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

Author:

Ichiwara Hideyuki1,Ito Hiroshi1,Yamamoto Kenjiro1,Mori Hiroki2,Ogata Tetsuya2

Affiliation:

1. Mechanical Engineering, Research & Development Group, Hitachi, Ltd.,Center for Technology Innovation,Ibaraki,Japan,312-0034

2. School of Fundamental Science and Engineering, Waseda University,Department of Intermedia Art and Science,Tokyo,Japan,169-855

Funder

National Institute of Advanced Industrial Science and Technology

Publisher

IEEE

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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3. ISS/JEM crew-task analysis to support astronauts with intra-vehicular robotics;2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN);2023-08-28

4. Safe Self-Supervised Learning in Real of Visuo-Tactile Feedback Policies for Industrial Insertion;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

5. Multimodal Time Series Learning of Robots Based on Distributed and Integrated Modalities: Verification with a Simulator and Actual Robots;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

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