TY - GEN
T1 - A Compliant Five-Bar Legged Mechanism for Heavy-Load Legged Robots by Using Magneto-Rheological Actuators
AU - Chen, Guangzeng
AU - Ran, Jiangtao
AU - Bai, Chenguang
AU - Jie, Pengyu
AU - Lou, Yunjiang
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this paper, a compliant five-bar leg mechanism is proposed, designed and manufactured for heavy-load legged robots, by using two magneto-rheological actuators (MRAs) that are capable of offering a maximal torque of 78Nm. To address the rate-dependent hysteresis of the MRA, a hybrid rate-dependent hysteresis model is derived based on the idea of mappings between different hysteresis loops. With integrating the classical Preisach model and the NARX neural network, the hybrid model is able to model hysteresis nonlinearity of the magneto-rheological clutch (MRC). It is then used to estimate and control the output torque of the MRA at the absent of external force/torque sensors. High fidelity force control and variable compliance of the leg mechanism are realized and validated in various experiments with using the MRAs.
AB - In this paper, a compliant five-bar leg mechanism is proposed, designed and manufactured for heavy-load legged robots, by using two magneto-rheological actuators (MRAs) that are capable of offering a maximal torque of 78Nm. To address the rate-dependent hysteresis of the MRA, a hybrid rate-dependent hysteresis model is derived based on the idea of mappings between different hysteresis loops. With integrating the classical Preisach model and the NARX neural network, the hybrid model is able to model hysteresis nonlinearity of the magneto-rheological clutch (MRC). It is then used to estimate and control the output torque of the MRA at the absent of external force/torque sensors. High fidelity force control and variable compliance of the leg mechanism are realized and validated in various experiments with using the MRAs.
UR - https://www.scopus.com/pages/publications/85124344010
U2 - 10.1109/IROS51168.2021.9636256
DO - 10.1109/IROS51168.2021.9636256
M3 - 会议稿件
AN - SCOPUS:85124344010
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 8217
EP - 8224
BT - 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Y2 - 27 September 2021 through 1 October 2021
ER -