A Path Planning Algorithm Based on Improved RRT for Lunar Subsurface Autonomous Burrowing Robot

The detection with autonomous burrowing robot might be a low-cost and high-efficient solution for a future lunar subsurface exploration mission. The path planning of underground locomotive robot in a three-dimensional (3-D) domain is a very challenging task under the circumstance of lunar subsurface segregated by lunar rocks. In this work, a pruning-improved RRT algorithm was proposed to generate robotic paths in a 3-D geological model: a confined cubic zone with distributed obstacles. This digital terrain model may be constructed based on the mapping technology of Lunar Penetrating Radar (LPR). Here, a numerical simulation scheme was adapted for a simplicity. The effects of iteration scheme of path finding and distribution of geological structures were discussed. Then, Bezier parametric curve was utilized to enhanced the smoothness of robotic trajectory. After a comprehensive study, the proposed algorithm was proven to outperform the original RRT method in both effectiveness and convergence.