Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid

Z. Li; C. Zhou; J. Castano; Xin Wang; F. Negrello; N. G. Tsagarakis; D. G. Caldwell

doi:10.1109/ICRA.2015.7139908

Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid

Z. Li, C. Zhou, J. Castano, Xin Wang, F. Negrello, N. G. Tsagarakis, D. G. Caldwell

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

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.

Original language	English
Title of host publication	2015 IEEE International Conference on Robotics and Automation (ICRA)
Publisher	Institute of Electrical and Electronics Engineers
Pages	5094-5100
Number of pages	7
ISBN (Print)	978-1-4799-6923-4
DOIs	https://doi.org/10.1109/ICRA.2015.7139908
Publication status	Published - 1 May 2015

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10.1109/ICRA.2015.7139908

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7139908

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Li, Z., Zhou, C., Castano, J., Wang, X., Negrello, F., Tsagarakis, N. G., & Caldwell, D. G. (2015). Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid. In 2015 IEEE International Conference on Robotics and Automation (ICRA) (pp. 5094-5100). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICRA.2015.7139908

@inproceedings{7cbb7782af664c94bf1d773767c8a364,

title = "Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid",

abstract = "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.",

author = "Z. Li and C. Zhou and J. Castano and Xin Wang and F. Negrello and Tsagarakis, {N. G.} and Caldwell, {D. G.}",

year = "2015",

month = may,

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doi = "10.1109/ICRA.2015.7139908",

language = "English",

isbn = "978-1-4799-6923-4",

pages = "5094--5100",

booktitle = "2015 IEEE International Conference on Robotics and Automation (ICRA)",

publisher = "Institute of Electrical and Electronics Engineers",

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Li, Z, Zhou, C, Castano, J, Wang, X, Negrello, F, Tsagarakis, NG & Caldwell, DG 2015, Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid. in 2015 IEEE International Conference on Robotics and Automation (ICRA). Institute of Electrical and Electronics Engineers, pp. 5094-5100. https://doi.org/10.1109/ICRA.2015.7139908

Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid. / Li, Z.; Zhou, C.; Castano, J. et al.
2015 IEEE International Conference on Robotics and Automation (ICRA). Institute of Electrical and Electronics Engineers, 2015. p. 5094-5100.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid

AU - Li, Z.

AU - Zhou, C.

AU - Castano, J.

AU - Wang, Xin

AU - Negrello, F.

AU - Tsagarakis, N. G.

AU - Caldwell, D. G.

PY - 2015/5/1

Y1 - 2015/5/1

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.

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DO - 10.1109/ICRA.2015.7139908

M3 - Conference contribution

SN - 978-1-4799-6923-4

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BT - 2015 IEEE International Conference on Robotics and Automation (ICRA)

PB - Institute of Electrical and Electronics Engineers

ER -

Fall Prediction of legged robots based on energy state and its implication of balance augmentation: A study on the humanoid

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