Research on Mobile Robot Path Planning Based on Artificial Potential Field and the Optimization of Artificial Potential Field

摘要

Mobile robots play a significant role in enhancing the convenience of human life. Among the key research areas in mobile robotics, path planning is a central issue. Artificial Potential Field (APF), as a classic path planning algorithm, has received considerable attention. This paper introduces the principles and applications of path planning based on APF method. To address the issue of local minima, it analyzes existing approaches, including collision risk assessment and virtual target point methods. Furthermore, to tackle the problem of non-shortest path, the integration of APF with A-star algorithm, as proposed in the literature, is explored. Simulation experiments demonstrate that both improved methods achieve excellent results. This paper proposes an innovative improvement termed the "Contour Tracing Mode." Based on collision risk assessment, the contour tracing mode is introduced to avoid local minima. Additionally, a novel "Deviation Detection Formula" is proposed to determine whether the robot deviates from the original planned path. When deviation is detected, the integrated algorithm is reactivated to plan the shortest path. Finally, the paper discusses potential future developments of APF, providing references for further research.