Global Path Planning for Mobile Robot Based on Improved Artificial Potential Function

There is a major problem with traditional artificial potential field method. It is the formation of local minima that can trap the robot before reaching its goal. To overcome the problem, this paper presents an improved potential field approach. It consists of two parts. The former, the improved attractive potential function, brings the minimum distance between the robot and the obstacle into consideration, and the latter, the improved repulsive potential function, includes the relative position between the robot and the target. These ensure the target is the global minimum of the artificial potential function. The simulation experiment is made under the VC++ 6.0 environment. Experimental results show that the improved approach has much higher capacity of global optimization than traditional method.