基于改进A*算法的移动机器人路径规划

Ju Gao, Xiangrong Xu, Xingning Zhang, Shanshan Xu, Quancheng Pu
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引用次数: 6

摘要

路径规划技术是移动机器人自主导航的核心部分。道路规划不规范、拐点节点多等问题亟待解决。针对传统A*算法节点多、搜索时间长、路径弯曲过多等问题,提出了一种采用激励函数优化和三次Bezier曲线优化的改进A*算法。基于ROS开源系统,构建了Gazebo物理仿真环境,并在实际测绘中构建了网格地图。将改进前后的改进算法作为全局路径规划器插件,应用于ROS进行仿真实验。仿真结果表明:在相同的仿真实验环境下,改进的A*算法路径长度减少了17.161%,冗余转弯节点数减少了71.429%;更加合理,进一步满足移动机器人的约束条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Planning of Mobile Robot Based on Improved A* Algorithm
Path planning technology is the core part of the independent navigation of mobile robots. The problem of unscrupulous road planning and many turning point nodes need to be resolved. In response to the problem of traditional A* algorithm expansion nodes, long search time, and excessive path bending, an improvement A* algorithm that uses an inspiration function optimization and cubic Bezier curve optimization. Based on the ROS open-source system, the Gazebo physical simulation environment is built, and the practical Gmapping builds a grid map. The improved algorithm before and after the improvement is used as a global path planner plugin and applied to ROS for simulation experiments. The simulation results show that in the same simulation experimental environment, the length of the improved A* algorithm path is reduced by 17.161%, and the number of redundant turning nodes is reduced by 71.429%; More reasonable, further meet the constraints of mobile robots.
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