系统仿真学报 ›› 2026, Vol. 38 ›› Issue (2): 332-345.doi: 10.16182/j.issn1004731x.joss.24-1327

• 机器学习算法 • 上一篇    

基于改进REA*算法的机器人自适应路径规划

朱玲, 李靖, 张朝辉   

  1. 西安电子科技大学 数学与统计学院,陕西 西安 710126
  • 收稿日期:2024-12-02 修回日期:2025-01-16 出版日期:2026-02-18 发布日期:2026-02-11
  • 通讯作者: 李靖
  • 第一作者简介:朱玲(2001-),女,硕士生,研究方向为多智能体系统、路径规划等。
  • 基金资助:
    国家自然科学基金(62202351);陕西省自然科学基础研究计划(2024JC-YBMS538);西安电子科技大学2024年学科交叉拓展特支计划(TZJH2024003)

An Adaptive Robot Path Planning Based on Improved REA* Algorithm

Zhu Ling, Li Jing, Zhang Zhaohui   

  1. School of Mathematics and Statistics, Xidian University, Xi'an 710126, China
  • Received:2024-12-02 Revised:2025-01-16 Online:2026-02-18 Published:2026-02-11
  • Contact: Li Jing

摘要:

为提高机器人全局路径规划的计算效率及路径平滑度,提出了一种基于改进单边矩形扩展(rectangle expansion A*,REA*)算法的机器人自适应路径规划策略。在障碍物周围设置缓冲区保障机器人运行的安全性;以矩形单边扩展形成的通行区间作为运算单位结合双向交替搜索策略加速路径规划的效率;基于势场理论,引入向量形式优化评价函数自适应快速避障;提出一种新的路径规划策略以优化路径平滑度。仿真结果表明:与经典的A*算法及REA*算法等相比,该算法能够在更短时间内找到较短且平滑的路径。

关键词: 路径规划, REA*算法, 双向交替搜索, 自适应评价函数, 路径平滑度

Abstract:

In order to improve the computational efficiency and path smoothness in a robot's global path planning, an adaptive robot path planning strategy based on an improved unilateral rectangle expansion A*(REA*) algorithm was proposed. The robot's operational safety was ensured by setting a buffer around obstacles. A passable interval formed by unilateral rectangle expansion was used as the operation unit, and bidirectional alternating search was combined to enhance the path planning efficiency. Inspired by potential field theory, the evaluation function was optimized by introducing a vector form to achieve fast adaptive obstacle avoidance. A new path planning strategy was proposed tooptimize the path smoothness. The simulation results show that compared with the classical A* algorithm, the REA* algorithm, and other algorithms, the proposed algorithm can find the shortest and smoothest path within the shortest time.

Key words: path planning, REA* algorithm, bidirectional alternating search, adaptive evaluation function, path smoothness

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