizer.h" #include "rtabmap/core/VWDictionary.h" #include "rtabmap/core/Graph.h" #include "rtabmap/utilite/ULogger.h" #include "rtabmap/utilite/UTimer.h" #include "rtabmap/utilite/UMath.h" #include "rtabmap/utilite/UStl.h" #include "rtabmap/utilite/UConversion.h" #if CV_MAJOR_VERSION < 5 #include #else #include #endif #include #include #if _MSC_VER #define ISFINITE(value) _finite(value) #else #define ISFINITE(value) std::isfinite(value) #endif namespace rtabmap { OdometryF2M::OdometryF2M(const ParametersMap & parameters) : Odometry(parameters), maximumMapSize_(Parameters::defaultOdomF2MMaxSize()), keyFrameThr_(Parameters::defaultOdomKeyFrameThr()), visKeyFrameThr_(Parameters::defaultOdomVisKeyFrameThr()), maxNewFeatures_(Parameters::defaultOdomF2MMaxNewFeatures()), initDepthFactor_(Parameters::defaultOdomF2MInitDepthFactor()), floorThreshold_(Parameters::defaultOdomF2MFloorThreshold()), scanKeyFrameThr_(Parameters::defaultOdomScanKeyFrameThr()), scanMaximumMapSize_(Parameters::defaultOdomF2MScanMaxSize()), scanSubtractRadius_(Parameters::defaultOdomF2MScanSubtractRadius()), scanSubtractAngle_(Parameters::defaultOdomF2MScanSubtractAngle()), scanMapMaxRange_(Parameters::defaultOdomF2MScanRange()), bundleAdjustment_(Parameters::defaultOdomF2MBundleAdjustment()), bundleMaxFrames_(Parameters::defaultOdomF2MBundleAdjustmentMaxFrames()), bundleMinMotion_(Parameters::defaultOdomF2MBundleAdjustmentMinMotion()), bundleMaxKeyFramesPerFeature_(Parameters::defaultOdomF2MBundleAdjustmentMaxKeyFramesPerFeature()), bundleUpdateFeatureMapOnAllFrames_(Parameters::defaultOdomF2MBundleUpdateFeatureMapOnAllFrames()), validDepthRatio_(Parameters::defaultOdomF2MValidDepthRatio()), pointToPlaneK_(Parameters::defaultIcpPointToPlaneK()), pointToPlaneRadius_(Parameters::defaultIcpPointToPlaneRadius()), map_(new Signature(-1)), lastFrame_(new Signature(1)), lastFrameOldestNewId_(0), bundleSeq_(0), sba_(0) { UDEBUG(""); Parameters::parse(parameters, Parameters::kOdomF2MMaxSize(), maximumMapSize_); Parameters::parse(parameters, Parameters::kOdomKeyFrameThr(), keyFrameThr_); Parameters::parse(parameters, Parameters::kOdomVisKeyFrameThr(), visKeyFrameThr_); Parameters::parse(parameters, Parameters::kOdomF2MMaxNewFeatures(), maxNewFeatures_); Parameters::parse(parameters, Parameters::kOdomF2MInitDepthFactor(), initDepthFactor_); Parameters::parse(parameters, Parameters::kOdomF2MFloorThreshold(), floorThreshold_); Parameters::parse(parameters, Parameters::kOdomScanKeyFrameThr(), scanKeyFrameThr_); Parameters::parse(parameters, Parameters::kOdomF2MScanMaxSize(), scanMaximumMapSize_); Parameters::parse(parameters, Parameters::kOdomF2MScanSubtractRadius(), scanSubtractRadius_); if(Parameters::parse(parameters, Parameters::kOdomF2MScanSubtractAngle(), scanSubtractAngle_)) { scanSubtractAngle_ *= M_PI/180.0f; } Parameters::parse(parameters, Parameters::kOdomF2MScanRange(), scanMapMaxRange_); Parameters::parse(parameters, Parameters::kOdomF2MBundleAdjustment(), bundleAdjustment_); Parameters::parse(parameters, Parameters::kOdomF2MBundleAdjustmentMaxFrames(), bundleMaxFrames_); Parameters::parse(parameters, Parameters::kOdomF2MBundleAdjustmentMinMotion(), bundleMinMotion_); Parameters::parse(parameters, Parameters::kOdomF2MBundleAdjustmentMaxKeyFramesPerFeature(), bundleMaxKeyFramesPerFeature_); Parameters::parse(parameters, Parameters::kOdomF2MBundleUpdateFeatureMapOnAllFrames(), bundleUpdateFeatureMapOnAllFrames_); Parameters::parse(parameters, Parameters::kOdomF2MValidDepthRatio(), validDepthRatio_); Parameters::parse(parameters, Parameters::kIcpPointToPlaneK(), pointToPlaneK_); Parameters::parse(parameters, Parameters::kIcpPointToPlaneRadius(), pointToPlaneRadius_); UASSERT(bundleMaxFrames_ >= 0); ParametersMap bundleParameters = parameters; if(bundleAdjustment_ > 0) { // The BundleAdjustment int matches the Optimizer/Strategy parameter // 1:1 (g2o=1, GTSAM=2, Ceres=3, CVSBA=4). 0 = "disabled" -- it's // the TORO slot, which isn't BA-capable. const Optimizer::Type sbaType = static_cast(bundleAdjustment_); if(Optimizer::isAvailable(sbaType)) { // disable bundle in RegistrationVis as we do it already here uInsert(bundleParameters, ParametersPair(Parameters::kVisBundleAdjustment(), "0")); sba_ = Optimizer::create(sbaType, bundleParameters); } else { UWARN("Selected bundle adjustment approach (\"%s\"=\"%d\") is not available, " "local bundle adjustment is then disabled.", Parameters::kOdomF2MBundleAdjustment().c_str(), bundleAdjustment_); bundleAdjustment_ = 0; } } UASSERT(maximumMapSize_ >= 0); UASSERT(keyFrameThr_ >= 0.0f && keyFrameThr_<=1.0f); UASSERT(visKeyFrameThr_>=0); UASSERT(scanKeyFrameThr_ >= 0.0f && scanKeyFrameThr_<=1.0f); UASSERT(maxNewFeatures_ >= 0); UASSERT(initDepthFactor_>0.0f); int corType = Parameters::defaultVisCorType(); Parameters::parse(parameters, Parameters::kVisCorType(), corType); if(corType != 0) { UWARN("%s=%d is not supported by OdometryF2M, using Features matching approach instead (type=0).", Parameters::kVisCorType().c_str(), corType); corType = 0; } uInsert(bundleParameters, ParametersPair(Parameters::kVisCorType(), uNumber2Str(corType))); int estType = Parameters::defaultVisEstimationType(); Parameters::parse(parameters, Parameters::kVisEstimationType(), estType); if(estType > 1) { UWARN("%s=%d is not supported by OdometryF2M, using 2D->3D approach instead (type=1).", Parameters::kVisEstimationType().c_str(), estType); estType = 1; } uInsert(bundleParameters, ParametersPair(Parameters::kVisEstimationType(), uNumber2Str(estType))); regPipeline_ = Registration::create(bundleParameters); if(bundleAdjustment_>0 && regPipeline_->isScanRequired()) { if(regPipeline_->isImageRequired()) { UWARN("%s=%d cannot be used with registration not done only with images (%s=%s), disabling bundle adjustment.", Parameters::kOdomF2MBundleAdjustment().c_str(), bundleAdjustment_, Parameters::kRegStrategy().c_str(), uValue(bundleParameters, Parameters::kRegStrategy(), uNumber2Str(Parameters::defaultRegStrategy())).c_str()); } bundleAdjustment_ = 0; } parameters_ = bundleParameters; } OdometryF2M::~OdometryF2M() { delete map_; delete lastFrame_; delete sba_; delete regPipeline_; UDEBUG(""); } void OdometryF2M::reset(const Transform & initialPose) { Odometry::reset(initialPose); UDEBUG("initialPose=%s", initialPose.prettyPrint().c_str()); Odometry::reset(initialPose); *lastFrame_ = Signature(1); *map_ = Signature(-1); scansBuffer_.clear(); bundleWordReferences_.clear(); bundlePoses_.clear(); bundleLinks_.clear(); bundleModels_.clear(); bundlePoseReferences_.clear(); bundleSeq_ = 0; lastFrameOldestNewId_ = 0; } // return not null transform if odometry is correctly computed Transform OdometryF2M::computeTransform( SensorData & data, const Transform & guessIn, OdometryInfo * info) { Transform guess = guessIn; UTimer timer; Transform output; if(info) { info->type = 0; } Transform imuT; if(sba_ && sba_->gravitySigma() > 0.0f && !imus().empty()) { imuT = Transform::getTransform(imus(), data.stamp()); if(data.imu().empty()) { Eigen::Quaternionf q = imuT.getQuaternionf(); data.setIMU(IMU(cv::Vec4d(q.x(), q.y(), q.z(), q.w()), cv::Mat(), cv::Vec3d(), cv::Mat(), cv::Vec3d(), cv::Mat())); } } RegistrationInfo regInfo; int nFeatures = 0; delete lastFrame_; int id = data.id(); data.setId(++bundleSeq_); // generate our own unique ids, to make sure they are correctly set lastFrame_ = new Signature(data); data.setId(id); bool addKeyFrame = false; int totalBundleWordReferencesUsed = 0; int totalBundleOutliers = 0; float bundleTime = 0.0f; bool visDepthAsMask = Parameters::defaultVisDepthAsMask(); Parameters::parse(parameters_, Parameters::kVisDepthAsMask(), visDepthAsMask); std::vector lastFrameModels; if(!lastFrame_->sensorData().cameraModels().empty() && lastFrame_->sensorData().cameraModels().at(0).isValidForProjection()) { lastFrameModels = lastFrame_->sensorData().cameraModels(); } else if(!lastFrame_->sensorData().stereoCameraModels().empty() && lastFrame_->sensorData().stereoCameraModels().at(0).isValidForProjection()) { for(size_t i=0; isensorData().stereoCameraModels().size(); ++i) { CameraModel model = lastFrame_->sensorData().stereoCameraModels()[i].left(); // Set Tx for stereo BA model = CameraModel(model.fx(), model.fy(), model.cx(), model.cy(), model.localTransform(), -lastFrame_->sensorData().stereoCameraModels()[i].baseline()*model.fx(), model.imageSize()); lastFrameModels.push_back(model); } } UDEBUG("lastFrameModels=%ld", lastFrameModels.size()); // Generate keypoints from the new data if(lastFrame_->sensorData().isValid()) { if((map_->getWords3().size() || !map_->sensorData().laserScanRaw().isEmpty()) && lastFrame_->sensorData().isValid()) { Signature tmpMap; Transform transform; UDEBUG("guess=%s frames=%d image required=%d", guess.prettyPrint().c_str(), this->framesProcessed(), regPipeline_->isImageRequired()?1:0); // bundle adjustment stuff if used std::map points3DMap; std::map bundlePoses; std::multimap bundleLinks; std::map > bundleModels; float bundleAvgInlierDistance = 0.0f; for(int guessIteration=0; guessIteration<(!guess.isNull()&®Pipeline_->isImageRequired()?2:1) && transform.isNull(); ++guessIteration) { tmpMap = *map_; // reset matches, but keep already extracted features in lastFrame_->sensorData() lastFrame_->removeAllWords(); points3DMap.clear(); bundlePoses.clear(); bundleLinks.clear(); bundleModels.clear(); float maxCorrespondenceDistance = 0.0f; float outlierRatio = 0.0f; if(guess.isNull() && !regPipeline_->isImageRequired() && regPipeline_->isScanRequired() && this->framesProcessed() < 2) { // only on initialization (first frame to register), increase icp max correspondences in case the robot is already moving maxCorrespondenceDistance = Parameters::defaultIcpMaxCorrespondenceDistance(); outlierRatio = Parameters::defaultIcpOutlierRatio(); Parameters::parse(parameters_, Parameters::kIcpMaxCorrespondenceDistance(), maxCorrespondenceDistance); Parameters::parse(parameters_, Parameters::kIcpOutlierRatio(), outlierRatio); ParametersMap params; params.insert(ParametersPair(Parameters::kIcpMaxCorrespondenceDistance(), uNumber2Str(maxCorrespondenceDistance*3.0f))); params.insert(ParametersPair(Parameters::kIcpOutlierRatio(), uNumber2Str(0.95f))); regPipeline_->parseParameters(params); } if(guessIteration == 1) { UWARN("Failed to find a transformation with the provided guess (%s), trying again without a guess.", guess.prettyPrint().c_str()); } transform = regPipeline_->computeTransformationMod( tmpMap, *lastFrame_, // special case for ICP-only odom, set guess to identity if we just started or reset guessIteration==0 && !guess.isNull()?this->getPose()*guess:!regPipeline_->isImageRequired()&&this->framesProcessed()<2?this->getPose():Transform(), ®Info); if(maxCorrespondenceDistance>0.0f) { // set it back ParametersMap params; params.insert(ParametersPair(Parameters::kIcpMaxCorrespondenceDistance(), uNumber2Str(maxCorrespondenceDistance))); params.insert(ParametersPair(Parameters::kIcpOutlierRatio(), uNumber2Str(outlierRatio))); regPipeline_->parseParameters(params); } data.setFeatures(lastFrame_->sensorData().keypoints(), lastFrame_->sensorData().keypoints3D(), lastFrame_->sensorData().descriptors()); data.setLaserScan(lastFrame_->sensorData().laserScanRaw()); UDEBUG("Registration time = %fs", regInfo.totalTime); if(!transform.isNull()) { // local bundle adjustment if(bundleAdjustment_>0 && sba_ && regPipeline_->isImageRequired() && !lastFrameModels.empty() && regInfo.inliersIDs.size()) { UDEBUG("Local Bundle Adjustment"); // make sure the IDs of words in the map are not modified (Optical Flow Registration issue) UASSERT(map_->getWords().size() && tmpMap.getWords().size()); if(map_->getWords().size() != tmpMap.getWords().size() || map_->getWords().begin()->first != tmpMap.getWords().begin()->first || map_->getWords().rbegin()->first != tmpMap.getWords().rbegin()->first) { UERROR("Bundle Adjustment cannot be used with a registration approach recomputing " "features from the \"from\" signature (e.g., Optical Flow) that would change " "their ids (size=old=%ld new=%ld first/last: old=%d->%d new=%d->%d).", map_->getWords().size(), tmpMap.getWords().size(), map_->getWords().begin()->first, map_->getWords().rbegin()->first, tmpMap.getWords().begin()->first, tmpMap.getWords().rbegin()->first); bundleAdjustment_ = 0; } else { UASSERT(bundlePoses_.size()); UASSERT_MSG(bundlePoses_.size()-1 == bundleLinks_.size(), uFormat("poses=%d links=%d", (int)bundlePoses_.size(), (int)bundleLinks_.size()).c_str()); UASSERT(bundlePoses_.size() == bundleModels_.size()); bundlePoses = bundlePoses_; bundleLinks = bundleLinks_; bundleModels = bundleModels_; bundleLinks.insert(bundleIMUOrientations_.begin(), bundleIMUOrientations_.end()); UASSERT_MSG(bundlePoses.find(lastFrame_->id()) == bundlePoses.end(), uFormat("Frame %d already added! Make sure the input frames have unique IDs!", lastFrame_->id()).c_str()); bundleLinks.insert(std::make_pair(bundlePoses_.rbegin()->first, Link(bundlePoses_.rbegin()->first, lastFrame_->id(), Link::kNeighbor, bundlePoses_.rbegin()->second.inverse()*transform, regInfo.covariance.inv()))); bundlePoses.insert(std::make_pair(lastFrame_->id(), transform)); if(!imuT.isNull()) { bundleLinks.insert(std::make_pair(lastFrame_->id(), Link(lastFrame_->id(), lastFrame_->id(), Link::kGravity, imuT))); } bundleModels.insert(std::make_pair(lastFrame_->id(), lastFrameModels)); UDEBUG("Fill matches (%d)", (int)regInfo.inliersIDs.size()); std::map > wordReferences; size_t maxKeyFramesForInlier = 0; for(unsigned int i=0; i::const_iterator iter3D = tmpMap.getWords().find(wordId); UASSERT(iter3D!=tmpMap.getWords().end() && !tmpMap.getWords3().empty()); points3DMap.insert(std::make_pair(wordId, tmpMap.getWords3()[iter3D->second])); // all other references std::map >::iterator refIter = bundleWordReferences_.find(wordId); UASSERT_MSG(refIter != bundleWordReferences_.end(), uFormat("wordId=%d", wordId).c_str()); if(info && refIter->second.size() > maxKeyFramesForInlier) { maxKeyFramesForInlier = refIter->second.size(); } std::map references; int step = bundleMaxFrames_>0?(refIter->second.size() / bundleMaxFrames_):1; if(step == 0) { step = 1; } int oi=0; for(std::map::iterator jter=refIter->second.begin(); jter!=refIter->second.end(); ++jter) { if(oi++ % step == 0 && bundlePoses.find(jter->first)!=bundlePoses.end()) { references.insert(*jter); ++totalBundleWordReferencesUsed; } } //make sure the last reference is here if(refIter->second.size() > 1) { if(references.insert(*refIter->second.rbegin()).second) { ++totalBundleWordReferencesUsed; } } std::multimap::const_iterator iter2D = lastFrame_->getWords().find(wordId); if(iter2D!=lastFrame_->getWords().end()) { UASSERT(!lastFrame_->getWordsKpts().empty()); cv::KeyPoint kpt = lastFrame_->getWordsKpts()[iter2D->second]; int cameraIndex = 0; if(lastFrameModels.size()>1) { UASSERT(lastFrameModels[0].imageWidth()>0); float subImageWidth = lastFrameModels[0].imageWidth(); cameraIndex = int(kpt.pt.x / subImageWidth); UASSERT(cameraIndex < (int)lastFrameModels.size()); kpt.pt.x = kpt.pt.x - (subImageWidth*float(cameraIndex)); } //get depth float d = 0.0f; if( !lastFrame_->getWords3().empty() && util3d::isFinite(lastFrame_->getWords3()[iter2D->second])) { //move back point in camera frame (to get depth along z) d = util3d::transformPoint(lastFrame_->getWords3()[iter2D->second], lastFrameModels[cameraIndex].localTransform().inverse()).z; } references.insert(std::make_pair(lastFrame_->id(), FeatureBA(kpt, d, cv::Mat(), cameraIndex))); } wordReferences.insert(std::make_pair(wordId, references)); //UDEBUG("%d (%f,%f,%f)", iter3D->first, iter3D->second.x, iter3D->second.y, iter3D->second.z); //for(std::map::iterator iter=inserted.first->second.begin(); iter!=inserted.first->second.end(); ++iter) //{ // UDEBUG("%d (%f,%f)", iter->first, iter->second.x, iter->second.y); //} } UDEBUG("sba...start"); // set root negative to fix all other poses BAOutliers sbaOutliers; UTimer bundleTimer; bundlePoses = sba_->optimizeBA(-lastFrame_->id(), bundlePoses, bundleLinks, bundleModels, points3DMap, wordReferences, &sbaOutliers); bundleTime = bundleTimer.ticks(); UDEBUG("sba...end"); int sbaOutliersCount = 0; for(unsigned int i=0; isecond.find(lastFrame_->id()) != iter->second.end()) { ++sbaOutliersCount; } } totalBundleOutliers = sbaOutliersCount; UDEBUG("bundleTime=%fs (poses=%d wordRef=%d outliers=%d)", bundleTime, (int)bundlePoses.size(), (int)bundleWordReferences_.size(), sbaOutliersCount); if(info) { info->localBundlePoses = bundlePoses; info->localBundleModels = bundleModels; info->localBundleMaxKeyFramesForInlier = maxKeyFramesForInlier; } UDEBUG("Local Bundle Adjustment Before: %s", transform.prettyPrint().c_str()); if(bundlePoses.size() == bundlePoses_.size()+1) { if(!bundlePoses.rbegin()->second.isNull()) { if(info) { info->localBundleOutliersPerCam = std::vector(lastFrameModels.size(),0); } if(sbaOutliersCount) { regInfo.inliersPerCam = std::vector(lastFrameModels.size(),0); std::vector newInliers(regInfo.inliersIDs.size()); int oi=0; for(unsigned int i=0; isecond.find(lastFrame_->id()) == iter->second.end()) { newInliers[oi++] = regInfo.inliersIDs[i]; regInfo.inliersPerCam[wordReferences.at(regInfo.inliersIDs[i]).at(lastFrame_->id()).cameraIndex] += 1; } else if(info) { info->localBundleOutliersPerCam[wordReferences.at(regInfo.inliersIDs[i]).at(lastFrame_->id()).cameraIndex] += 1; } } newInliers.resize(oi); UDEBUG("BA outliers ratio %f", float(sbaOutliersCount)/float(regInfo.inliersIDs.size())); regInfo.inliers = (int)newInliers.size(); regInfo.inliersIDs = newInliers; } if(regInfo.inliers < regPipeline_->getMinVisualCorrespondences()) { regInfo.rejectedMsg = uFormat("Too low inliers after bundle adjustment: %d<%d", regInfo.inliers, regPipeline_->getMinVisualCorrespondences()); transform.setNull(); } else { transform = bundlePoses.rbegin()->second; std::multimap::iterator iter = graph::findLink(bundleLinks, bundlePoses_.rbegin()->first, lastFrame_->id(), false); UASSERT(iter != bundleLinks.end()); iter->second.setTransform(bundlePoses_.rbegin()->second.inverse()*transform); iter = graph::findLink(bundleLinks, lastFrame_->id(), lastFrame_->id(), false); if(info && iter!=bundleLinks.end() && iter->second.type() == Link::kGravity) { float rollImu,pitchImu,yaw; iter->second.transform().getEulerAngles(rollImu, pitchImu, yaw); float roll,pitch; transform.getEulerAngles(roll, pitch, yaw); info->gravityRollError = fabs(rollImu - roll); info->gravityPitchError = fabs(pitchImu - pitch); } // With bundle adjustment, scale down covariance by 10 UASSERT(regInfo.covariance.cols==6 && regInfo.covariance.rows == 6 && regInfo.covariance.type() == CV_64FC1); double thrLin = Registration::COVARIANCE_LINEAR_EPSILON*10.0; double thrAng = Registration::COVARIANCE_ANGULAR_EPSILON*10.0; if(regInfo.covariance.at(0,0)>thrLin) regInfo.covariance.at(0,0) *= 0.1; if(regInfo.covariance.at(1,1)>thrLin) regInfo.covariance.at(1,1) *= 0.1; if(regInfo.covariance.at(2,2)>thrLin) regInfo.covariance.at(2,2) *= 0.1; if(regInfo.covariance.at(3,3)>thrAng) regInfo.covariance.at(3,3) *= 0.1; if(regInfo.covariance.at(4,4)>thrAng) regInfo.covariance.at(4,4) *= 0.1; if(regInfo.covariance.at(5,5)>thrAng) regInfo.covariance.at(5,5) *= 0.1; // Estimate how much the new frame moved from previous frame in term of pixels if(bundleMinMotion_ > 0.0f) { UASSERT(!bundlePoses_.empty()); int count = 0; for(unsigned int i=0; i >::iterator wter = wordReferences.find(regInfo.inliersIDs[i]); if(wter != wordReferences.end()) { std::map::iterator fter = wter->second.find(bundlePoses_.rbegin()->first); if(fter != wter->second.end()) { const FeatureBA & f1 = fter->second; // previous key-frame const FeatureBA & f2 = wter->second.find(lastFrame_->id())->second; // current key-frame float dx = f1.kpt.pt.x - f2.kpt.pt.x; float dy = f1.kpt.pt.y - f2.kpt.pt.y; bundleAvgInlierDistance += sqrt(dx*dx + dy*dy); ++count; } } } if(count) { bundleAvgInlierDistance /= count; } UDEBUG("Average pixel distance between %d inliers: %f", count, bundleAvgInlierDistance); if(info) { info->localBundleAvgInlierDistance = bundleAvgInlierDistance; } } } UDEBUG("Local Bundle Adjustment After : %s", transform.prettyPrint().c_str()); } else { regInfo.rejectedMsg = "Last bundle pose is null?!"; transform.setNull(); } } else { regInfo.rejectedMsg = "Local bundle adjustment failed!"; transform.setNull(); } } } if(!transform.isNull()) { // make it incremental transform = this->getPose().inverse() * transform; } } if(transform.isNull()) { if(guessIteration == 1) { UWARN("Trial with no guess still fail."); } if(!regInfo.rejectedMsg.empty()) { if(guess.isNull()) { UWARN("Registration failed: \"%s\"", regInfo.rejectedMsg.c_str()); } else { UWARN("Registration failed: \"%s\" (guess=%s)", regInfo.rejectedMsg.c_str(), guess.prettyPrint().c_str()); } } else { UWARN("Unknown registration error"); } } else if(guessIteration == 1) { UWARN("Trial with no guess succeeded!"); } } if(!transform.isNull()) { output = transform; bool modified = false; Transform newFramePose = this->getPose()*output; // fields to update LaserScan mapScan = tmpMap.sensorData().laserScanRaw(); std::multimap mapWords = tmpMap.getWords(); std::vector mapWordsKpts = tmpMap.getWordsKpts(); std::vector mapPoints = tmpMap.getWords3(); cv::Mat mapDescriptors = tmpMap.getWordsDescriptors(); // update last frame features without depth (if bundle adjustment was done) // Do this before adding bundle frames to keep mono observations without depth bool lastFrameWords3Updated = false; std::vector lastFrameWords3; if( regPipeline_->isImageRequired() && !visDepthAsMask && bundleAdjustment_>0 && !lastFrame_->getWords().empty() && lastFrame_->getWords().size() == lastFrame_->getWords3().size() && !points3DMap.empty()) { lastFrameWords3 = lastFrame_->getWords3(); Transform newFramePoseInv = newFramePose.inverse(); for(std::multimap::const_iterator iter=lastFrame_->getWords().begin(); iter!=lastFrame_->getWords().end(); ++iter) { cv::Point3f & pt = lastFrameWords3.at(iter->second); if(!util3d::isFinite(pt)) { std::map::iterator mapIter = points3DMap.find(iter->first); if(mapIter != points3DMap.end()) { // in base frame pt = util3d::transformPoint(mapIter->second, newFramePoseInv); lastFrameWords3Updated = true; } } } } if( regPipeline_->isImageRequired() && bundleAdjustment_>0 && bundleUpdateFeatureMapOnAllFrames_ && !points3DMap.empty()) { // update local map 3D points (if bundle adjustment was done) for(std::map::iterator iter=points3DMap.begin(); iter!=points3DMap.end(); ++iter) { UASSERT(mapWords.count(iter->first) == 1); mapPoints[mapWords.find(iter->first)->second] = iter->second; } modified = true; } bool addVisualKeyFrame = regPipeline_->isImageRequired() && (keyFrameThr_ == 0.0f || visKeyFrameThr_ == 0 || float(regInfo.inliers) <= (keyFrameThr_*float(lastFrame_->getWords().size())) || regInfo.inliers <= visKeyFrameThr_) && (bundleAdjustment_==0 || bundleAvgInlierDistance >= bundleMinMotion_); bool addGeometricKeyFrame = regPipeline_->isScanRequired() && (scanKeyFrameThr_==0 || regInfo.icpInliersRatio <= scanKeyFrameThr_); addKeyFrame = addVisualKeyFrame || addGeometricKeyFrame; UDEBUG("keyframeThr=%f visKeyFrameThr_=%d matches=%d inliers=%d (avg dist=%f, min=%f) features=%d mp=%d", keyFrameThr_, visKeyFrameThr_, regInfo.matches, regInfo.inliers, bundleAvgInlierDistance, bundleMinMotion_, (int)lastFrame_->sensorData().keypoints().size(), (int)mapPoints.size()); if(addKeyFrame) { //Visual int added = 0; int removed = 0; UTimer tmpTimer; UDEBUG("Update local map"); modified = bundleAdjustment_>0; // We always add new references even if we don't add/remove points // update local map UASSERT(mapWords.size() == mapPoints.size()); UASSERT(mapWords.size() == mapWordsKpts.size()); UASSERT((int)mapPoints.size() == mapDescriptors.rows); UASSERT_MSG(lastFrame_->getWordsDescriptors().rows == (int)lastFrame_->getWords3().size(), uFormat("%d vs %d", lastFrame_->getWordsDescriptors().rows, (int)lastFrame_->getWords3().size()).c_str()); std::map::iterator iterBundlePosesRef = bundlePoseReferences_.end(); if(bundleAdjustment_>0) { bundlePoseReferences_.insert(std::make_pair(lastFrame_->id(), 0)); std::multimap::iterator iter = graph::findLink(bundleLinks, bundlePoses_.rbegin()->first, lastFrame_->id(), false); UASSERT(iter != bundleLinks.end()); bundleLinks_.insert(*iter); iter = graph::findLink(bundleLinks, lastFrame_->id(), lastFrame_->id(), false); if(iter != bundleLinks.end()) { bundleIMUOrientations_.insert(*iter); } uInsert(bundlePoses_, bundlePoses); UASSERT(bundleModels.find(lastFrame_->id()) != bundleModels.end()); bundleModels_.insert(*bundleModels.find(lastFrame_->id())); iterBundlePosesRef = bundlePoseReferences_.find(lastFrame_->id()); if(!bundleUpdateFeatureMapOnAllFrames_) { // update local map 3D points (if bundle adjustment was done) for(std::map::iterator iter=points3DMap.begin(); iter!=points3DMap.end(); ++iter) { UASSERT(mapWords.count(iter->first) == 1); mapPoints[mapWords.find(iter->first)->second] = iter->second; } } } // sort by feature response std::multimap > > > > newIds; UASSERT(lastFrame_->getWords3().size() == lastFrame_->getWords().size()); UDEBUG("new frame words3=%d", (int)lastFrame_->getWords3().size()); std::set seenStatusUpdated; // add points without depth only if the local map has reached its maximum size bool addPointsWithoutDepth = false; if(!visDepthAsMask && validDepthRatio_ < 1.0f && !lastFrame_->getWords3().empty()) { int ptsWithDepth = 0; for (std::vector::const_iterator iter = lastFrame_->getWords3().begin(); iter != lastFrame_->getWords3().end(); ++iter) { if(util3d::isFinite(*iter)) { ++ptsWithDepth; } } float r = float(ptsWithDepth) / float(lastFrame_->getWords3().size()); addPointsWithoutDepth = r > validDepthRatio_; if(!addPointsWithoutDepth) { UWARN("Not enough points with valid depth in current frame (%d/%d=%f < %s=%f), points without depth are not added to map.", ptsWithDepth, (int)lastFrame_->getWords3().size(), r, Parameters::kOdomF2MValidDepthRatio().c_str(), validDepthRatio_); } } if(!lastFrameModels.empty()) { UASSERT(lastFrame_->getWordsKpts().size() == lastFrame_->getWords().size()); for(std::multimap::const_iterator iter = lastFrame_->getWords().begin(); iter!=lastFrame_->getWords().end(); ++iter) { const cv::Point3f & pt = lastFrame_->getWords3()[iter->second]; cv::KeyPoint kpt = lastFrame_->getWordsKpts()[iter->second]; int cameraIndex = 0; if(lastFrameModels.size()>1) { UASSERT(lastFrameModels[0].imageWidth()>0); float subImageWidth = lastFrameModels[0].imageWidth(); cameraIndex = int(kpt.pt.x / subImageWidth); UASSERT(cameraIndex < (int)lastFrameModels.size()); kpt.pt.x = kpt.pt.x - (subImageWidth*float(cameraIndex)); } if(mapWords.find(iter->first) == mapWords.end()) // Point not in map { if(util3d::isFinite(pt) || addPointsWithoutDepth) { newIds.insert( std::make_pair(kpt.response>0?1.0f/kpt.response:0.0f, std::make_pair(iter->first, std::make_pair(kpt, std::make_pair(pt, std::make_pair(lastFrame_->getWordsDescriptors().row(iter->second), cameraIndex)))))); } } else if(bundleAdjustment_>0) { if(lastFrame_->getWords().count(iter->first) == 1) { std::multimap::iterator iterKpts = mapWords.find(iter->first); if(iterKpts!=mapWords.end() && !mapWordsKpts.empty()) { mapWordsKpts[iterKpts->second].octave = kpt.octave; } UASSERT(iterBundlePosesRef!=bundlePoseReferences_.end()); iterBundlePosesRef->second += 1; //move back point in camera frame (to get depth along z) float depth = 0.0f; if(util3d::isFinite(pt)) { depth = util3d::transformPoint(pt, lastFrameModels[cameraIndex].localTransform().inverse()).z; } if(bundleWordReferences_.find(iter->first) == bundleWordReferences_.end()) { std::map framePt; framePt.insert(std::make_pair(lastFrame_->id(), FeatureBA(kpt, depth, cv::Mat(), cameraIndex))); bundleWordReferences_.insert(std::make_pair(iter->first, framePt)); } else { std::map & keyframes = bundleWordReferences_.find(iter->first)->second; if(bundleMaxKeyFramesPerFeature_ != 0 && (int)keyframes.size() > bundleMaxKeyFramesPerFeature_) { // To keep number of keyframes looking at same feature bounded int frameId = keyframes.rbegin()->first; UASSERT(bundlePoseReferences_.find(frameId) != bundlePoseReferences_.end()); bundlePoseReferences_.at(frameId) -= 1; keyframes.erase(frameId); } keyframes.insert(std::make_pair(lastFrame_->id(), FeatureBA(kpt, depth, cv::Mat(), cameraIndex))); } } } } UDEBUG("newIds=%d", (int)newIds.size()); } int lastFrameOldestNewId = lastFrameOldestNewId_; lastFrameOldestNewId_ = lastFrame_->getWords().size()?lastFrame_->getWords().rbegin()->first:0; for(std::multimap > > > >::reverse_iterator iter=newIds.rbegin(); iter!=newIds.rend(); ++iter) { if(maxNewFeatures_ == 0 || added < maxNewFeatures_) { int cameraIndex = iter->second.second.second.second.second; cv::Point3f pt = iter->second.second.second.first; if(!util3d::isFinite(pt)) { // get the ray instead float x = iter->second.second.first.pt.x; //subImageWidth should be already removed float y = iter->second.second.first.pt.y; Eigen::Vector3f ray = util3d::projectDepthTo3DRay( lastFrameModels[cameraIndex].imageSize(), x, y, lastFrameModels[cameraIndex].cx(), lastFrameModels[cameraIndex].cy(), lastFrameModels[cameraIndex].fx(), lastFrameModels[cameraIndex].fy()); float scaleInf = initDepthFactor_ * lastFrameModels[cameraIndex].fx(); pt = util3d::transformPoint(cv::Point3f(ray[0]*scaleInf, ray[1]*scaleInf, ray[2]*scaleInf), lastFrameModels[cameraIndex].localTransform()); // in base_link frame } if(floorThreshold_ != 0.0f && pt.z < floorThreshold_) { continue; } if(bundleAdjustment_>0) { if(lastFrame_->getWords().count(iter->second.first) == 1) { UASSERT(iterBundlePosesRef!=bundlePoseReferences_.end()); iterBundlePosesRef->second += 1; //move back point in camera frame (to get depth along z) float depth = 0.0f; if(util3d::isFinite(iter->second.second.second.first)) { depth = util3d::transformPoint(iter->second.second.second.first, lastFrameModels[cameraIndex].localTransform().inverse()).z; } if(bundleWordReferences_.find(iter->second.first) == bundleWordReferences_.end()) { std::map framePt; framePt.insert(std::make_pair(lastFrame_->id(), FeatureBA(iter->second.second.first, depth, cv::Mat(), cameraIndex))); bundleWordReferences_.insert(std::make_pair(iter->second.first, framePt)); } else { bundleWordReferences_.find(iter->second.first)->second.insert(std::make_pair(lastFrame_->id(), FeatureBA(iter->second.second.first, depth, cv::Mat(), cameraIndex))); } } } mapWords.insert(mapWords.end(), std::make_pair(iter->second.first, mapWords.size())); mapWordsKpts.push_back(iter->second.second.first); mapPoints.push_back(util3d::transformPoint(pt, newFramePose)); mapDescriptors.push_back(iter->second.second.second.second.first); if(lastFrameOldestNewId_ > iter->second.first) { lastFrameOldestNewId_ = iter->second.first; } ++added; } else { break; } } UDEBUG(""); // remove words in map if max size is reached if((int)mapWords.size() > maximumMapSize_) { // remove oldest outliers first std::set inliers(regInfo.inliersIDs.begin(), regInfo.inliersIDs.end()); std::vector ids = regInfo.matchesIDs; if(regInfo.projectedIDs.size()) { ids.resize(ids.size() + regInfo.projectedIDs.size()); int oi=0; for(unsigned int i=0; i=lastFrameOldestNewId) { ids[regInfo.matchesIDs.size()+oi++] = regInfo.projectedIDs[i]; } } ids.resize(regInfo.matchesIDs.size()+oi); UDEBUG("projected added=%d/%d minLastFrameId=%d", oi, (int)regInfo.projectedIDs.size(), lastFrameOldestNewId); } for(unsigned int i=0; i maximumMapSize_ && mapWords.size() >= newIds.size(); ++i) { int id = ids.at(i); if(inliers.find(id) == inliers.end()) { std::map >::iterator iterRef = bundleWordReferences_.find(id); if(iterRef != bundleWordReferences_.end()) { for(std::map::iterator iterFrame = iterRef->second.begin(); iterFrame != iterRef->second.end(); ++iterFrame) { if(bundlePoseReferences_.find(iterFrame->first) != bundlePoseReferences_.end()) { bundlePoseReferences_.at(iterFrame->first) -= 1; } } bundleWordReferences_.erase(iterRef); } mapWords.erase(id); ++removed; } } // remove oldest first for(std::multimap::iterator iter = mapWords.begin(); iter!=mapWords.end() && (int)mapWords.size() > maximumMapSize_ && mapWords.size() >= newIds.size();) { if(inliers.find(iter->first) == inliers.end()) { std::map >::iterator iterRef = bundleWordReferences_.find(iter->first); if(iterRef != bundleWordReferences_.end()) { for(std::map::iterator iterFrame = iterRef->second.begin(); iterFrame != iterRef->second.end(); ++iterFrame) { if(bundlePoseReferences_.find(iterFrame->first) != bundlePoseReferences_.end()) { bundlePoseReferences_.at(iterFrame->first) -= 1; } } bundleWordReferences_.erase(iterRef); } mapWords.erase(iter++); ++removed; } else { ++iter; } } if(mapWords.size() != mapPoints.size()) { UDEBUG("Remove points"); std::vector mapWordsKptsClean(mapWords.size()); std::vector mapPointsClean(mapWords.size()); cv::Mat mapDescriptorsClean(mapWords.size(), mapDescriptors.cols, mapDescriptors.type()); int index = 0; for(std::multimap::iterator iter = mapWords.begin(); iter!=mapWords.end(); ++iter, ++index) { mapWordsKptsClean[index] = mapWordsKpts[iter->second]; mapPointsClean[index] = mapPoints[iter->second]; mapDescriptors.row(iter->second).copyTo(mapDescriptorsClean.row(index)); iter->second = index; } mapWordsKpts = mapWordsKptsClean; mapWordsKptsClean.clear(); mapPoints = mapPointsClean; mapPointsClean.clear(); mapDescriptors = mapDescriptorsClean; } Link * previousLink = 0; for(std::map::iterator iter=bundlePoseReferences_.begin(); iter!=bundlePoseReferences_.end();) { if(iter->second <= 0) { if(previousLink == 0 || bundleLinks_.find(iter->first) != bundleLinks_.end()) { if(previousLink) { UASSERT(previousLink->to() == iter->first); *previousLink = previousLink->merge(bundleLinks_.find(iter->first)->second, previousLink->type()); } UASSERT(bundlePoses_.erase(iter->first) == 1); bundleLinks_.erase(iter->first); bundleModels_.erase(iter->first); bundleIMUOrientations_.erase(iter->first); bundlePoseReferences_.erase(iter++); } } else { previousLink=0; if(bundleLinks_.find(iter->first) != bundleLinks_.end()) { previousLink = &bundleLinks_.find(iter->first)->second; } ++iter; } } } if(added || removed) { modified = true; } UDEBUG("Update local features map = %fs", tmpTimer.ticks()); // Geometric UDEBUG("scankeyframeThr=%f icpInliersRatio=%f", scanKeyFrameThr_, regInfo.icpInliersRatio); UINFO("Update local scan map %d (ratio=%f < %f)", lastFrame_->id(), regInfo.icpInliersRatio, scanKeyFrameThr_); if(lastFrame_->sensorData().laserScanRaw().size()) { pcl::PointCloud::Ptr mapCloudNormals = util3d::laserScanToPointCloudINormal(mapScan, tmpMap.sensorData().laserScanRaw().localTransform()); Transform viewpoint = newFramePose * lastFrame_->sensorData().laserScanRaw().localTransform(); pcl::PointCloud::Ptr frameCloudNormals (new pcl::PointCloud()); if(scanMapMaxRange_ > 0) { frameCloudNormals = util3d::laserScanToPointCloudINormal(lastFrame_->sensorData().laserScanRaw()); frameCloudNormals = util3d::cropBox(frameCloudNormals, Eigen::Vector4f(-scanMapMaxRange_ / 2, -scanMapMaxRange_ / 2,-scanMapMaxRange_ / 2, 0), Eigen::Vector4f(scanMapMaxRange_ / 2,scanMapMaxRange_ / 2,scanMapMaxRange_ / 2, 0) ); frameCloudNormals = util3d::transformPointCloud(frameCloudNormals, viewpoint); } else { frameCloudNormals = util3d::laserScanToPointCloudINormal(lastFrame_->sensorData().laserScanRaw(), viewpoint); } pcl::IndicesPtr frameCloudNormalsIndices(new std::vector); int newPoints; if(mapCloudNormals->size() && scanSubtractRadius_ > 0.0f) { // remove points that overlap (the ones found in both clouds) frameCloudNormalsIndices = util3d::subtractFiltering( frameCloudNormals, pcl::IndicesPtr(new std::vector), mapCloudNormals, pcl::IndicesPtr(new std::vector), scanSubtractRadius_, lastFrame_->sensorData().laserScanRaw().hasNormals()&&mapScan.hasNormals()?scanSubtractAngle_:0.0f); newPoints = frameCloudNormalsIndices->size(); } else { newPoints = frameCloudNormals->size(); } if(newPoints) { if (scanMapMaxRange_ > 0) { // Copying new points to tmp cloud // These are the points that have no overlap between mapScan and lastFrame pcl::PointCloud tmp; pcl::copyPointCloud(*frameCloudNormals, *frameCloudNormalsIndices, tmp); if (int(mapCloudNormals->size() + newPoints) > scanMaximumMapSize_) // 20 000 points { // Print mapSize UINFO("mapSize=%d newPoints=%d maxPoints=%d", int(mapCloudNormals->size()), newPoints, scanMaximumMapSize_); *mapCloudNormals += tmp; cv::Point3f boxMin (-scanMapMaxRange_/2, -scanMapMaxRange_/2, -scanMapMaxRange_/2); cv::Point3f boxMax (scanMapMaxRange_/2, scanMapMaxRange_/2, scanMapMaxRange_/2); boxMin = util3d::transformPoint(boxMin, viewpoint.translation()); boxMax = util3d::transformPoint(boxMax, viewpoint.translation()); mapCloudNormals = util3d::cropBox(mapCloudNormals, Eigen::Vector4f(boxMin.x, boxMin.y, boxMin.z, 0 ), Eigen::Vector4f(boxMax.x, boxMax.y, boxMax.z, 0 )); } else { *mapCloudNormals += tmp; } mapCloudNormals = util3d::voxelize(mapCloudNormals, scanSubtractRadius_); pcl::PointCloud::Ptr mapCloud (new pcl::PointCloud ()); copyPointCloud(*mapCloudNormals, *mapCloud); pcl::PointCloud::Ptr normals = util3d::computeNormals(mapCloud, pointToPlaneK_, pointToPlaneRadius_, Eigen::Vector3f(viewpoint.x(), viewpoint.y(), viewpoint.z())); copyPointCloud(*normals, *mapCloudNormals); } else { scansBuffer_.push_back(std::make_pair(frameCloudNormals, frameCloudNormalsIndices)); //remove points if too big UDEBUG("scansBuffer=%d, mapSize=%d newPoints=%d maxPoints=%d", (int)scansBuffer_.size(), int(mapCloudNormals->size()), newPoints, scanMaximumMapSize_); if(scansBuffer_.size() > 1 && int(mapCloudNormals->size() + newPoints) > scanMaximumMapSize_) { //regenerate the local map mapCloudNormals->clear(); std::list toRemove; int i = int(scansBuffer_.size())-1; for(; i>=0; --i) { int pointsToAdd = scansBuffer_[i].second->size()?scansBuffer_[i].second->size():scansBuffer_[i].first->size(); if((int)mapCloudNormals->size() + pointsToAdd > scanMaximumMapSize_ || i == 0) { *mapCloudNormals += *scansBuffer_[i].first; break; } else { if(scansBuffer_[i].second->size()) { pcl::PointCloud tmp; pcl::copyPointCloud(*scansBuffer_[i].first, *scansBuffer_[i].second, tmp); *mapCloudNormals += tmp; } else { *mapCloudNormals += *scansBuffer_[i].first; } } } // remove old clouds if(i > 0) { std::vector::Ptr, pcl::IndicesPtr> > scansTmp(scansBuffer_.size()-i); int oi = 0; for(; i<(int)scansBuffer_.size(); ++i) { UASSERT(oi < (int)scansTmp.size()); scansTmp[oi++] = scansBuffer_[i]; } scansBuffer_ = scansTmp; } } else { // just append the last cloud if(scansBuffer_.back().second->size()) { pcl::PointCloud tmp; pcl::copyPointCloud(*scansBuffer_.back().first, *scansBuffer_.back().second, tmp); *mapCloudNormals += tmp; } else { *mapCloudNormals += *scansBuffer_.back().first; } } } if(mapScan.is2d()) { Transform mapViewpoint(-newFramePose.x(), -newFramePose.y(),0,0,0,0); mapScan = LaserScan(util3d::laserScan2dFromPointCloud(*mapCloudNormals, mapViewpoint), 0, 0.0f); } else { Transform mapViewpoint(-newFramePose.x(), -newFramePose.y(), -newFramePose.z(),0,0,0); mapScan = LaserScan(util3d::laserScanFromPointCloud(*mapCloudNormals, mapViewpoint), 0, 0.0f); } modified=true; } } UDEBUG("Update local scan map = %fs", tmpTimer.ticks()); } if(modified) { *map_ = tmpMap; if(mapScan.is2d()) { map_->sensorData().setLaserScan( LaserScan( mapScan.data(), 0, 0.0f, mapScan.format(), Transform(newFramePose.x(), newFramePose.y(), lastFrame_->sensorData().laserScanRaw().localTransform().z(),0,0,0))); } else { map_->sensorData().setLaserScan( LaserScan( mapScan.data(), 0, 0.0f, mapScan.format(), newFramePose.translation())); } map_->setWords(mapWords, mapWordsKpts, mapPoints, mapDescriptors); } if(lastFrameWords3Updated) { // update output with refined 3d points from bundle adjustment data.setFeatures(lastFrame_->getWordsKpts(), lastFrameWords3, lastFrame_->getWordsDescriptors()); } } if(info) { // use tmpMap instead of map_ to make sure that correspondences with the new frame matches info->localMapSize = (int)tmpMap.getWords3().size(); info->localScanMapSize = tmpMap.sensorData().laserScanRaw().size(); if(this->isInfoDataFilled()) { info->localMap.clear(); if(!tmpMap.getWords3().empty()) { for(std::multimap::const_iterator iter=tmpMap.getWords().begin(); iter!=tmpMap.getWords().end(); ++iter) { info->localMap.insert(std::make_pair(iter->first, tmpMap.getWords3()[iter->second])); } } info->localScanMap = tmpMap.sensorData().laserScanRaw(); } } } else { // Just generate keypoints for the new signature // For scan, we want to use reading filters, so set dummy's scan and set back to reference afterwards Signature dummy; dummy.sensorData().setLaserScan(lastFrame_->sensorData().laserScanRaw()); lastFrame_->sensorData().setLaserScan(LaserScan()); regPipeline_->computeTransformationMod( *lastFrame_, dummy); lastFrame_->sensorData().setLaserScan(dummy.sensorData().laserScanRaw()); data.setFeatures(lastFrame_->sensorData().keypoints(), lastFrame_->sensorData().keypoints3D(), lastFrame_->sensorData().descriptors()); data.setLaserScan(lastFrame_->sensorData().laserScanRaw()); // a very high variance tells that the new pose is not linked with the previous one regInfo.covariance = cv::Mat::eye(6,6,CV_64FC1)*9999.0; bool frameValid = false; Transform newFramePose = this->getPose(); // initial pose may be not identity... if(regPipeline_->isImageRequired()) { int ptsWithDepth = 0; for (std::multimap::const_iterator iter = lastFrame_->getWords().begin(); iter != lastFrame_->getWords().end(); ++iter) { if(!lastFrame_->getWords3().empty() && util3d::isFinite(lastFrame_->getWords3()[iter->second])) { ++ptsWithDepth; } } if (ptsWithDepth >= regPipeline_->getMinVisualCorrespondences()) { frameValid = true; // update local map UASSERT_MSG(lastFrame_->getWordsDescriptors().rows == (int)lastFrame_->getWords3().size(), uFormat("%d vs %d", lastFrame_->getWordsDescriptors().rows, (int)lastFrame_->getWords3().size()).c_str()); UASSERT(lastFrame_->getWords3().size() == lastFrame_->getWords().size()); std::multimap words; std::vector wordsKpts; std::vector transformedPoints; std::multimap mapPointWeights; cv::Mat descriptors; if(!lastFrame_->getWords3().empty() && !lastFrameModels.empty()) { for (std::multimap::const_iterator iter = lastFrame_->getWords().begin(); iter != lastFrame_->getWords().end(); ++iter) { const cv::Point3f & pt = lastFrame_->getWords3()[iter->second]; if (util3d::isFinite(pt)) { words.insert(words.end(), std::make_pair(iter->first, words.size())); wordsKpts.push_back(lastFrame_->getWordsKpts()[iter->second]); transformedPoints.push_back(util3d::transformPoint(pt, newFramePose)); mapPointWeights.insert(std::make_pair(iter->first, 0)); descriptors.push_back(lastFrame_->getWordsDescriptors().row(iter->second)); } } } if(bundleAdjustment_>0) { // update bundleWordReferences_: used for bundle adjustment if(!wordsKpts.empty()) { for(std::multimap::const_iterator iter=words.begin(); iter!=words.end(); ++iter) { if(words.count(iter->first) == 1) { UASSERT(bundleWordReferences_.find(iter->first) == bundleWordReferences_.end()); std::map framePt; cv::KeyPoint kpt = wordsKpts[iter->second]; int cameraIndex = 0; if(lastFrameModels.size()>1) { UASSERT(lastFrameModels[0].imageWidth()>0); float subImageWidth = lastFrameModels[0].imageWidth(); cameraIndex = int(kpt.pt.x / subImageWidth); kpt.pt.x = kpt.pt.x - (subImageWidth*float(cameraIndex)); } //get depth float d = 0.0f; if(lastFrame_->getWords().count(iter->first) == 1 && !lastFrame_->getWords3().empty() && util3d::isFinite(lastFrame_->getWords3()[lastFrame_->getWords().find(iter->first)->second])) { //move back point in camera frame (to get depth along z) d = util3d::transformPoint(lastFrame_->getWords3()[lastFrame_->getWords().find(iter->first)->second], lastFrameModels[cameraIndex].localTransform().inverse()).z; } framePt.insert(std::make_pair(lastFrame_->id(), FeatureBA(kpt, d, cv::Mat(), cameraIndex))); bundleWordReferences_.insert(std::make_pair(iter->first, framePt)); } } } bundlePoseReferences_.insert(std::make_pair(lastFrame_->id(), (int)bundleWordReferences_.size())); bundleModels_.insert(std::make_pair(lastFrame_->id(), lastFrameModels)); bundlePoses_.insert(std::make_pair(lastFrame_->id(), newFramePose)); if(!imuT.isNull()) { bundleIMUOrientations_.insert(std::make_pair(lastFrame_->id(), Link(lastFrame_->id(), lastFrame_->id(), Link::kGravity, newFramePose))); } } map_->setWords(words, wordsKpts, transformedPoints, descriptors); addKeyFrame = true; } else { UWARN("%d visual features required to initialize the odometry (only %d extracted).", regPipeline_->getMinVisualCorrespondences(), (int)lastFrame_->getWords3().size()); } } if(regPipeline_->isScanRequired()) { if (lastFrame_->sensorData().laserScanRaw().size()) { pcl::PointCloud::Ptr mapCloudNormals = util3d::laserScanToPointCloudINormal(lastFrame_->sensorData().laserScanRaw(), newFramePose * lastFrame_->sensorData().laserScanRaw().localTransform()); double complexity = 0.0;; if(!frameValid) { float minComplexity = Parameters::defaultIcpPointToPlaneMinComplexity(); bool p2n = Parameters::defaultIcpPointToPlane(); Parameters::parse(parameters_, Parameters::kIcpPointToPlane(), p2n); Parameters::parse(parameters_, Parameters::kIcpPointToPlaneMinComplexity(), minComplexity); if(p2n && minComplexity>0.0f) { if(lastFrame_->sensorData().laserScanRaw().hasNormals()) { complexity = util3d::computeNormalsComplexity(*mapCloudNormals, Transform::getIdentity(), lastFrame_->sensorData().laserScanRaw().is2d()); if(complexity > minComplexity) { frameValid = true; } else if(!guess.isNull() && !guess.isIdentity()) { UWARN("Scan complexity too low (%f) to init robustly the first " "keyframe. Make sure the lidar is seeing enough " "geometry in all axes for good initialization. " "Accepting as an initial guess (%s) is provided.", complexity, guess.prettyPrint().c_str()); frameValid = true; } } else { UWARN("Input raw scan doesn't have normals, complexity check on first frame is not done."); frameValid = true; } } else { frameValid = true; } } const int scanMaxPoints = lastFrame_->sensorData().laserScanRaw().maxPoints(); if(frameValid && scanMaxPoints > 0) { float correspondenceRatio = Parameters::defaultIcpCorrespondenceRatio(); Parameters::parse(parameters_, Parameters::kIcpCorrespondenceRatio(), correspondenceRatio); if(float(lastFrame_->sensorData().laserScanRaw().size()) < float(scanMaxPoints) * correspondenceRatio) { UWARN("Scan has %d points of the %d of a full sweep, under the %s=%f " "that a registration against it would have to reach, so no " "later scan could be matched to it. Not initializing on it.", (int)lastFrame_->sensorData().laserScanRaw().size(), scanMaxPoints, Parameters::kIcpCorrespondenceRatio().c_str(), correspondenceRatio); frameValid = false; } } if(frameValid) { if (scanMapMaxRange_ > 0 ){ UINFO("Local map will be updated using range instead of time with range threshold set at %f", scanMapMaxRange_); } else { scansBuffer_.push_back(std::make_pair(mapCloudNormals, pcl::IndicesPtr(new std::vector))); } if(lastFrame_->sensorData().laserScanRaw().is2d()) { Transform mapViewpoint(-newFramePose.x(), -newFramePose.y(),0,0,0,0); map_->sensorData().setLaserScan( LaserScan( util3d::laserScan2dFromPointCloud(*mapCloudNormals, mapViewpoint), 0, 0.0f, Transform(newFramePose.x(), newFramePose.y(), lastFrame_->sensorData().laserScanRaw().localTransform().z(),0,0,0))); } else { Transform mapViewpoint(-newFramePose.x(), -newFramePose.y(), -newFramePose.z(),0,0,0); map_->sensorData().setLaserScan( LaserScan( util3d::laserScanFromPointCloud(*mapCloudNormals, mapViewpoint), 0, 0.0f, newFramePose.translation())); } addKeyFrame = true; } else { UWARN("Scan complexity too low (%f) to init first keyframe.", complexity); } } else { UWARN("Missing scan to initialize odometry."); } } if (frameValid) { // We initialized the local map output.setIdentity(); } if(info) { info->localMapSize = (int)map_->getWords3().size(); info->localScanMapSize = map_->sensorData().laserScanRaw().size(); if(this->isInfoDataFilled()) { info->localMap.clear(); if(!map_->getWords3().empty()) { for(std::multimap::const_iterator iter=map_->getWords().begin(); iter!=map_->getWords().end(); ++iter) { info->localMap.insert(std::make_pair(iter->first, map_->getWords3()[iter->second])); } } info->localScanMap = map_->sensorData().laserScanRaw(); } } } map_->sensorData().setFeatures(std::vector(), std::vector(), cv::Mat()); // clear sensorData features nFeatures = lastFrame_->getWords().size(); if(this->isInfoDataFilled() && info) { if(regPipeline_->isImageRequired()) { info->words.clear(); if(!lastFrame_->getWordsKpts().empty()) { for(std::multimap::const_iterator iter=lastFrame_->getWords().begin(); iter!=lastFrame_->getWords().end(); ++iter) { info->words.insert(std::make_pair(iter->first, lastFrame_->getWordsKpts()[iter->second])); } } } } } else { UERROR("SensorData not valid!"); } if(info) { info->features = nFeatures; info->localKeyFrames = (int)bundlePoses_.size(); info->keyFrameAdded = addKeyFrame; info->localBundleOutliers = totalBundleOutliers; info->localBundleConstraints = totalBundleWordReferencesUsed; info->localBundleTime = bundleTime; if(this->isInfoDataFilled()) { info->reg = regInfo; } else { info->reg = regInfo.copyWithoutData(); } if(output.isNull()) { info->reg.covariance = cv::Mat::eye(6,6,CV_64FC1)*9999.0; // Lost } } UINFO("Odom update time = %fs lost=%s features=%d inliers=%d/%d variance:lin=%f, ang=%f local_map=%d local_scan_map=%d", timer.elapsed(), output.isNull()?"true":"false", nFeatures, regInfo.inliers, regInfo.matches, !regInfo.covariance.empty()?regInfo.covariance.at(0,0):0, !regInfo.covariance.empty()?regInfo.covariance.at(5,5):0, regPipeline_->isImageRequired()?(int)map_->getWords3().size():0, regPipeline_->isScanRequired()?(int)map_->sensorData().laserScanRaw().size():0); return output; } } // namespace rtabmap