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基于改进人工势场法的无人车路径规划算法研究
Research on Path Planning Algorithm of Unmanned Vehicle Based on Improved Artificial Potential Field Method

DOI: 10.12677/CSA.2023.134069, PP. 698-707

Keywords: 人工势场法,路径规划,无人驾驶,虚拟目标点
Artificial Potential Field Method
, Path Planning, Unmanned Vehicle, Virtual Target Point

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Abstract:

针对传统人工势场法路径规划中存在的局部极小值和目标不可达等问题,本文提出了一种人工势场法的改进方法。首先,定义障碍物的碰撞范围并建立基于角度的影响范围,排除无人车前方一定距离和角度内的任何障碍物,从而将它们的影响降到最低。其次,为了解决目标不可达问题,通过新增目标点与无人车的距离因子改进斥力函数。最后,针对局部极小值问题,在障碍物碰撞范围外创造虚拟目标点。利用Matlab对所提出的改进算法进行验证,仿真结果表明了规划算法的避障有效性、安全性以及可跟踪性。
To address issues such as local minima and unreachable targets that arise in path planning using the traditional artificial potential field method, an enhanced approach to the artificial potential field method has been proposed in this paper. First, define the collision range of obstacles and establish an angle-based influence range to exclude any obstacles within a certain distance and angle in front of the unmanned vehicle, thereby minimizing their impact. Secondly, in order to solve the problem of unreachable targets, the repulsion function is improved by adding the distance factor between the target point and the unmanned vehicle. Finally, for the local minimum problem, a virtual target point is created outside the obstacle collision range. The proposed improved algorithm is verified by Matlab, and the simulation results show the effectiveness, safety and traceability of the planning algorithm for obstacle avoidance.

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