Self-Learning Control of Cooperative Motion for Humanoid Robots

  • Hwang, Yoon-Kwon (School of Mechatronics, Changwon National University) ;
  • Choi, Kook-Jin (Department of Mechanical Design and Manufacturing, Changwon National University) ;
  • Hong, Dae-Sun (Department of Mechanical Design and Manufacturing, Changwon National University)
  • Published : 2006.12.30

Abstract

This paper deals with the problem of self-learning cooperative motion control for the pushing task of a humanoid robot in the sagittal plane. A model with 27 linked rigid bodies is developed to simulate the system dynamics. A simple genetic algorithm(SGA) is used to find the cooperative motion, which is to minimize the total energy consumption for the entire humanoid robot body. And the multi-layer neural network based on backpropagation(BP) is also constructed and applied to generalize parameters, which are obtained from the optimization procedure by SGA, in order to control the system.

Keywords

References

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