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2-D and 3-D occupancy maps, egocentric maps, raycasting

Occupancy maps are used to represent obstacles in an environment and define limits of your world. You can build maps and update obstacle locations from sensor readings using raycasting. Sync with existing maps and move local frames to create egocentric maps that follow your vehicle. Maps support binary and probabilistic values for 2-D maps and a probabilistic representation for 3-D maps.

Use these maps along with Motion Planning to plan paths in a map, or use Localization and Pose Estimation algorithms to estimate your vehicle pose in an environment.


binaryOccupancyMapCreate occupancy grid with binary values
occupancyMapCreate occupancy map with probabilistic values
occupancyMap3D Create 3-D occupancy map
mapLayerCreate map layer for N-dimensional data
multiLayerMapManage multiple map layers


buildMapBuild occupancy map from lidar scans
checkOccupancyCheck locations for free, occupied, or unknown values
exportOccupancyMap3DImport an octree file as 3D occupancy map
getOccupancyGet occupancy value of locations
getMapDataRetrieve data from map layer
importOccupancyMap3DImport an octree file as 3D occupancy map
inflateInflate each occupied grid location
insertRayInsert ray from laser scan observation
insertPointCloudInsert 3-D points or point cloud observation into map
mapClutterGenerate map with randomly scattered obstacles
mapMazeGenerate random 2-D maze map
moveMove map in world frame
occupancyMatrixConvert occupancy grid to double matrix
raycastCompute cell indices along a ray
rayIntersectionFind intersection points of rays and occupied map cells
setOccupancySet occupancy value of locations
setMapDataAssign data to map layer
syncWithSync map with overlapping map
showShow grid values in a figure
updateOccupancyIntegrate probability observations at locations