A Three-Dimensional Path Planning Method of Autonomous Burrowing Robot for Lunar Subsurface Exploration

The subsurface exploration with autonomous burrowing robot might be a low-cost and high-efficient solution for a future extraterrestrial mission on the Moon. To enable a locomotive mechanism drilling into an uncertain lunar formation composed of soils and rocks, the design of trajectory planning scheme is a very challenging task. In this work, a trajectory planning method in a three-dimensional (3-D) geological domain with distributed obstacles is proposed. An improved pruning version of Rapid-exploration Random Tree algorithm was first developed, then a set of candidate paths was generated. By introducing the evaluation functions, the optimal path was selected among a group of recommended paths. At last, Bezier parametric curve was utilized to enhance the smoothness of robotic trajectory. The method was examined and discussed through numerical experiments. The simulation results show that this method may adapt to a variety of underground environments and different task requirements. Overall, the proposed method provides a powerful multi-objective optimization strategy to operate an autonomous burrowing robot in lunar subsurface. It can be further generalized to consider more factors in an intelligent decision-making manner.