Efficient Motion Planning for Mobile Robots Dealing with Changes in Rough Terrain

Abstract This paper proposes a novel motion planning method that can deal with changes in rough terrain efficiently. Previous studies on motion planning in rough terrain did not consider significant changes in the environment. To solve this problem, we propose an efficient re-planning method. The re-planning method is characterized by using search tree repeatedly as long as it is still valid. Reusing search tree enables limiting the re-planning region, which leads to the shorter planning time. After re-planning, the re-planned path is deformed to shorten the length of the path. Experimental results show that the proposed method can generate a collision-free path against a significant environmental change and perform the re-planning within a short time.