Research on Path Planning of Unmanned Vehicle Based on Improved Artificial Potential Field Method

Abstract

An improved method is presented to solve the problems of local optimum and poor real-time performance of conventional artificial potential field method on route planning of unmanned surface vehicles. This method introduces a new repulsive potential field function and adds a regulatory factor. In order to limit the active area, the boundary repulsion field is introduced. By adjusting the boundary repulsion factor and the adjustment factor, the algorithm can be better prevented from falling into local optimum and the optimization efficiency can be improved. This method is simulated in Matlab and compared with traditional algorithms. The test results show that compared to traditional algorithms, using this method for path planning can shorten the range by 3.1%, have a relatively small curvature, reduce the turning point by 33.3 ^% , and have a smoother path, which has broad application prospects.