Building a generic architecture for robot hand control

Huan Liu, Thea Iberall, George A. Bekey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

As various dextrous robot hands are designed and built, a major question is how to develop device-independent robot hand controllers. This would allow the low-level control problems to be separated from high level functionality. GeSAM is a generic robot hand controller that is based on a model of human prehensile function. It focuses on the relationship between geometric object primitives and the ways a hand can perform prehensile behaviors. The authors show how the relationship between object primitives and a useful set of grasp modes can be learned by an adaptive neural network. By adding training points as necessary, system performance can be improved, avoiding the tedious job of computing every relationship by hand.

Original languageEnglish (US)
Title of host publicationIEEE Int Conf on Neural Networks
Place of PublicationNew York, NY, USA
PublisherPubl by IEEE
Pages567-574
Number of pages8
StatePublished - 1988
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Liu, H., Iberall, T., & Bekey, G. A. (1988). Building a generic architecture for robot hand control. In IEEE Int Conf on Neural Networks (pp. 567-574). Publ by IEEE.