系统仿真学报 ›› 2019, Vol. 31 ›› Issue (12): 2569-2574.doi: 10.16182/j.issn1004731x.joss.19-0550

• 专栏:机器人机构建模与仿真 •    下一篇

基于全局可操作度的6R机械臂尺寸优化方法

李宪华1, 石雪松1, 吕磊1, 张雷刚2, 宋韬2   

  1. 1. 安徽理工大学机械工程学院,安徽 淮南 232001;
    2. 上海大学机电工程与自动化学院,上海 200444
  • 收稿日期:2019-10-14 修回日期:2019-10-20 发布日期:2019-12-13
  • 作者简介:李宪华(1980-),男,山东,博士,教授,研究方向为机器人技术。
  • 基金资助:
    国家自然科学基金(61803251), 安徽高校自然科学研究重点项目(KJ2016A200), 安徽省科技重大专项(16030901012), 安徽省重点研究与开发计划项目(201904a05020092)

Size Optimization Method of 6R Manipulator Based on Global Maneuverability

Li Xianhua1, Shi Xuesong1, Lü Lei1, Zhang Leigang2, Song Tao2   

  1. 1. School of Mechanical Engineering, Anhui University of Science and Technology, Huainan 232001, China;
    2. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
  • Received:2019-10-14 Revised:2019-10-20 Published:2019-12-13

摘要: 针对服务机器人六自由度模块化机械臂,对其结构尺寸参数进行优化分析。定义机械臂工作空间全局可操作度指标,建立位姿坐标系,结合机械臂的逆解计算出位姿可达度,提出机械臂全局可操作度指标以该指标的最大值作为优化目标,应用遗传算法对机械臂的连杆尺寸参数进行优化,得到优化后的连杆尺寸和全局可操作度并绘制出优化前后的机械臂工作空间操作能力地图。仿真结果表明:优化后的机械臂全局可操作度明显提高,对比工作空间能力地图,进一步验证了机械臂尺寸优化算法的有效性。

关键词: 机械臂, 全局可操作度, 遗传算法, 尺寸优化

Abstract: Aiming at the six-DOF manipulator of service robot, the structure size parameters are optimized and analyzed. The global manipulability index of the manipulator workspace is defined, the coordinate system of the position and attitude is established, and the reachability of the position and attitude is calculated with the inverse solution of the manipulator, and the global manipulability index of the manipulator is proposed. Taking the maximum value of this index as the optimization target, the size parameters of the connecting rod of the manipulator are optimized by genetic algorithm, the size of the optimized connecting rod and the global operational degree are obtained, and the operational ability map of the manipulator workspace before and after optimization is drawn. The simulation results show that the global maneuverability of the optimized manipulator is obviously improved, and the validity of the size optimization algorithm is further verified by comparing the workspace capability map.

Key words: manipulator, global maneuverability, genetic algorithm, size optimization

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