Paper ID: 2211.06766

The Study of Complex Human Locomotion Behaviors: From Crawling to Walking

Shengjie Xu, Kevin Mok

This paper uses a simple state machine to develop a control algorithm for controlling an infant humanoid in the context of a simple model system. The algorithm is inspired by a baby who starts learning to stand and walk at 7 to 12 months of age: he or she initially learns to crawl and then, once the lower limb muscles are strong enough, can learn to walk by coming to support his or her upper trunk. Ideally, this algorithm-supported locomotion can take the baby to any desired location: a pile of toys, a tasty snack, or the baby's parents or relatives. In this paper we analyze the crawling stage, the simple 2d bipedal model, and the initial walking form from 8 to 18 months of age, and quantitatively evaluate the ideal kinematics model and simulation results for these stages.

Submitted: Nov 12, 2022