TY - GEN
T1 - Fall Prediction of legged robots based on energy state and its implication of balance augmentation
T2 - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
AU - Li, Zhibin
AU - Zhou, Chengxu
AU - Castano, Juan
AU - Xin, Wang
AU - Negrello, Francesca
AU - Tsagarakis, Nikos G.
AU - Caldwell, Darwin G.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/29
Y1 - 2015/6/29
N2 - In this paper, we propose an Energy based Fall Prediction (EFP) which observes the real-time balance status of a humanoid robot during standing. The EFP provides an analytic and quantitative measure of the level of balance. Both simulation and experimental studies were conducted and compared with the previously proposed indicators, such as Capture Point (CP) and Foot Rotation Indicator (FRI). The EFP also suggests the balance augmentation by active foot tilting to create larger potential barriers. As a proof of concept, a hybrid balance controller was designed to stabilize the robot including under-actuation phases so the robot can also balance with shoes. Our study reveals that both EFP and CP successfully predict falling about 0.2s in advance for the tested robot, while the FRI fails due to the light weight of the foot and limited resolution of the force/torque measurement.
AB - In this paper, we propose an Energy based Fall Prediction (EFP) which observes the real-time balance status of a humanoid robot during standing. The EFP provides an analytic and quantitative measure of the level of balance. Both simulation and experimental studies were conducted and compared with the previously proposed indicators, such as Capture Point (CP) and Foot Rotation Indicator (FRI). The EFP also suggests the balance augmentation by active foot tilting to create larger potential barriers. As a proof of concept, a hybrid balance controller was designed to stabilize the robot including under-actuation phases so the robot can also balance with shoes. Our study reveals that both EFP and CP successfully predict falling about 0.2s in advance for the tested robot, while the FRI fails due to the light weight of the foot and limited resolution of the force/torque measurement.
UR - https://www.scopus.com/pages/publications/84938275015
U2 - 10.1109/ICRA.2015.7139908
DO - 10.1109/ICRA.2015.7139908
M3 - 会议稿件
AN - SCOPUS:84938275015
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 5094
EP - 5100
BT - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 May 2015 through 30 May 2015
ER -