Tested in several real-world publicly-available cluttered maps obtained inĭifferent conditions. Segment, i.e., to identify rooms in, the original occupancy grid map. Geometrical floor-plan-like description of the environment, which is used to To clutter and partial observations, allowing to extract a clean, abstract ROSE^2 identifies the main directions of walls and is resilient We propose a method for the RObust StructurE identificationĪnd ROom SEgmentation (ROSE^2 ) of 2D occupancy maps, which may be clutteredĪnd incomplete. Problem due to clutter (e.g., furniture and movable object), occlusions, and Of structure and room segmentation from 2D occupancy maps is still an open These robots often rely on 2D occupancy maps for core tasks suchĪs localisation and motion and task planning. Operation of indoor autonomous mobile robots, including semantic environment Rooms and walls, can facilitate several tasks fundamental for the successful Download a PDF of the paper titled Robust Structure Identification and Room Segmentation of Cluttered Indoor Environments from Occupancy Grid Maps, by Matteo Luperto and 4 other authors Download PDF Abstract: Identifying the environment's structure, i.e., to detect core components as
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