Path Planning Considering Motion Uncertainty for Exploration Robots in Natural Terrain
Michihiro Mizuno, Takashi Kubota · Journal of the Robotics Society of Japan · 2019
This paper proposes a new path planning architecture with consideration of motion uncertainty for wheeled robots in rough terrain with multiple types of terrain. The proposed scheme uses particles to describe the uncertainty propagation between different terrain types and to expand RRT (Rapidly-exploring Random Tree) based on the uncertainty of each node in order to prevent the expansion of position uncertainty. The effectiveness of the proposed method is evaluated on the simulation which hypothesizes Mars enviroment. The simulation results show that the proposed method can prevent the expansion of position uncertainty substantially, which can decrease the times of path following or re-planning.