Study of human walking patterns based on the parameter optimization of a passive dynamic walking robot

Background: The study of human walking patterns mainly focuses on how control affects walking because control schemes are considered to be dominant in human walking.

Objective: This study proposes that not only fine control schemes but also optimized body segment parameters are responsible for humans' low-energy walking.

Methods: A passive dynamic walker provides the possibility of analyzing the effect of parameters on walking efficiency because of its ability to walk without any control. Thus, a passive dynamic walking model with a relatively human-like structure was built, and a parameter optimization process based on the gait sensitivity norm was implemented to determine the optimal mechanical parameters by numerical simulation.

Results: The results were close to human body parameters, thus indicating that humans can walk under a passive pattern based on their body segment parameters. A quasi-passive walking prototype was built on the basis of the optimization results. Experiments showed that a passive robot with optimized parameters could walk on level ground with only a simple hip actuation.

Conclusion: This result implies that humans can walk under a passive pattern based on their body segment parameters with only simple control strategy implying that humans can opt to walk instinctively under a passive pattern.