Improved Artificial Potential Field Method Fused with Fuzzy Logic Algorithm

Abstract

The APF (artificial potential field, APF) has been applied to the path planner of mobile robots by many technology developers and engineers because of its simple structure, small amount of calculation, good obstacle avoidance effect. However, in complex environments, the robot using this algorithm will have target inaccessibility and local minimum. In this article, the Euclidean distance between the mobile robot and the target point is multiplied by the gain coefficient of the potential field function as a regulating factor, which is used to optimize the repulsive potential field function to avoid the situation that the repulsive force is greater than the attractive force near the target point and the target is unreachable. Furthermore, APF was coupled with fuzzy logic algorithm based on fuzzy logic algorithm (Improved Artificial Potential Field Method Fused with Fuzzy Logic Algorithm, FUZZY_APF). This method helps a mobile robot trapped in a local minimum to set a virtual target point nearby, providing it with an escape force to make the local minimum disappear. The FUZZY_APF proposed in this article will be simulated and tested by MATLAB software. The simulation results show that FUZZY_APF can help mobile robots that encounter local minima and unreachable goals in complex environments to complete path planning tasks. Compared with the algorithm without improvement, the path planned by the FUZZY_APF is smoother, and the planning time and the planning path are shorter.