Stabilizing position/force control of robots interacting with environment by learning connectionist structures

Author:

Vukobratović Miomir,Katić Duško

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Reference24 articles.

1. Learning control for robot tasks under geometric endpoint constraints;Arimoto,1992

2. Teaching and learning of compliance using neural nets: representation and generalization of nonlinear compliance;Asada,1990

3. Transfer of human skills to neural net robot controllers;Asada,1991

4. On the modelling of robots in contact with dynamic environments;DeLuca,1991

5. Adaptation and learning by neural network for robotic manipulator;Fukuda,1990

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Intelligent robotic fettling using a visual feedback technique and force sensing;The International Journal of Advanced Manufacturing Technology;2004-04-21

2. A robust position/force learning controller of manipulators via nonlinear H∞ control and neural networks;IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics);2000-04

3. Experiments in robotic fettling using visual feedback;Industrial Robot: An International Journal;1998-08

4. Control of robots with elastic joints interacting with dynamic environment;Journal of Intelligent and Robotic Systems;1998

5. A neural network-based classification of environment dynamics models for compliant control of manipulation robots;IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics);1998

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