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Global Stiffness and Well-Conditioned Workspace Optimization Analysis of 3UPU-UPU Robot Based on Pareto Front Theory

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Book cover Cooperative Design, Visualization, and Engineering (CDVE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9320))

Abstract

In this paper, an approach based on the Pareto front theory is employed to conduct the multi-objective optimization of the global stiffness and well-conditioned workspace of 3UPU-UPU parallel mechanism. The inverse kinematic and Jacobian matrix of the 3UPU-UPU mechanism are first calculated. Then the stiffness model of the mechanism is derived and the sum of the diagonal elements of the stiffness matrix is used as a criterion to evaluate the global stiffness. Secondly, the Monte Carlo method is used to derive the global condition index of the mechanism which later is used as a criterion to evaluate the well-conditioned workspace of the mechanism. Normally, increasing the workspace of the mechanism will deteriorate the stiffness, here the global stiffness and well-conditioned workspace of the mechanism are optimized simultaneously based on the Pareto front theory, and the optimized results are displayed and compared.

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Acknowledgements

The authors would like to gratefully acknowledge the financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and Canada Research Chairs program.

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Authors and Affiliations

  1. University of Ontario Institute of Technology, Oshawa, ON, Canada

    Dan Zhang & Bin Wei

Authors
  1. Dan Zhang
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  2. Bin Wei
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Correspondence to Dan Zhang .

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Editors and Affiliations

  1. University of Balearic Islands, Palma de Mallorca, Spain

    Yuhua Luo

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Zhang, D., Wei, B. (2015). Global Stiffness and Well-Conditioned Workspace Optimization Analysis of 3UPU-UPU Robot Based on Pareto Front Theory. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-24132-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24131-9

  • Online ISBN: 978-3-319-24132-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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