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2-D and 3-D simultaneous localization and mapping

Simultaneous localization and mapping (SLAM) uses both Mapping and Localization and Pose Estimation algorithms to build a map and localize your vehicle in that map at the same time. Use lidarSLAM to tune your own SLAM algorithm that processes lidar scans and odometry pose estimates to iteratively build a map. Use buildMap to take logged and filtered data to create a map using SLAM. The SLAM Map Builder app lets you manually modify relative poses and align scans to improve the accuracy of your map.


SLAM Map BuilderBuild 2-D grid maps using lidar-based SLAM


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ekfSLAMPerform simultaneous localization and mapping using extended Kalman filter
correctCorrect state and state error covariance
landmarkInfoRetrieve landmark information
poseHistoryRetrieve corrected and predicted pose history
predictPredict state and state error covariance
removeLandmarkRemove landmark from state vector
resetReset state and state estimation error covariance
lidarSLAM Perform localization and mapping using lidar scans
addScanAdd scan to lidar SLAM map
buildMapBuild occupancy map from lidar scans
removeLoopClosures Remove loop closures from pose graph
scansAndPoses Extract scans and corresponding poses
showPlot scans and robot poses