3D Path planning of fixed and mobile environments using potential field algorithm with Genetic algorithm

A. F. Albaghdadi, A. Ali
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引用次数: 6

Abstract

Path planning is one of the most important techniques responsible for drawing a collision-free path for each robot in a crowded environment. Potential field algorithm is one of most fame algorithms of path planning, it works online. The potential field algorithm deals with any robot as an electron in a potential field. This robot or electron attract to the goal location and repulsion from other robots and obstacles. These forces cause it to move naturally to the target point with a suboptimal path. In this paper, we study and simulate multi scenarios of potential field algorithm in both cases which are: static and dynamic 3D environments. In the static environment, we suppose many static obstacles in random positions then find suboptimal path according to this algorithm. The second scenarios based on the existence of multiple mobile robots. The straight line path of each robot collides at least with the one other path. This algorithm used to solve this problem and find a collision-free path for each robot.
利用势场算法结合遗传算法进行固定和移动环境的三维路径规划
路径规划是在拥挤环境中为每个机器人绘制无碰撞路径的重要技术之一。势场算法是最著名的路径规划算法之一,它在线工作。势场算法将任何机器人视为势场中的电子。这种机器人或电子吸引到目标位置,并排斥其他机器人和障碍物。这些力使它以次优路径自然地移动到目标点。本文对势场算法在静态和动态两种三维环境下的多场景进行了研究和仿真。在静态环境中,我们假设许多静态障碍物在随机位置,然后根据该算法找到次优路径。第二种场景基于多个移动机器人的存在。每个机器人的直线路径至少与另一条路径发生碰撞。该算法用于解决这一问题,并为每个机器人找到一条无碰撞的路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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