Construction of Semantic Maps for Personal Mobility Robots in Dynamic Outdoor Environments

In this paper, a construction system of outdoor semantic maps by personal mobility robots that move in dynamic outdoor environments is proposed. The maps have topological forms based on understanding of road structures. That is, the nodes of maps are intersections, and arcs are roads between each pair of intersections. Topological framework significantly reduces computer resources, and enables consistent map building in environments which include loops. Trajectories of moving objects, landmarks, entrances of buildings, and traffic signs are added along each road. This framework enables personal mobility robots to recognize dangerous points or regions. The proposed system uses two laser range finders (LRFs) and one omni-directional camera. One LRF is swung by a tilt unit, and reconstruct 3D shapes of obstacles and the ground. The other LRF is fixed on the body of the robot, and is used for moving objects detection and tracking. The camera is used for localization and loop closings. We implemented the proposed system in a personal mobility robot, and demonstrated its effectiveness in outdoor environments.