Robust Path Planning for Slope Traversing Under Uncertainty in Slip Prediction

Abstract

This letter addresses the path planning problem for a rover on deformable, sloped terrains. As such terrains induce high slip and possible immobilization of rovers, finding a path that avoids critical slip is important for traversing the terrains. However, it is difficult to predict rover slippage precisely, especially on steep slopes, and a certain level of prediction uncertainty is inevitable. Although several path planning algorithms that consider rover slippage have been proposed thus far, they do not consider the uncertainty in slip prediction. This letter proposes a robust path planning algorithm that finds a safe and efficient path based on a chance-constrained planning approach. The proposed algorithm probabilistically guarantees safety against immobilization, with the safety level specified by user-definable parameters. The simulation results demonstrate the effectiveness and flexibility of the proposed algorithm.