Learning expert systems for robot fine motion control

The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the authors (1987). EARSA is mainly concerned with the self-discovery of skills by a robot in...

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Bibliographic Details
Published inProceedings IEEE International Symposium on Intelligent Control 1988 pp. 534 - 544
Main Authors Lee, S., Kim, M.H.
Format Conference Proceeding
LanguageEnglish
Published IEEE Comput. Soc. Press 1988
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ISBN9780818620126
0818620129
ISSN2158-9860
DOI10.1109/ISIC.1988.65488

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Summary:The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the authors (1987). EARSA is mainly concerned with the self-discovery of skills by a robot in conjunction with the transfer of human skills to a robot and emphasizes the distinctive difference in perceptual and physical capabilities between a human and a robot. The authors review the theory and mechanism of EARSA, describe the robot fine motion skill learning algorithm formulated on the basis of EARSA, and present the details of simulation on the robot learning of two-dimensional peg-hole insertion skills. The results of simulation indicate the dramatic improvement of performance as a result of skill learning.< >
ISBN:9780818620126
0818620129
ISSN:2158-9860
DOI:10.1109/ISIC.1988.65488