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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.


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binaryOccupancyMapCreate occupancy grid with binary values
occupancyMapCreate 2-D occupancy map (Since R2019b)
mapClutterGenerate map with randomly scattered obstacles (Since R2020b)
mapMazeGenerate random 2-D maze map (Since R2021a)
buildMapBuild occupancy map from lidar scans (Since R2019b)
occupancyMap3D Create 3-D occupancy map (Since R2019b)
exportOccupancyMap3DExport 3-D occupancy map as octree or binary tree file (Since R2020a)
importOccupancyMap3DImport octree or binary tree file as 3-D occupancy map (Since R2020a)
occupancyMap3DCollisionOptionsCollision-checking options between 3-D occupancy map and collision geometries (Since R2022b)
mapLayerCreate map layer for N-dimensional data (Since R2021a)
multiLayerMapManage multiple map layers (Since R2021a)
signedDistanceMapDiscrete signed distance map of 2-D region (Since R2023a)
meshtsdfTruncated signed distance field for 3-D regions containing meshes (Since R2024a)