电子学报 ›› 2020, Vol. 48 ›› Issue (11): 2101-2113.DOI: 10.3969/j.issn.0372-2112.2020.11.003

• 学术论文 • 上一篇    下一篇

多策略集成的樽海鞘群算法的机器人路径规划

王秋萍, 王彦军, 戴芳   

  1. 西安理工大学理学院, 陕西西安 710054
  • 收稿日期:2020-01-20 修回日期:2020-08-05 出版日期:2020-11-25 发布日期:2020-11-25
  • 通讯作者: 王秋萍
  • 作者简介:王彦军 男,1993年3月出生于甘肃临洮,硕士研究生,研究方向为智能计算及在机器人路径规划中的应用.E-mail:1725917163@qq.com;戴芳 女,1966年出生,陕西蓝田人,教授,博士,硕士生导师,主要研究方向为图像处理与计算机视觉.E-mail:daifang@xaut.edu.cn
  • 基金资助:
    国家自然科学基金(No.61976176)

Multi-Strategy Ensemble Salp Swarm Algorithm for Robot Path Planning

WANG Qiu-ping, WANG Yan-jun, Dai Fang   

  1. Faculty of Sciences, Xi'an University of Technology, Xi'an, Shaanxi 710054, China
  • Received:2020-01-20 Revised:2020-08-05 Online:2020-11-25 Published:2020-11-25

摘要: 针对求解机器人路径规划问题,本文提出了一种多策略集成的樽海鞘群算法.在该算法中,提出了新的自适应领导者结构,以平衡算法的探索和开发能力;引入可以提高Lyapunov指数的Logistic-Cubic级联混沌映射作为食物源的扰动算子,来避免算法陷入局部最优;采用基于自适应参数的分散觅食策略使部分追随者探索有前景的区域.在CEC 2014测试集的多种函数上,本文算法与3种改进的樽海鞘群算法和5种先进的群智能算法进行比较,结果表明本文算法综合优化性能更好.本文算法2将其用于求解机器人路径规划问题,其中用三次样条插值对路径进行平滑.在障碍是8,9,13的环境下分别进行仿真实验,仿真结果表明,本文算法在给定的仿真场景下与给定的对比算法相比获得了最好的结果.

关键词: 樽海鞘群算法, 路径规划, Lyapunov指数, 级联混沌, 三次样条

Abstract: A multi-strategy ensemble salp swarm algorithm is proposed for solving problem of robot path planning.In the algorithm,a new adaptive leader structure is proposed to balance the exploration and exploitation ability of the algorithm.The chaotic map of Logistic-Cubic cascade which can improve the Lyapunov exponent of the cascade chaotic system is introduced as the disturbance operator of the food source to avoid the algorithm falling into the local optimum.A disperse foraging strategy based on adaptive parameters is adopted to force a part of followers to explore promising areas.The algorithm in this paper is compared with three improved SSA algorithms and five state-of-the-art swarm intelligence algorithms on IEEE CEC 2014 functions.The results show that the comprehensive optimization performance of the algorithm in this paper is better.The proposed algorithm is applied to solve the robot path planning problem,in which the path is smoothed by cubic spline interpolation.Simulation experiments are implemented on computer in the environments where the obstacles are 8,9,13,respectively.The simulation results demonstrate that the proposed algorithm can achieve the best results compared with the given contrast algorithms in given simulation scenarios.

Key words: salp swarm algorithm, path planning, Lyapunov exponent, cascade chaotic, cubic spline

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