Build Occupancy Map from Lidar Scans and Poses
Load scan and pose estimates collected from sensors on a robot in a parking garage. The data collected is correlated using a
lidarSLAM algorithm, which performs scan matching to associate scans and adjust poses over the full robot trajectory. Check to make sure scans and poses are the same length.
load scansAndPoses.mat length(scans) == length(poses)
ans = logical 1
Build the map. Specify the scans and poses in the
buildMap function and include the desired map resolution (10 cells per meter) and the max range of the lidar (19.2 meters). Each scan is added at the associated poses and probability values in the occupancy grid are updated.
occMap = buildMap(scans,poses,10,19.2); figure show(occMap) title('Occupancy Map of Garage')