TY - GEN
T1 - A Novel Foot Contact Probability Estimator for Biped Robot State Estimation
AU - Qin, Mingyue
AU - Yu, Zhangguo
AU - Chen, Xuechao
AU - Huang, Qiang
AU - Fu, Chenglong
AU - Ming, Aiguo
AU - Tao, Chunjing
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - State estimation is an important part of biped robot control, but unreliable foot contact estimation would lead to inaccurate state estimation result. In this paper, to reduce the state estimation error caused by the inaccurate contact estimation, we propose a novel simplified contact probability estimator based on the force/torque sensor mounted on the foot. The contact probability is used to tune the covariance matrices of the extended Kalman filter, and the parameters of the probability estimator are optimized iteratively through minimizing the error between state estimation result and ground truth measurement. The experimental result on BHR-6P biped robot shows that the proposed method can effectively reduce the state estimation error.
AB - State estimation is an important part of biped robot control, but unreliable foot contact estimation would lead to inaccurate state estimation result. In this paper, to reduce the state estimation error caused by the inaccurate contact estimation, we propose a novel simplified contact probability estimator based on the force/torque sensor mounted on the foot. The contact probability is used to tune the covariance matrices of the extended Kalman filter, and the parameters of the probability estimator are optimized iteratively through minimizing the error between state estimation result and ground truth measurement. The experimental result on BHR-6P biped robot shows that the proposed method can effectively reduce the state estimation error.
KW - Bayesian optimization
KW - State estimation
KW - biped robot
KW - extended Kalman filter
KW - probabilistic estimation
UR - http://www.scopus.com/inward/record.url?scp=85096520494&partnerID=8YFLogxK
U2 - 10.1109/ICMA49215.2020.9233715
DO - 10.1109/ICMA49215.2020.9233715
M3 - Conference contribution
AN - SCOPUS:85096520494
T3 - 2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020
SP - 1901
EP - 1906
BT - 2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Mechatronics and Automation, ICMA 2020
Y2 - 13 October 2020 through 16 October 2020
ER -