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Applications of Back Propagation Neural Networks to Robot Position Control

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Proceedings of the Twenty-Ninth International Matador Conference

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Summary

A method using neural network techniques for solving picking-up problems for robotic manipulators is presented in this article. An error back propagation network is used twice to process an image of a randomly placed object in order to find the gripping point and to obtain the required joint angles of the robot arms. Techniques of probabilistic and periodic coding are employed to improve generalisation ability of the network.

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References

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Author information

Authors and Affiliations

  1. University of Liverpool, UK

    C. Lee

Authors
  1. C. Lee
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Editor information

Editors and Affiliations

  1. Division of Manufacturing and Machine Tools, Department of Mechanical Engineering, UMIST, UK

    J. Atkinson , G. Barrow , M. Burdekin , N. R. Chitkara  & R. G. Hannam , , ,  & 

Copyright information

© 1992 Department of Mechanical Engineering University of Manchester Institute of Science and Technology

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Lee, C. (1992). Applications of Back Propagation Neural Networks to Robot Position Control. In: Atkinson, J., Barrow, G., Burdekin, M., Chitkara, N.R., Hannam, R.G. (eds) Proceedings of the Twenty-Ninth International Matador Conference. Palgrave, London. https://doi.org/10.1007/978-1-349-12433-6_20

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  • DOI: https://doi.org/10.1007/978-1-349-12433-6_20

  • Publisher Name: Palgrave, London

  • Print ISBN: 978-1-349-12435-0

  • Online ISBN: 978-1-349-12433-6

  • eBook Packages: EngineeringEngineering (R0)

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