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Neural Network Force Control for Industrial Robots

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Abstract

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

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Chung-Hsing University, Taichung, Taiwan, R.O.C

    Shih-Tin Lin & Shyi-Jang Tzeng

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  1. Shih-Tin Lin
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  2. Shyi-Jang Tzeng
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Lin, ST., Tzeng, SJ. Neural Network Force Control for Industrial Robots. Journal of Intelligent and Robotic Systems 24, 253–268 (1999). https://doi.org/10.1023/A:1008093719860

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