Learning control for similar robot motions

Kuu-Young Young*, Shaw Ji Shiah

*Corresponding author for this work

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

1 Scopus citations

Abstract

In this paper, we propose a novel scheme for governing similar robot motions by using learning mechanisms. Most learning schemes need to repeat the learning process each time a new trajectory is encountered. The main reason for this deficiency is that the learning space for executing general motions of multi-joint robot manipulators is too large. To reduce the complexity in learning, we first classify robot motions according to their similarity. A new learning structure, which is motivated by the concept of a motor program, is then used to learn a class of motions. The proposed structure consists mainly of a fuzzy system and a CMAC-type neural network. The fuzzy system is used for learning of the samples in a class of motions. The CMAC-type neural network is used to generalize the parameters of the fuzzy system, which are appropriate for the control of the sampled motions, to deal with the whole class of motions. The learning process is performed only once and the learning effort is dramatically reduced for a wide range of robot motions.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Pages2168-2174
Number of pages7
DOIs
StatePublished - 1 Jan 1995
EventProceedings of the 1995 IEEE International Conference on Robotics and Automation. Part 1 (of 3) - Nagoya, Jpn
Duration: 21 May 199527 May 1995

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2
ISSN (Print)1050-4729

Conference

ConferenceProceedings of the 1995 IEEE International Conference on Robotics and Automation. Part 1 (of 3)
CityNagoya, Jpn
Period21/05/9527/05/95

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  • Cite this

    Young, K-Y., & Shiah, S. J. (1995). Learning control for similar robot motions. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 2168-2174). (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2). https://doi.org/10.1109/ROBOT.1995.525581