TY - GEN
T1 - Estimation of Ground Reaction Forces Based on Knee Joint Acceleration of Lower-Limb Exoskeletons
AU - Hsiao, Tesheng
AU - Yip, Kinglam
AU - Chiu, Yun Jen
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/11/4
Y1 - 2020/11/4
N2 - The distribution of ground reaction forces (GRFs) on the soles of a legged robot changes the location of center of pressure (CoP) or zero moment point (ZMP) during walking, which is crucial for maintaining dynamic stability of legged locomotion. In addition, many lower-limb exoskeletons use GRF to detect different phases in a gait cycle as well as the walking intention of the wearer. Therefore, many legged robots and exoskeletons install force or pressure sensors on the feet to measure GRF. However, frequent contact with the ground tends to damage the sensors on the feet, reducing reliability and durability of the robot. In this paper, we propose an on-line GRF estimation method based on knee joint acceleration. We analyze the experimental data and identify features in the knee joint acceleration that are highly correlated to GRF. A linear dynamic model is used to fit experimental data and generate GRF estimates. Then by searching for the desired features in the knee joint acceleration and applying the linear dynamic model, we can online estimate GRF with reasonable accuracy. Consequently, force or pressure sensors on the feet of a robot are no longer required, and reliability of the robotic system can be improved.
AB - The distribution of ground reaction forces (GRFs) on the soles of a legged robot changes the location of center of pressure (CoP) or zero moment point (ZMP) during walking, which is crucial for maintaining dynamic stability of legged locomotion. In addition, many lower-limb exoskeletons use GRF to detect different phases in a gait cycle as well as the walking intention of the wearer. Therefore, many legged robots and exoskeletons install force or pressure sensors on the feet to measure GRF. However, frequent contact with the ground tends to damage the sensors on the feet, reducing reliability and durability of the robot. In this paper, we propose an on-line GRF estimation method based on knee joint acceleration. We analyze the experimental data and identify features in the knee joint acceleration that are highly correlated to GRF. A linear dynamic model is used to fit experimental data and generate GRF estimates. Then by searching for the desired features in the knee joint acceleration and applying the linear dynamic model, we can online estimate GRF with reasonable accuracy. Consequently, force or pressure sensors on the feet of a robot are no longer required, and reliability of the robotic system can be improved.
KW - assistive walking
KW - exoskeleton
KW - ground reaction force
UR - http://www.scopus.com/inward/record.url?scp=85099750011&partnerID=8YFLogxK
U2 - 10.1109/CACS50047.2020.9289732
DO - 10.1109/CACS50047.2020.9289732
M3 - Conference contribution
AN - SCOPUS:85099750011
T3 - 2020 International Automatic Control Conference, CACS 2020
BT - 2020 International Automatic Control Conference, CACS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Automatic Control Conference, CACS 2020
Y2 - 4 November 2020 through 7 November 2020
ER -