Rapid Physics-Based Rough-Terrain Rover Planning with Sensor and Control Uncertainty

In future planetary exploration missions, rovers will be required to autonomously traverse challenging environments. Much of the previous work in robot motion planning cannot be successfully applied to the rough-terrain planning problem. A model-based planning method is presented in this paper that is computationally efficient and takes into account uncertainty in the robot model, terrain model, range sensor data, and rover pathfollowing errors. It is based on rapid path planning through the visible terrain map with a simple graph-search algorithm, followed by a physics-based evaluation of the path with a rover model. Simulation results are presented which demonstrate the method’s effectiveness.