基于混合搜索蜂群算法的机器人轨迹规划  

Robot Trajectory Planning Based on Hybrid Search Bee Colony Algorithm

作　　者：姚江云 吴方圆 YAO Jiang-yun;WU Fang-yuan(College of Information Science and Engineering,Liuzhou Institute of Technology,Liuzhou 545616,China;Guangxi Aurora Intellectual Property Service Co.,Ltd.,Nanning 530000,China)

机构地区：[1]柳州工学院信息科学与工程学院,柳州545616 [2]广西曙光知识产权服务有限公司,南宁530000

出　　处：《自动化与仪表》2022年第10期40-43,51,共5页Automation & Instrumentation

基　　金：2020年度广西高校中青年教师科研基础能力提升项目(2020KY60012);广西科技基地和人才专项项目(2020AC19115)。

摘　　要：为了解决在复杂环境下机器人工作过程中的避障及运动轨迹优化问题,提出一种基于混合搜索策略改进的人工蜂群算法机器人轨迹规划方法。传统的蜂群算法在进行邻域搜索时,都采用单一的、静态的搜索策略,存在收敛速度慢,易陷入局部最优的问题,该文通过引入搜索因子将不同的搜索策略进行整合,通过模糊控制算法控制搜索因子的大小决定采用何种搜索策略,实现了多种搜索策略混合执行的改进型人工蜂群算法,最后将该算法应用于机器人轨迹优化问题中。实验结果表明,该方法能够得到较优轨迹,且寻优速度快、过程稳定。In order to solve the obstacle avoidance and trajectory optimization problems of robots,an improved artificial bee colony algorithm based on hybrid search strategy is proposed. Tradi tional artificial bee colony algorithm adopts a single and static search strategy,which leads to slow convergence rate and easy to fall into local optimum.In this paper,different search strategies are integrated by search factors,the size of search factors is controlled by fuzzy control algorithm to determine which search strategy to adopt,an improved artificial bee colony algorithm with mixed execution of multiple search strategies is realized. Finally,the algorithm is applied to the trajectory optimization of robot,the results show that this method can get the optimal trajectory,the speed of optimization is fast and the process is stable.

关 键 词：机器人 轨迹规划 混合搜索 蜂群算法 最优解 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置] TN302[自动化与计算机技术—控制科学与工程]