Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지

Visual Servoing of Robot Manipulators using the Neural Network with Optimal structure

최적구조의 신경회로망을 이용한 로붓 매니퓰레이터의 비주얼 서보잉

  • Kim, Dae-Joon (Dept. of Control and Instrumentation Engineering, Chung-Ang University) ;
  • Lee, Dong-Wook (Dept. of Control and Instrumentation Engineering, Chung-Ang University) ;
  • Chun, Hyo-Byong (Dept. of Control and Instrumentation Engineering, Chung-Ang University) ;
  • Sim, Kwee-Bo (Dept. of Control and Instrumentation Engineering, Chung-Ang University)
  • 김대준 (중앙대학교 제어계측공학과) ;
  • 이동욱 (중앙대학교 제어계측공학과) ;
  • 전효병 (중앙대학교 제어계측공학과) ;
  • 심귀보 (중앙대학교 제어계측공학과)
  • Published : 1996.07.22
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents a visual servoing combined by evolutionary algorithms and neural network for a robotic manipulators to control position and orientation of the end-effector. Using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we generate the control input to agree the target image, to realize the visual servoing. The validity and effectiveness of the proposed control scheme will be verified by computer simulations.

Keywords