Optimal and Risk-Aware Path Planning considering Localization Uncertainty for Space Exploration Rovers

Abstract

The reliability of autonomous traverses of rovers is critical. It may be jeopardized by the accumulation of errors and the uncertainty propagation of their localization systems. Moreover, space environments are usually harsh, challenging and unpredictable. Teleoperation is complex due to the significant and unavoidable delay. For these reasons, a path planner that provides some level of autonomy with guarantees could increase the success rate of planetary exploration missions. This paper proposes a path planning solution that tackles increasing localization uncertainty and makes a trade-off between the collision risk and the path length. The planner uses the the Fast Marching Method (FMM) to produce a costmap aware of this uncertainty and calculate the optimal path for a level of confidence. This paper additionally presents several simulation and experimental using a wheeled robotic vehicle within a lunar analogue facility.