A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning

Denz R, Demirci R, Cansev ME, Bliek A, Beckerle P, Rueckert E, Rottmann N (2021)

Publication Type: Conference contribution

Publication year: 2021

Publisher: IEEE

City/Town: NEW YORK

Pages Range: 1109-1115

Conference Proceedings Title: 2021 20TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR)

Event location: , ELECTR NETWORK

DOI: 10.1109/icar53236.2021.9659403

Authors with CRIS profile

Mehmet Ege Cansev Lehrstuhl für Autonome Systeme und Mechatronik Adna Bliek Lehrstuhl für Autonome Systeme und Mechatronik Philipp Beckerle Lehrstuhl für Autonome Systeme und Mechatronik

Involved external institutions

Universität zu Lübeck DE Germany (DE) Montanuniversität Leoben AT Austria (AT)

How to cite

APA:

Denz, R., Demirci, R., Cansev, M.E., Bliek, A., Beckerle, P., Rueckert, E., & Rottmann, N. (2021). A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning. In 2021 20TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR) (pp. 1109-1115). , ELECTR NETWORK: NEW YORK: IEEE.

MLA:

Denz, Robin, et al. "A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning." Proceedings of the 20th International Conference on Advanced Robotics (ICAR), , ELECTR NETWORK NEW YORK: IEEE, 2021. 1109-1115.

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