Learning Multiple Sensorimotor Units to Complete Compound Tasks using an RNN with Multiple Attractors

Kei Kase, Ryoichi Nakajo, Hiroki Mori, Tetsuya Ogata

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

As the complexity of the robot's tasks increases, we can consider many general tasks in a compound form that consists of shorter tasks. Therefore, for robots to generate various tasks, they need to be able to execute shorter tasks in succession, appropriately to the situation. With the design principle to construct the architecture for robots to execute complex tasks compounded with multiple subtasks, this study proposes a visuomotor-control framework with the characteristics of a state machine to train shorter tasks as sensorimotor units. The design procedure of training framework consists of 4 steps: (1) segment entire task into appropriate subtasks, (2) define subtasks as states and transitions in a state machine, (3) collect subtasks data, and (4) train neural networks: (a) autoencoder to extract visual features, (b) a single recurrent neural network to generate subtasks to realize a pseud-state-machine model with a constraint in hidden values. We implemented this framework on two different robots to allow their performance of repetitive tasks with error-recovery motion, subsequently, confirming the ability of the robot to switch the sensorimotor units from visual input at the attractors of the hidden values created by the constraint.

本文言語English
ホスト出版物のタイトル2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ4244-4249
ページ数6
ISBN(電子版)9781728140049
DOI
出版ステータスPublished - 2019 11
イベント2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China
継続期間: 2019 11 32019 11 8

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems
ISSN(印刷版)2153-0858
ISSN(電子版)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
国/地域China
CityMacau
Period19/11/319/11/8

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

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