北京航空航天大学学报 ›› 2015, Vol. 41 ›› Issue (9): 1693-1700.doi: 10.13700/j.bh.1001-5965.2014.0665

• 论文 • 上一篇    下一篇

基于姿态可操作度的机械臂尺寸优化方法

贾世元, 贾英宏, 徐世杰   

  1. 北京航空航天大学 宇航学院, 北京 100191
  • 收稿日期:2014-10-25 出版日期:2015-09-20 发布日期:2015-09-29
  • 通讯作者: 贾英宏(1976—),男,河北阳原人,副教授,jia_yingh@163.com,主要研究方向为航天器动力学与控制. E-mail:jia_yingh@163.com
  • 作者简介:贾世元(1988—),男,山东日照人,博士研究生,jiashi.yuan@163.com
  • 基金资助:
    国家自然科学基金(11272027)

Dimensional optimization method for manipulator based on orientation manipulability

JIA Shiyuan, JIA Yinghong, XU Shijie   

  1. School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2014-10-25 Online:2015-09-20 Published:2015-09-29

摘要: 为解决机械臂尺寸优化设计问题,首先定义了表征灵活性的数值指标——姿态概率系数,即指定工作点上可行样本姿态与所取样本姿态之间的比值;之后根据姿态概率系数提出了姿态可操作度概念,它表征了机械臂在工作空间上的整体可操作性.在此基础上,提出了机械臂尺寸优化方法.该方法在机械臂原有结构设计的基础上,以机械臂自身无碰撞为约束条件,以姿态可操作度的倒数为适应度函数,利用遗传算法优化机械臂的尺寸参数,使优化后机械臂的可操作性最优.以六自由度(DOF)机械臂为例的优化结果表明:优化后机械臂姿态可操作度提高了40.33%.最后利用灵活性工作空间图进一步验证了算法的有效性,并讨论了姿态概率系数对优化结果的影响.

关键词: 机械臂, 尺寸优化, 灵活性, 姿态可操作度, 遗传算法

Abstract: To solve the dimensional optimization design problem of manipulator, the numerical index of dexterity was presented by pose probability coefficient, which was defined as the ratio between possibly sampled orientations and sampled orientations of the working point. According to the pose probability coefficient, the concept of orientation manipulability was proposed, which represented the operability of manipulator. On the basis of orientation manipulability, an algorithm of dimensional optimization to manipulator was proposed. Based on the original structure design, this algorithm takes the reciprocal of the orientation manipulability as fitness function. Under the condition of self-collision, dimensional parameters of manipulator were optimized to maximize the operability by using genetic algorithm. Optimization algorithm was applied to a six-degree of freedom (DOF) manipulator. Results show that the orientation manipulability increases by 40.33% after optimization. Finally, validity of the algorithm was further verified by dexterous workspace and the effect of the pose probability coefficient to the optimal results was also discussed.

Key words: manipulator, dimensional optimization, dexterity, orientation manipulability, genetic algorithm

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