Planetary Rover Path Planning Based On Improved A* Algorithm

Developing a space rover with ability to explore robustly and autonomously the unknown outer space landscape like Moon and Mars has always been a major challenge, since the first roving remote-controlled robot, Lunokhod 1, landed on the moon. Path planning is one of important task when the rover travels a certain distance without the human control. To traverse safely on the harsh and complex planetary surface, the terrain environmental information and the ability of the roving vehicle to overcome obstacles should be taken into account. In this paper, an improved A* algorithm is proposed via introducing both the environmental characteristics (such as surface slope and surface toughness) and the rover's traversability as the constraint conditions. Comparison of the performance of the proposed A* algorithm relative to the original A* algorithm is conducted based on MATLAB platform. Numerical simulations indicate that the improved A* algorithm has shorter path and higher planning success rate.