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Neural Network Compensation for Improvement of Real-Time Moving Object Tracking Performance of the ROBOKER Head with a Virtual Link

가상링크 기반의 ROBOKER 머리의 실시간 대상체 추종 성능 향상을 위한 신경망 제어

  • 김동민 (충남대학교 지능로봇시스템) ;
  • 최호진 (충남대학교 지능로봇시스템) ;
  • 이근형 (충남대학교 지능로봇시스템) ;
  • 정슬 (충남대학교 지능로봇시스템)
  • Published : 2009.07.01

Abstract

This paper presents the implementation of the real-time object tracking control of the ROBOKER head. The visual servoing technique is used to track the moving object, but suffers from ill-estimated Jacobian of the virtual link design. To improve the tracking performance, the RBF(Radial Basis Function) network is used to compensate for uncertainties in the kinematics of the robot head in on-line fashion. The reference compensation technique is employed as a neural network control scheme. Performances of three schemes, the kinematic based scheme, the Jacobian based scheme, and the neural network compensation scheme are verified by experimental studies. The neural compensation scheme performs best.

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