TY - GEN
T1 - Understand Human Walking Through a 2D Inverted Pendulum Model
AU - Ye, Linqi
AU - Chen, Xuechao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - This paper gives some macroscopic understandings on human walking about the limitations on walking speed and step length, the reachable region, capture region, and disturbance recovery through a 2D inverted pendulum model. Our concern is the most basic problems in human walking, such as what are the limitations on walking speed and step length, how people change speed during step-to-step transition, and how people prevent a fall. The concept of walking orbit is proposed as a tool to study these problems. It describes the walking motion in the state space under walking constraints, giving us an intuitive way to study human walking during a step and switch between steps. The model has a point mass on the hip and two massless legs. The two dominant control inputs, hip and ankle actuation are idealized into a free determined foot placement and an impulsive push off. Based on this model, some quantitative and qualitative analysis are given, leading to some macroscopic understandings on human walking. Although this paper does not talk about any details on how to realize the control for a real biped robot, it may serve as a helpful guide for biped robot design and control in the future.
AB - This paper gives some macroscopic understandings on human walking about the limitations on walking speed and step length, the reachable region, capture region, and disturbance recovery through a 2D inverted pendulum model. Our concern is the most basic problems in human walking, such as what are the limitations on walking speed and step length, how people change speed during step-to-step transition, and how people prevent a fall. The concept of walking orbit is proposed as a tool to study these problems. It describes the walking motion in the state space under walking constraints, giving us an intuitive way to study human walking during a step and switch between steps. The model has a point mass on the hip and two massless legs. The two dominant control inputs, hip and ankle actuation are idealized into a free determined foot placement and an impulsive push off. Based on this model, some quantitative and qualitative analysis are given, leading to some macroscopic understandings on human walking. Although this paper does not talk about any details on how to realize the control for a real biped robot, it may serve as a helpful guide for biped robot design and control in the future.
UR - http://www.scopus.com/inward/record.url?scp=85062285630&partnerID=8YFLogxK
U2 - 10.1109/HUMANOIDS.2018.8625057
DO - 10.1109/HUMANOIDS.2018.8625057
M3 - Conference contribution
AN - SCOPUS:85062285630
T3 - IEEE-RAS International Conference on Humanoid Robots
SP - 340
EP - 345
BT - 2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018
PB - IEEE Computer Society
T2 - 18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018
Y2 - 6 November 2018 through 9 November 2018
ER -