TY - GEN
T1 - Identification and validation of the dynamic model of a tendon-driven anthropomorphic finger
AU - Li, Junnan
AU - Chen, Lingyun
AU - Ringwald, Johannes
AU - Fortunić, Edmundo Pozo
AU - Ganguly, Amartya
AU - Haddadin, Sami
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This study addresses the absence of an identification framework to quantify a comprehensive dynamic model of human and anthropomorphic tendon-driven fingers, which is necessary to investigate the physiological properties of human fingers and improve the control of robotic hands. First, a generalized dynamic model was formulated, which takes into account the inherent properties of such a mechanical system. This includes rigid-body dynamics, coupling matrix, joint viscoelasticity, and tendon friction. Then, we propose a methodology comprising a series of experiments, for step-wise identification and validation of this dynamic model. Moreover, an experimental setup was designed and constructed that features actuation modules and peripheral sensors to facilitate the identification process. To verify the proposed methodology, a 3D-printed robotic finger based on the index finger design of the Dexmart hand was developed, and the proposed experiments were executed to identify and validate its dynamic model. This study could be extended to explore the identification of cadaver hands, aiming for a consistent dataset from a single cadaver specimen to improve the development of musculoskeletal hand models.
AB - This study addresses the absence of an identification framework to quantify a comprehensive dynamic model of human and anthropomorphic tendon-driven fingers, which is necessary to investigate the physiological properties of human fingers and improve the control of robotic hands. First, a generalized dynamic model was formulated, which takes into account the inherent properties of such a mechanical system. This includes rigid-body dynamics, coupling matrix, joint viscoelasticity, and tendon friction. Then, we propose a methodology comprising a series of experiments, for step-wise identification and validation of this dynamic model. Moreover, an experimental setup was designed and constructed that features actuation modules and peripheral sensors to facilitate the identification process. To verify the proposed methodology, a 3D-printed robotic finger based on the index finger design of the Dexmart hand was developed, and the proposed experiments were executed to identify and validate its dynamic model. This study could be extended to explore the identification of cadaver hands, aiming for a consistent dataset from a single cadaver specimen to improve the development of musculoskeletal hand models.
UR - http://www.scopus.com/inward/record.url?scp=85216475934&partnerID=8YFLogxK
U2 - 10.1109/IROS58592.2024.10801538
DO - 10.1109/IROS58592.2024.10801538
M3 - Conference contribution
AN - SCOPUS:85216475934
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 8330
EP - 8337
BT - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
Y2 - 14 October 2024 through 18 October 2024
ER -