Robot Path Planning using Particle Swarm Optimization of Ferguson Splines

M. Saska, M. Macas, L. Preucil, L. Lhotská
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引用次数: 140

Abstract

Robot path planning problem is one of most important task mobile robots. This paper proposes an original approach using a path description by string of cubic splines. Such path is easy executable and natural for car-like robot. Furthermore, it is possible to ensure smooth derivation in connections of particular splines. In this case, the path planning is equivalent to optimization of parameters of splines. An evolutionary technique called particle swarm optimization (PSO) was used hereunder due to its relatively fast convergence and global search character. Various settings of PSO parameters were tested and the best setting was compared to two classical mobile robot path planning algorithms.
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基于Ferguson样条粒子群算法的机器人路径规划
机器人路径规划问题是移动机器人最重要的任务之一。本文提出了一种新颖的三次样条串路径描述方法。这种路径易于执行,对于类车机器人来说是自然的。此外,还可以确保在特定样条的连接中推导平滑。在这种情况下,路径规划相当于样条参数的优化。由于粒子群优化算法具有快速收敛和全局搜索的特点,本文采用了粒子群优化算法。测试了PSO参数的各种设置,并将最佳设置与两种经典移动机器人路径规划算法进行了比较。
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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