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  • 标题:Research on the inverse kinematics of manipulator using an improved self-adaptive mutation differential evolution algorithm
  • 本地全文:下载
  • 作者:Qianqian Zhang ; Daqing Wang ; Lifu Gao
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2021
  • 卷号:18
  • 期号:3
  • 页码:1
  • DOI:10.1177/17298814211014413
  • 出版社:SAGE Publications
  • 摘要:To assess the inverse kinematics (IK) of multiple degree-of-freedom (DOF) serial manipulators, this article proposes a method for solving the IK of manipulators using an improved self-adaptive mutation differential evolution (DE) algorithm. First, based on the self-adaptive DE algorithm, a new adaptive mutation operator and adaptive scaling factor are proposed to change the control parameters and differential strategy of the DE algorithm. Then, an error-related weight coefficient of the objective function is proposed to balance the weight of the position error and orientation error in the objective function. Finally, the proposed method is verified by the benchmark function, the 6-DOF and 7-DOF serial manipulator model. Experimental results show that the improvement of the algorithm and improved objective function can significantly improve the accuracy of the IK. For the specified points and random points in the feasible region, the proportion of accuracy meeting the specified requirements is increased by 22.5% and 28.7%, respectively.
  • 关键词:DE ; IK ; adaptive mutation operator ; adaptive scaling factor ; orienting weighting factor
  • 其他关键词:DE ; IK ; adaptive mutation operator ; adaptive scaling factor ; orienting weighting factor
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