Grasping Control of a Robot Hand by Reinforcement Learning
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- Sugio Noboru
- The University of Tokushima Shikoku Instrumentation Co., Ltd.
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- Kinouchi Yohsuke
- The University of Tokushima
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- Shirai Fumio
- Shikoku Instrumentation Co., Ltd.
Bibliographic Information
- Other Title
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- 強化学習によるロボットハンドの把握制御
- キョウカ ガクシュウ ニ ヨル ロボットハンド ノ ハアク セイギョ
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Description
It is very useful to apply a reinforcement learning for controlling a robot hand with tactile sensors which can grasp and manipulate an object delicately like a human hand. A reinforcement learning based on trial and error is proposed here, which is expected to learn autonomously the optimum manipulation from experiences. In computer simulations, the learning algorithm is applied to controlling a simple hand with two fingers and four fingers to investigate its validity . As a result, it has acquired autonomously almost the optimum control for the manipulation of the hand to grasp and convey an object. Therefore, the learning algorithm proposed may be useful basically for controlling a robot hand.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 121 (4), 710-717, 2001
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204610715904
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- NII Article ID
- 130006845621
- 10007450827
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 5725636
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed