A Study on Trajectory Control of Robot Manipulator using Neural Network and Evolutionary Algorithm

신경망과 진화 알고리즘을 이용한 로봇 매니퓰레이터의 궤적 제어에 관한 연구

  • Kim, Hae-Jin (dept. of Electrical Engineering Kyungpook National University) ;
  • Lim, Jung-Eun (dept. of Electrical Engineering Kyungpook National University) ;
  • Lee, Young-Seok (dept. of Digital Electricity & Medical System Yeungjin Collage) ;
  • Seo, Bo-Hyeok (dept. of Electrical Engineering Kyungpook National University)
  • 김해진 (경북대학교 전기공학과) ;
  • 임정은 (경북대학교 전기공학과) ;
  • 이영석 (영진전문대학 디지털의료전기계열) ;
  • 서보혁 (경북대학교 전기공학과)
  • Published : 2006.07.12

Abstract

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.

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