Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Intelligent Walking Modeling of Humanoid Robot Using Learning Based Neuro-Fuzzy System

학습기반 뉴로-퍼지 시스템을 이용한 휴머노이드 로봇의 지능보행 모델링

  • 박귀태 (고려대학교 전기전자전파공학과) ;
  • 김동원 (고려대학교 전기전자전파공학과)
  • Published : 2007.04.01
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Abstract

Intelligent walking modeling of humanoid robot using learning based neuro-fuzzy system is presented in this paper. Walking pattern, trajectory of the zero moment point (ZMP) in a humanoid robot is used as an important criterion for the balance of the walking robots but its complex dynamics makes robot control difficult. In addition, it is difficult to generate stable and natural walking motion for a robot. To handle these difficulties and explain empirical laws of the humanoid robot, we are modeling practical humanoid robot using neuro-fuzzy system based on the two types of natural motions which are walking trajectories on a t1at floor and on an ascent. Learning based neuro-fuzzy system employed has good learning capability and computational performance. The results from neuro-fuzzy system are compared with previous approach.

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References

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