Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Felix von Drigalski"'
Publikováno v:
IEEE Access, Vol 10, Pp 99321-99329 (2022)
This study aimed to anticipate fractures of fragile food during robotic food manipulation. Anticipating fractures allows a robot to manipulate ingredients without irreversible failure. Food fracture models investigated in food texture fields explain
Externí odkaz:
https://doaj.org/article/c0047f77bbc54cdca20c42ab52a7d96d
Autor:
Felix von Drigalski, Cristian C. Beltran-Hernandez, Chisato Nakashima, Zhengtao Hu, Shuichi Akizuki, Toshio Ueshiba, Manabu Hashimoto, Kazumi Kasaura, Yukiyasu Domae, Weiwei Wan, Kensuke Harada
Publikováno v:
Advanced Robotics. 36:1213-1227
Autor:
Felix von Drigalski, Kazumi Kasaura, Cristian C. Beltran-Hernandez, Masashi Hamaya, Kazutoshi Tanaka, Takamitsu Matsubara
Publikováno v:
IEEE Robotics and Automation Letters. 7:11942-11949
Autor:
Lotfi El Hafi, Gustavo Alfonso Garcia Ricardez, Felix von Drigalski, Yuki Inoue, Masaki Yamamoto, Takashi Yamamoto
Publikováno v:
Advanced Robotics. 36:533-547
Autor:
Yusaku Nakajima, Masashi Hamaya, Yuta Suzuki, Takafumi Hawai, Felix von Drigalski, Kazutoshi Tanaka, Yoshitaka Ushiku, Kanta Ono
Publikováno v:
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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
Learning-based Manipulation with Explicit and Implicit Dynamics Parameters for Multiple Environments
Publikováno v:
Journal of the Robotics Society of Japan. 39:177-180
Publikováno v:
Journal of the Robotics Society of Japan. 39:609-612
Autor:
Kazutoshi Tanaka, Masashi Hamaya, Devwrat Joshi, Felix von Drigalski, Ryo Yonetani, Takamitsu Matsubara, Yoshihisa Ijiri
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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