RESEARCH ARTICLE

Optimal design of a linkage–cam mechanism-based redundantly actuated parallel manipulator

  • Haiying WEN 1 ,
  • Ming CONG 2 ,
  • Weiliang XU 3 ,
  • Zhisheng ZHANG , 1 ,
  • Min DAI 1
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  • 1. School of Mechanical Engineering, Southeast University, Nanjing 211189, China
  • 2. School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
  • 3. Department of Mechanical Engineering, The University of Auckland, Auckland 1142, New Zealand

Received date: 14 Sep 2020

Accepted date: 20 Feb 2021

Published date: 15 Sep 2021

Copyright

2021 Higher Education Press

Abstract

A redundantly actuated parallel manipulator (RAPM) with mixed translational and rotational degrees of freedom (DOFs) is challenged for its dimensionally homogeneous Jacobian modeling and optimal design of architecture. In this paper, a means to achieve redundant actuation by adding kinematic constraints is introduced, which reduces the DOFs of the end-effector (EE). A generic dimensionally homogeneous Jacobian is developed for this type of RAPMs, which maps the generalized velocities of three points on the EE to the joint velocities. A new optimization algorithm derived from this dimensionally homogeneous Jacobian is proposed for the optimal design of this type of RAPMs. As an example, this paper presents a spatial RAPM involving linkages and cam mechanisms. This RAPM has 4 DOFs and 6 translational actuations. The linkage lengths and the position of the universal joints of the RAPM are optimized based on the dimensionally homogeneous Jacobian.

Cite this article

Haiying WEN , Ming CONG , Weiliang XU , Zhisheng ZHANG , Min DAI . Optimal design of a linkage–cam mechanism-based redundantly actuated parallel manipulator[J]. Frontiers of Mechanical Engineering, 2021 , 16(3) : 451 -467 . DOI: 10.1007/s11465-021-0634-6

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 51705063 and 51575078) and the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20190368).
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