A multi-strategy path planner based on space accessibility

The problem of planning a path in the real complex environment remains a difficult challenge although path planning has been studied extensively in the context of autonomous indoor mobile robots. One of the main reasons is lacking semantic information of the robot's working space. In this paper, we introduce the notion of space accessibility into path planning research. Semantic mapping is utilized to identify and recognize room and hallway on an occupancy grid map. A region topological map is built based on physical connection relation between regions and the types of regions. A multi-strategy path planning combining grid and region topological maps is developed. Paths in hallways will be selected preferentially and different planning methods are used for creating paths in different kinds of regions. Experimental evaluation is conducted on dozens of test maps with indoor layouts. Compared with paths produced by other techniques, the paths generated by our method are more like human beings decisions.