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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Motion Imitation Learning and Real-time Movement Generation of Humanoid Using Evolutionary Algorithm

진화 알고리즘을 사용한 인간형 로봇의 동작 모방 학습 및 실시간 동작 생성

  • 박가람 (고려대학교 기계공학과, 한국과학기술연구원(KIST)) ;
  • 나성권 (한국과학기술연구원(KIST) 인지로봇연구단) ;
  • 김창환 (한국과학기술연구원(KIST) 인지로봇연구단) ;
  • 송재복 (고려대학교 기계공학과)
  • Published : 2008.10.01
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Abstract

This paper presents a framework to generate human-like movements of a humanoid in real time using the movement primitive database of a human. The framework consists of two processes: 1) the offline motion imitation learning based on an Evolutionary Algorithm and 2) the online motion generation of a humanoid using the database updated bγ the motion imitation teaming. For the offline process, the initial database contains the kinetic characteristics of a human, since it is full of human's captured motions. The database then develops through the proposed framework of motion teaming based on an Evolutionary Algorithm, having the kinetic characteristics of a humanoid in aspect of minimal torque or joint jerk. The humanoid generates human-like movements far a given purpose in real time by linearly interpolating the primitive motions in the developed database. The movement of catching a ball was examined in simulation.

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References

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