An Improved Simulated Annealing-Artificial Potential Field Path Planning Algorithm
Lei Qian, Zhi Lü, Xu Jun, Dong Yang, Min Xie, Dian Wu · 2024
In response to the issue of local minimum problems in artificial potential field algorithms based on simulated annealing, a random escape force is introduced, and an improved SA-APF (Simulated Annealing-Artificial Potential Field) algorithm is proposed, which allows the robot to quickly escape from local optimal solutions. To address the issue of still-existing target inaccessibility in the algorithm, an adaptive repulsion field gain coefficient is proposed based on the fuzzy control method, enabling the robot to reach the target point when encountering obstacles symmetrically arranged near the target point. The path is made smoother by fitting with a 4th-order Bezier curve. Simulation results show that under both simple and complex obstacle experimental conditions, the improved algorithm can accurately and efficiently complete path planning.