JOURNAL ARTICLE

Research on path planning based on improved artificial potential field method

Chun-li XieTao TianyiJiahao Li

Year: 2024 Journal:   Scientific insights and discoveries review Vol: 3 Pages: 95-103

Abstract

Aiming at the unreachable target and local minimum problems existing in the traditional artificial potential field method in the path planning of mobile robots, an improved artificial potential field method is proposed. Firstly, when there are obstacles near the target point, the robot is difficult to reach the target point due to the large repulsive force. A safety distance factor is introduced in the potential field, and the parameter is optimized, so that the robot can maintain a suitable distance from the obstacle and reach the target point smoothly. Secondly, in order to solve the local minimum problem, the local minimum judgment condition is introduced, and when the condition is triggered, the local minimum area is bypassed, so that the robot can reach the target point smoothly. The simulation results show that the improved algorithm runs in the environment of different numbers of obstacles and has strong robustness. The proposed algorithm can enable the robot to bypass the local minimum area in the U-shaped obstacle environment, and successfully solves the local minimum problem in the path planning of mobile robots.

Keywords:
Potential field Field (mathematics) Computer science Path (computing) Artificial intelligence Motion planning Mathematics Geology Robot Geophysics Computer network

Metrics

4
Cited By
2.12
FWCI (Field Weighted Citation Impact)
11
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Control and Dynamics of Mobile Robots
Physical Sciences →  Engineering →  Control and Systems Engineering

Related Documents

JOURNAL ARTICLE

Path Planning Based on Improved Artificial Potential Field Method

Feifan XuHuailin ZhaoZhen NieXin ZhouZheheng Tao

Journal:   Proceedings of International Conference on Artificial Life and Robotics Year: 2020 Vol: 25 Pages: 592-598
JOURNAL ARTICLE

AGV Path Planning Based on Improved Artificial Potential Field Method

Zheyi ChenBing Xu

Journal:   2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA) Year: 2021 Pages: 32-37
© 2026 ScienceGate Book Chapters — All rights reserved.