Optimal Motion Generation of Flexible Macro-micro Manipulator Systems Using Estimation of Distribution Algorithm

  • Yu Zhang
  • Shude Zhou
  • Tangwen Yang
  • Zengqi Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)


In this paper, a new approach for motion generation and optimization of the flexible macro-micro manipulator system is proposed based on Estimation of Distribution Algorithm (EDA). The macro-micro manipulator system is a redundant system, of which inverse kinematics remains challenging, with no generic solution to date. Here, the manipulator system configurations, or the optimal joint motions, are generated using the EDA algorithm base on Gaussian probability model. Compared with simple genetic algorithms (SGA), this approach uses fewer parameters and the time for motion optimization is remarkably reduced. The proposed approach shows excellent performance on motion generation and optimization of a flexible macro-micro manipulator system, as demonstrated by the simulation results.


Motion Generation Motion Error Distribution Algorithm Joint Variable Simple Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yu Zhang
    • 1
  • Shude Zhou
    • 1
  • Tangwen Yang
    • 1
  • Zengqi Sun
    • 1
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina

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