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Abstract
In this paper, we propose a knowledge sharing oriented approach to enable a robot to reuse other robots' knowledge by adapting itself to the inverse dynamics model of the knowledge-sharing robot. The purpose of this work is to remove the heavy fine-tuning procedure required before using a new robot for a task via reusing other robots' knowledge. We use the Neural Knowledge DNA (NK-DNA) to help robots gain empirical knowledge and introduce a Knowledge Adaption Module (KAM) utilizing the deep neural networks (DNN) for knowledge reuse. The initial experiment shows that the target robot can adapt to the inverse dynamic model of the source robot via our KAM and reuse the knowledge shared by the source robot.
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Authors (4)
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Guixian Li
- Chengdu University, China
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Yufeng Xu
- Chengdu University, China
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Haoxi Zhang
- Chengdu University, China
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2021.2018550
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
CYBERNETICS AND SYSTEMS
no. 53,
pages 520 - 528,
ISSN: 0196-9722 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Li G., Xu Y., Zhang H., Szczerbicki E.: Towards Knowledge Sharing Oriented Adaptive Control// CYBERNETICS AND SYSTEMS -Vol. 53,iss. 5 (2022), s.520-528
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2021.2018550
- Verified by:
- Gdańsk University of Technology
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