Výsledky vyhledávání - "Yoshihisa Ijiri"

Robotic Learning From Advisory and Adversarial Interactions Using a Soft Wrist

Autor: Chisato Nakashima, Kazutoshi Tanaka, Yoshihisa Ijiri, Masashi Hamaya, Yoshiya Shibata, Felix von Drigalski

Publikováno v: IEEE Robotics and Automation Letters. 6:3878-3885

In this letter, we developed a novel learning framework from physical human-robot interactions. Owing to human domain knowledge, such interactions can be useful for facilitation of learning. However, applying numerous interactions for training data m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fd9d06de9ea52ac81f0b563f1c71718a
https://doi.org/10.1109/lra.2021.3067232

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Iterative Backpropagation Disturbance Observer with Forward Dynamics Model

Autor: Felix von Drigalski, Masashi Hamaya, Kazutoshi Tanaka, Takayuki Murooka, Yoshihisa Ijiri

Publikováno v: CASE

Disturbance Observer (DOB) has been widely used for robotic applications to eliminate various kinds of disturbances. Recently, learning-based DOB has attracted significant attention as it can deal with complex robotic systems. In this study, we propo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cc4357b02b2614f51516cd3718e93650
https://doi.org/10.1109/case49439.2021.9551455

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Precise Multi-Modal In-Hand Pose Estimation using Low-Precision Sensors for Robotic Assembly

Autor: Ryo Yonetani, Yoshihisa Ijiri, Kazutoshi Tanaka, Yifei Huang, Masashi Hamaya, Hayashi Kennosuke, Felix von Drigalski

Publikováno v: ICRA

In industrial assembly tasks, the in-hand pose of grasped objects needs to be known with high precision for subsequent manipulation tasks such as insertion. This problem (in-hand-pose estimation) has traditionally been addressed using visual recognit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::47bc8ea22f0905f77923a32544afb5e9
https://doi.org/10.1109/icra48506.2021.9561222

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Learning Soft Robotic Assembly Strategies from Successful and Failed Demonstrations

Autor: Felix von Drigalski, Yoshiya Shibata, Masashi Hamaya, Robert Lee, Kazutoshi Tanaka, Chisato Nakashima, Takamitsu Matsubara, Yoshihisa Ijiri

Publikováno v: IROS

Physically soft robots are promising for robotic assembly tasks as they allow stable contacts with the environment. In this study, we propose a novel learning system for soft robotic assembly strategies. We formulate this problem as a reinforcement l

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0ed90c8becf5c9a24e06acab92de6d93
https://doi.org/10.1109/iros45743.2020.9341504

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