Neural Network Force Control for Industrial Robots

Authors:
Shih-Tin Lin;Shyi-Jang Tzeng
Affiliations:
Department of Mechanical Engineering, National Chung-Hsing University, Taichung, Taiwan, R.O.C.;Department of Mechanical Engineering, National Chung-Hsing University, Taichung, Taiwan, R.O.C.
Venue:
Journal of Intelligent and Robotic Systems
Year:
1999

Citing 6
Cited 1

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Motion and force control of coordinated robots during constrained motion tasks

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Abstract

In this paper, we present a hierarchical force control framework consisting of a high level control system based onneural network and the existing motion control system of a manipulator in the low level. Inputs of the neural network are thecontact force error and estimated stiffness of the contacted environment. The output of the neural network is the positioncommand for the position controller of industrial robots. A MITSUBISHI MELFA RV-M1 industrial robot equipped with aBL Force/Torque sensor is utilized for implementing the hierarchical neural network force control system. Successfulexperiments for various contact motions are carried out. Additionally, the proposed neural network force controller togetherwith the master/slave control method are used in dual-industrial robot systems. Successful experiments are carried out for thedual-robot system handling an object.