Path planning in dynamic environment for a rover using A∗ and potential field method

This paper proposes a path planning method for a wheeled mobile robot operating in rough terrain dynamic environments using a combination of A∗ search algorithm and potential field method. In this method, the mobile robot uses the structured light system to extract real terrain data as a discrete points to generate a b-spline surface. The terrain is classified based on the slope and elevation using a fuzzy logic controller and a user defined cost function is generated. A combination of A∗ and potential field method has been introduced to find the path from the start location to goal location according to the cost function. The A∗ algorithm determines the path that globally optimizes terrain roughness, curvature and length of the path, and the potential field method has been used as a local planner which performs an on-line planning to avoid the newly detected obstacles by the sensory information. The developed potential function is found to be able to avoid local minima in the work space. The results shows the effectiveness of the proposed algorithm.