基于改进遗传算法的换纱筒机器人路径规划  

Path Planning of the Bobbin Changing Robot Based on Improved Genetic Algorithm

作　　者：段玉堂 屠佳佳 韩思捷 史伟民[1] Duan Yutang;Tu Jiajia;Han Sijie;Shi Weimin(Key Laboratory of Modern Textile Machinery&Technology of Zhejiang Province,Zhejiang Sci-tech University,Hangzhou,Zhejiang 310018,China;School of Automation,Zhejiang Institute of Mechanical and Electrical Engineering,Hangzhou,Zhejiang 310053,China)

机构地区：[1]浙江理工大学浙江省现代纺织装备技术重点试验室,浙江杭州310018 [2]浙江机电职业技术学院自动化学院,浙江杭州310053

出　　处：《针织工业》2024年第7期1-4,共4页Knitting Industries

基　　金：国家重点研发计划资助项目(2017YFB1304000)。

摘　　要：为了解决针织换筒机器人顺序换筒耗时长、功耗高问题,首先综合考虑换筒机器人移动距离和翻转等待时间,建立具有时空约束的换筒路径数学模型;其次基于自适应遗传算法,提出一种改进的近邻度初始种群算子和按位变异的局部搜索算子,得到改进的遗传算法。结果表明,改进遗传算法规划的换筒机器人路径所消耗的生产时间相对于人工排序缩减55.5%,改进算法收敛速度相对于传统遗传算法提升48.3%,改进算法最优解质量也优于其他几种传统启发式算法,提升了系统效率,证明改进遗传算法应用在换筒机器人路径规划优化问题中的可行性和有效性。In order to solve the problem of long time consuming and high power consumption of bobbin changing robot,a mathematical model of bobbin changing path with spatio-temporal constraints was established by considering the moving distance and waiting time of the bobbin changing robot.Secondly,based on the adaptive genetic algorithm,an improved initial population operator of neighbor degree and local search operator of bitwise variation are proposed to obtain the improved genetic algorithm.The results show that the improved genetic algorithm programming of the robot in drum production time consumed by a path relative to the manual sorting shrinks by 55.5%,the convergence rate of the improved algorithm is 48.3%higher than that of the traditional genetic algorithm,the quality of the optimal solution of improved algorithm is also better than other traditional heuristic algorithm,which improves the system efficiency,and proves the feasibility and effectiveness of the improved genetic algorithm in the path planning optimization problem of the bobbin-changing robot.

关 键 词：针织换筒机器人 路径规划 自动换筒 局部搜索算子 改进遗传算法 

分 类 号：TS183.92[轻工技术与工程—纺织材料与纺织品设计]