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SP-search-based path planning algorithm for mobile robots using quintic trigonometric Bézier curves
Concurrency and Computation: Practice and Experience ( IF 2 ) Pub Date : 2021-07-18 , DOI: 10.1002/cpe.6493
Vahide Bulut 1
Affiliation  

Path planning is an essential step for mobile robots. This paper presents a novel shape parameter search- (SP-Search) based path planning algorithm for mobile robots using quintic trigonometric Bézier curve and its two shape parameters. The proposed search algorithm recursively divides the shape parameter space into a grid and uses a multi-objective function to determine the shape parameter values. The multi-objective function is expressed by the sum of four terms multiplied by coefficients: the integral of the squared jerk, the integral of the squared curvature, the mean of minimum distances between the predefined skeleton and quintic trigonometric Bézier path, and the arclength. Optimal shape parameters can be determined according to the required cases by the user using four coefficient values. Experimental results illustrate the feasibility of the proposed SP-Search algorithm. Also, we have developed another intuitive algorithm, the Brute Force Grid Search algorithm, which is the brute force approach for shape parameter search to compare the performance of the proposed SP-search algorithm for path planning problems as a baseline. The experimental results show that the SP-Search algorithm finds better shape parameter values with a considerably small number of searched points.

中文翻译:

使用五次三角贝塞尔曲线的基于SP搜索的移动机器人路径规划算法

路径规划是移动机器人必不可少的一步。本文提出了一种新颖的基于形状参数搜索(SP-Search)的移动机器人路径规划算法,该算法使用五次三角贝塞尔曲线及其两个形状参数。所提出的搜索算法递归地将形状参数空间划分为网格,并使用多目标函数来确定形状参数值。多目标函数由四项之和乘以系数表示:平方加加速度的积分、平方曲率的积分、预定义骨架和五次三角贝塞尔路径之间的最小距离的平均值以及弧长。用户可以根据需要使用四个系数值确定最佳形状参数。实验结果说明了所提出的SP-Search算法的可行性。此外,我们还开发了另一种直观的算法,Brute Force Grid Search 算法,它是形状参数搜索的蛮力方法,以比较建议的 SP 搜索算法作为基线的路径规划问题的性能。实验结果表明,SP-Search算法在搜索点数相当少的情况下找到了更好的形状参数值。
更新日期:2021-07-18
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