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A solution to room-by-room coverage for autonomous cleaning robots

Alexander Kleiner, Rodrigo Baravalle, Andreas Kolling, Pablo Pilotti, Mario E. Munich

Year
2017
Citations
29

Abstract

We introduce RoomsSeg, a novel method for segmenting occupancy grid maps into regions that represent rooms and corridors in the real world. The segmentation is utilized for systematic room-by-room cleaning on autonomous vacuum cleaners running in private homes. RoomsSeg is based on automated clutter removal and watershed segmentation on grid maps. Segmented regions are merged into rooms by semantic decision rules. Presented experimental results clearly indicate the efficiency and accuracy of the approach when compared with state of the art methods. When deployed on cleaning robots, a substantial decrease in mission time can be achieved.

Keywords

RobotClutterComputer scienceSegmentationGridOccupancy grid mappingComputer visionArtificial intelligenceMobile robotGeography

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