• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2022, Vol. 44 ›› Issue (04): 746-752.

• 人工智能与数据挖掘 • 上一篇    下一篇

基于模拟退火算法的人工势场法路径规划研究

赵炳巍,贾峰,曹岩,孙瑜,刘一鸿   

  1. (西安工业大学机电工程学院,陕西 西安 710021)
  • 收稿日期:2020-08-16 修回日期:2020-11-02 接受日期:2022-04-25 出版日期:2022-04-25 发布日期:2022-04-20
  • 基金资助:
    陕西省创新能力支撑计划(2018TD-36)

Path planning of artificial potential field method based on simulated annealing algorithm

ZHAO Bing-wei,JIA Feng,CAO Yan,SUN Yu,LIU Yi-hong   

  1. (School of Mechanical and Electrical Engineering,Xi’an Technological University,Xi’an  710021,China)
  • Received:2020-08-16 Revised:2020-11-02 Accepted:2022-04-25 Online:2022-04-25 Published:2022-04-20

摘要: 针对传统人工势场法在路径规划中存在局部极值小点问题,使得移动机器人无法运动到目标点,提出一种基于模拟退火算法的人工势场法,其利用模拟退火算法在出现局部极小点的位置附近增设随机目标点,引导移动机器人逐渐逃离出局部极小点区域。最终通过Matlab仿真表明,所设计的方法能使移动机器人逃离局部极小点位置,成功到达目标点位置,并且用时较短,更加稳定。

关键词: 移动机器人, 路径规划, 人工势场法, 模拟退火算法

Abstract: In the traditional artificial potential field method, the local minimum point problem exists in path planning, which makes the mobile robot unable to move to the target point. Therefore, an artificial potential field method based on simulated annealing algorithm is proposed. Artificial potential field method uses the simulated annealing algorithm to add random target points near the local minimum point and guide the mobile robot to escape from the local minimum point area gradually. Finally, Matlab simulation proves that the method can make the mobile robot escape from the local minimum position, successfully reach the target position, consumes shorter time, and is more stable.


Key words: mobile robot, path planning, artificial potential field method, simulated annealing algorithm