粒子群算法在崎岖地形路径规划中的应用

N. ZakeriNejad, A. Bakhtiary, M. R. Jahed Motlagh
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引用次数: 4

摘要

随着自动驾驶汽车的发展,在崎岖地形上的导航问题成为一个有趣的问题。一种可能的解决方案已经被证明是使用粒子群优化(PSO)在平面上进行导航。本文旨在介绍从实验中获得的结果,以衡量PSO在崎岖地形环境中路径规划的充分性。建立了粒子群算法来选择由直线段组成的路径。然后在模拟器中使用控制器来引导我们的车辆沿着每条路径,然后使用所穿越路线的质量来评估每条路径。准备并求解了两种不同的环境,并给出了每种环境的求解结果。结果表明,粒子群算法确实适用于粗糙环境下的路径规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of Particle Swarm Optimization in path planning for rough terrain
With the advancement of autonomous vehicles the problem of navigation in rough terrain is becoming an interesting problem to tackle. One possible solution that has already been demonstrated for navigation on flat surfaces has been the use of Particle Swarm Optimization, PSO. This document aims to present results obtained from experiments gauging the adequacy of PSO for path planning in rough terrain environments. The PSO algorithm is set up to choose paths composed of straight line segments. A Controller is then used in a simulator to guide our vehicle along each path and the quality of the route traversed is then used to evaluate each path. Two different environments are prepared and solved for and the result for each environment is presented. It is shown that PSO is indeed applicable for use in path planning for rough environments.
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