摘要
针对移动机器人在断路器柔性装配过程中的路径长度较长、转折点较多等效率问题,提出了一种BAS算法与PSO算法结合的路径优化方法。利用天牛个体更新方式与群体学习相结合,采用自适应步长衰减策略以及动态权重变更策略,实现全局路径规划寻优。为了验证BSO算法的有效性,通过三种不同的测试函数比较性能以及仿真地图进行对比,最后将该算法通过ROS应用到实际地图上。实验结果表明,相比于GA-PSO算法、AIW-PSO算法、BAS算法,路径长度优化率分别提升了7.7%、14.8%与12.5%,转折点优化率分别提升提升了25%、57.1%与40%。综上所述,本文所提出的融合算法能够有效地解决装配过程中的效率问题,提高断路器柔性装配产线效益。
Aiming at the problems of long path length and more turning points of mobile robots in the flexible assembly process of circuit breaker,apath optimization method combining BAS algorithm and PSO algorithm is proposed.By combining the individual update method of beetles with group learning,the adaptive step size decay strategy and the dynamic weight change strategy are adopted to realize the optimization of global path planning.In order to verify the effectiveness of the BSO algorithm,three different test functions are used to compare the performance and the simulation map,and finally the algorithm is applied to the actual map through ROS.Experimental results show that compared with GA-PSO algorithm,AIW-PSO algorithm and BAS algorithm,the optimization efficiency of path length is increased by 7.7%,14.8%and 12.5%,and the optimization efficiency of the number of turns is increased by 25%,57.1%and 40%,respectively.In summary,the fusion algorithm proposed in this paper can effectively solve the efficiency problem in the assembly process and improve the efficiency of the flexible assembly line of the circuit breaker.
作者
王凌浩
舒亮
钱祺
Wang Linghao;Shu Liang;Qian Qi(Low Voltage Apparatus Technology Research Center of Zhejiang,Wenzhou 325207,China;Yueqing Institute of Industrial Research,Wenzhou University,Wenzhou 325606,China)
出处
《电子测量技术》
北大核心
2023年第5期121-128,共8页
Electronic Measurement Technology
基金
浙江省重点研发计划项目(2021C01046)资助
关键词
移动机器人
路径优化
BSO算法
断路器
mobile robots
path optimization
beetle swarm optimization algorithm
circuit breaker
