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Path planning of mobile robot based on improved artificial potential field method
XU Xiaoqiang, WANG Mingyong, MAO Yan
Journal of Computer Applications    2020, 40 (12): 3508-3512.   DOI: 10.11772/j.issn.1001-9081.2020050640
Abstract598)      PDF (849KB)(677)       Save
Aiming at the problem that the traditional artificial potential field method is easy to fall into trap area and local minimum in the path planning process, an improved artificial potential field method was proposed. Firstly, the concept of safe distance was proposed to avoid unnecessary paths, so as to solve the problems of long path length and long algorithm running time. Then, in order to avoid the robot being trapped in the local minimum and trap area, the predictive distance was introduced into the algorithm, so that the algorithm was able to react before the robot being trapped in the local minimum or trap area. Finally, the robot was guided to avoid the local minimum and trap area by setting the virtual target points reasonably. The experimental results show that, the improved algorithm can effectively solve the problem that the traditional algorithm is easy to fall into the local minimum and trap area. At the same time, compared with those of the traditional artificial potential field method, the path length planned by this proposed algorithm is reduced by 5.2% and its speed is increased by 405.56%.
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