Contact-Rich Manipulation of a Flexible Object based on Deep Predictive Learning using Vision and Tactility

Hideyuki Ichiwara, Hiroshi Ito, Kenjiro Yamamoto, Hiroki Mori, Tetsuya Ogata

研究成果: Conference contribution

抄録

We achieved contact-rich flexible object manipulation, which was difficult to control with vision alone. In the unzipping task we chose as a validation task, the gripper grasps the puller, which hides the bag state such as the direction and amount of deformation behind it, making it difficult to obtain information to perform the task by vision alone. Additionally, the flexible fabric bag state constantly changes during operation, so the robot needs to dynamically respond to the change. However, the appropriate robot behavior for all bag states is difficult to prepare in advance. To solve this problem, we developed a model that can perform contact-rich flexible object manipulation by real-time prediction of vision with tactility. We introduced a point-based attention mechanism for extracting image features, softmax transformation for predicting motions, and convolutional neural network for extracting tactile features. The results of experiments using a real robot arm revealed that our method can realize motions responding to the deformation of the bag while reducing the load on the zipper. Furthermore, using tactility improved the success rate from 56.7% to 93.3% compared with vision alone, demonstrating the effectiveness and high performance of our method.

本文言語English
ホスト出版物のタイトル2022 IEEE International Conference on Robotics and Automation, ICRA 2022
出版社Institute of Electrical and Electronics Engineers Inc.
ページ5375-5381
ページ数7
ISBN(電子版)9781728196817
DOI
出版ステータスPublished - 2022
イベント39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States
継続期間: 2022 5月 232022 5月 27

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷版)1050-4729

Conference

Conference39th IEEE International Conference on Robotics and Automation, ICRA 2022
国/地域United States
CityPhiladelphia
Period22/5/2322/5/27

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 人工知能
  • 電子工学および電気工学

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