A dynamic bridge builder to identify difficult regions for path planning in changing environments

TLDR: An efficient path planner to identify difficult regions for path planning in changing environments, in which obstacles can move randomly, is presented based on a W-C nodes mapping and a Bridge planner method.

Abstract: This paper presents an efficient path planner to identify difficult regions for path planning in changing environments, in which obstacles can move randomly. The difficult regions consist of narrow passages and the boundaries of obstacles in robot Configuration Space (C-space). These regions exert significantly negative influence on finding a valid path in static environments. The problem becomes more complicated in changing environments, because that the regions will change their positions when obstacles move. Besides, it is necessary to identify difficult regions in real time since obstacles may move frequently. To identify difficult regions fast when they change their positions, a dynamic bridge builder is proposed based on a W-C nodes mapping and a Bridge planner method. The W-C nodes mapping is used not only to conserve the validity of nodes in C-space, but also to provide the information about where a "bridge" should be built, i.e. the positions of narrow passages, and where the boundaries of obstacles are. Furthermore, a hierarchy sampling strategy is employed to boost the density of nodes in difficult regions efficiently. In the query phase, a Lazy-edges evaluation method is adopted to validate the edges in a found path. Simulated experiments for a dual-manipulator system show that our method is efficient for path planning in changing environments.