Home /Research /Local path planning for multi-robot sytems based on improved artificial potential field algorithm
SWARM

Local path planning for multi-robot sytems based on improved artificial potential field algorithm

Qiang Liu, Jia Liu, Zhao Ya, Rui Shen, Linlin Hou, Yunxi Zhang

Year
2022
Citations
8

Abstract

In this paper, the local path planning of mobile robots is studied based on the improved artificial potential field algorithm. The principle of artificial potential field algorithm is explained, and several common shortcomings of traditional artificial potential field algorithm are explained. Accoding to the problem of unreachable target and local minimum in traditional artificial potential field algorithm, the repulsive force function is improved, and the method of resultant force offset is given. Finally, the improved algorithm is simulated in Matalb and compared with the traditional algorithm. Simulation results show that the improved algorithm obtained in this paper is more effective than the traditional algorithm.

Keywords

Potential fieldMotion planningAlgorithmComputer scienceOffset (computer science)Field (mathematics)Path (computing)Mobile robotRobotMathematical optimization

Related papers

Browse all SWARM papers