Research on Static/Dynamic Global Path Planning Based on Improved A ∗ Algorithm for Mobile Robots

J. Robotics Pub Date : 2023-06-16 DOI:10.1155/2023/5098156
Huifang Bao, Jie Fang, Chao Wang, Zebin Li, Jinsi Zhang, Chuansheng Wang
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Abstract

In view of the problems of A ∗ algorithm in path planning, such as collision risk, the path is not necessarily optimal, and there are numerous turning nodes. Therefore, this study proposes an improved A ∗ algorithm to improve the quality of the planned path. First, the 8-neighborhood children of the parent node are generated, and the security of the planned path is improved by further investigating the properties of the neighbors of these children one by one to reasonably set virtual obstacles. Second, the heuristic function of A ∗ algorithm is ameliorated to make it closer to the actual cost, so as to enhance the accuracy of the planned path; finally, the planned path is smoothed by using the cubic uniform B-spline curve to eliminate corner sharp points in the path. The simulation results show that the improved A ∗ algorithm can not only ensure the safety and smoothness of the planned path but also obtain the shortest planned path in the static environment with different obstacle rates. In addition, we combine the improved A ∗ algorithm with the dynamic window algorithm to enable mobile robots to realize real-time dynamic obstacle avoidance while ensuring the optimality of global path planning.
基于改进A *算法的移动机器人静态/动态全局路径规划研究
考虑到A *算法在路径规划中存在的碰撞风险、路径不一定最优、转弯节点众多等问题。因此,本研究提出一种改进的A *算法,以提高规划路径的质量。首先,生成父节点的8个邻域子节点,通过进一步逐一研究这些子节点的邻域属性,合理设置虚拟障碍物,提高规划路径的安全性。其次,对A *算法的启发式函数进行改进,使其更接近实际代价,从而提高规划路径的精度;最后,利用三次均匀b样条曲线对规划路径进行平滑处理,消除路径中的尖角点。仿真结果表明,改进的A *算法在不同障碍物率的静态环境下,既能保证规划路径的安全性和平滑性,又能获得最短的规划路径。此外,我们将改进的A *算法与动态窗口算法相结合,使移动机器人能够在保证全局路径规划最优的情况下实现实时动态避障。
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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