Towards efficient path planning of a mobile robot on rough terrain

Most path planning methods for mobile robots divide the environment in two areas - free and occupied - and restrict the path to lie entirely within the free space. However, the problem of path planning in rough terrain for a field robot, e.g. tracked wheel, is still a challenging problem, for which those methods cannot be directly applied. This paper addresses the problem of path planning on rough terrains, where the local properties of the environment are used to both constrain and optimize the resulting path. Finding both the feasibility and the cost of the robot crossing the terrain at a given point is cast as an optimization problem. Intuitively, this problem models dropping the robot at a given location and determining the minimal potential energy attitude. Then, a Fast Marching Method algorithm is used to obtain a potential field free of local minima. This field is then used to either pre-compute a complete trajectory or to control in real time the locomotion of the robot. Preliminary results are presented, showing feasible paths over an elevation map of a rough terrain.