書誌事項
- タイトル別名
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- Locomotion Controller of SHIKYAKU Robot based on Associative Memory
抄録
<p>For autonomous hexapedal locomotion of a legged robot, SHIKYAKU, we developed a teaching playback system. Since the mechanism of SHIKYAKU is based on the extension and flexion of fingers, motion patterns of the robot for walking and climbing are taught with finger through LeapMotion. The robot records the motion patterns as attractors. At the same time, the robot also records the sensor data. Thus the robot is allowed to have the motion attractors corresponding to the environment. In the teaching playback phase for the autonomous hexapedal locomotion, we use two feedforward neural network sequentially. The first one is for identifying the environment from the senser inputs. The second one is so-colded an associative memory for deciding locomotive motions. Through simulation experiments, we show that the robot is enabled to walk on the flat plane and climb an obstacle autonomously.</p>
収録刊行物
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- ロボティクス・メカトロニクス講演会講演概要集
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ロボティクス・メカトロニクス講演会講演概要集 2017 (0), 1P1-C08-, 2017
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390282680917345536
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- NII論文ID
- 130006220437
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- ISSN
- 24243124
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可