대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 1989년도 하계종합학술대회 논문집
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- Pages.679-684
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- 1989
신경 회로망에 의한 로보트 매니퓰레이터의 PTP 운동에 관한 연구
A Study on the PTP Motion of Robot Manipulators by Neural Networks
- 경계현 (서울 대학교 제어계측 공학과 로보틱스 및 지능 시스템 연구실) ;
- 고명삼 (서울 대학교 제어계측 공학과 로보틱스 및 지능 시스템 연구실) ;
- 이범희 (서울 대학교 제어계측 공학과 로보틱스 및 지능 시스템 연구실)
- Kyung, Kye-Hyun (Robotics and Intelligent Systems Lab. Dept. of Control and Instrumentation Engineering, Seoul National University) ;
- Ko, Myoung-Sam (Robotics and Intelligent Systems Lab. Dept. of Control and Instrumentation Engineering, Seoul National University) ;
- Lee, Bum-Hee (Robotics and Intelligent Systems Lab. Dept. of Control and Instrumentation Engineering, Seoul National University)
- 발행 : 1989.07.21
초록
In this paper, we describe the PTP notion of robot manipulators by neural networks. The PTP motion requires the inverse kinematic redline and the joint trajectory generation algorithm. We use the multi-layered Perceptron neural networks and the Error Back Propagation(EBP) learning rule for inverse kinematic problems. Varying the number of hidden layers and the neurons of each hidden layer, we investigate the performance of the neural networks. Increasing the number of learning sweeps, we also discuss the performance of the neural networks. We propose a method for solving the inverse kinematic problems by adding the error compensation neural networks(ECNN). And, we implement the neural networks proposed by Grossberg et al. for automatic trajectory generation and discuss the problems in detail. Applying the neural networks to the current trajectory generation problems, we can refute the computation time for trajectory generation.
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