河北水利电力学院学报

河北水利电力学院学报 ›› 2025, Vol. 35 ›› Issue (4): 33-39.DOI: 10.16046/j.cnki.issn2096-5680.2025.04.006

• 人工智能与机器人 • 上一篇    下一篇

基于改进蚁狮算法的机器人路径规划

范县成, 凌新宇, 黄洪斌, 朱国武   

  1. 安徽信息工程学院电气与电子工程学院,安徽省芜湖市湾沚区永和路1号 241000
  • 收稿日期:2024-12-17 修回日期:2025-02-24 出版日期:2025-11-30 发布日期:2026-01-05
  • 作者简介:范县成(1990-),男,安徽阜阳人,工程师,主要研究方向:运动控制系统方面的研究。E-mail:2382493123@qq.com
  • 基金资助:
    安徽省高等学校省级自然科学研究计划项目(2023AH052918、2024AH050637)

Robot Path Planning Based on Improved Ant Lion Optimizer

FAN Xiancheng, LING Xinyu, HUANG Hongbin, ZHU Guowu   

  1. School of Electrical and Electronic Engineering, Anhui Institute of Information Technology, 241000, Wuhu, Anhui, China
  • Received:2024-12-17 Revised:2025-02-24 Online:2025-11-30 Published:2026-01-05

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摘要： 蚁狮算法(Ant Lion Optimizer,ALO)应用过程中存在依赖初始种群、收敛速度慢和容易陷入局部最优值等问题,针对以上问题提出1种改进蚁狮路径规划算法。首先,使用Cat混沌映射函数初始化种群,提高种群多样性,以此来增强种群在全局环境的探索能力。其次,引入自适应动态权重调整蚂蚁的随机游走方式,减小陷入局部最优解的可能性,引入自适应系数,改进蚁狮对蚂蚁随机游走的影响。再次,设计不同的栅格地图,将改进后的蚁狮算法与多种智能算法在栅格地图中进行路径规划仿真对比,验证算法优越性。最后,对改进蚁狮算法规划的路径进行B样条曲线平滑处理,提高机器人运动的安全性和稳定性。实验结果表明:改进算法相较于部分算法在最短路径、迭代次数、转弯次数分别减少21.81%、87.04%、53.85%,改进后的蚁狮算法在路径规划问题中有着更好的表现,具有更快的收敛速度和更好的寻优能力。

关键词: 蚁狮算法, Cat混沌映射, 路径规划, B样条曲线

Abstract: Aiming at the problems of Ant Lion Optimizer (ALO), such as relying on the initial population, slow convergence speed and easy to fall into the local optima, an improved ant lion path planning algorithm is proposed.Firstly, the Cat chaotic mapping function is used to initialize the population and increase the population diversity as a way to enhance the ability of the population to explore the global environment.Secondly, adaptive dynamic weights are introduced to adjust the ants’ random wandering way to reduce the possibility of falling into the local optimal solution, and adaptive coefficients are introduced to improve the influence of ant lions on the ants’ random wandering.Then, different grid maps are designed, and the improved ant lion algorithm is compared with multiple intelligent algorithms for path planning simulation in grid maps to verify the superiority of the algorithm.Finally, the paths planned by the improved ant lion algorithm are smoothed with B-spline curves to improve the safety and stability of robot motion.The experimental results show that the improved algorithm reduces 21.81%, 87.04% and 53.85% in the shortest path, the number of iterations and the number of turns respectively compared with the partial algorithms, and the improved ant lion algorithm has a better performance in the path planning problem with faster convergence and better optimization-seeking ability.

Key words: Antlion algorithm, Cat chaotic mapping, path planning, B-spline curve

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