Modified artificial potential field method for online path planning applications

Abstract

This paper presents a modified potential field method for mobile robots and intelligent vehicles local navigation. The approach overcomes the well-known artificial potential field (APF) method issue, which is due to local minima that induce the standard APF method to trap in. Thus, the standard APF method is no longer useful in such cases. The advantage of the new proposed method, as opposed to those that resort to the global optimization methods, is the low computing time that lines up with the standardA-Star (A∗) method. The strategy consists of looking for a practical path in the potential field-according to the potential gradient descent algorithm (PGDA) — and adding a repulsive potential to the current state, in case of blocking configuration, a local minimum. When the PGDA reaches the global minimum, a new potential field will be constructed with only one minimum that matches the final destination of the robot, the global minimum. Finally, to determine the achievable trajectory, a second iteration is performed by the PGDA.