Scalable closed-form trajectories for periodic and non-periodic human-like walking

TL;DR

This paper introduces a scalable, closed-form framework for generating human-like walking trajectories that adapt to various parameters and conditions, enabling fast simulation and potential robotic applications.

Contribution

The authors present a novel 3LP model and an optimal control method that generate adaptable, human-like walking gaits without tuning or offline data, with solutions that are computationally efficient.

Findings

Framework generates realistic, adaptable walking gaits.

Simulation speeds are orders of magnitude faster than real time.

Applicable to robotics, animation, and real-time simulation.

Abstract

We present a new framework to generate human-like lower-limb trajectories in periodic and non-periodic walking conditions. In our method, walking dynamics is encoded in 3LP, a linear simplified model composed of three pendulums to model falling, swing and torso balancing dynamics. To stabilize the motion, we use an optimal time-projecting controller which suggests new footstep locations. On top of gait generation and stabilization in the simplified space, we introduce a kinematic conversion method that synthesizes more human-like trajectories by combining geometric variables of the 3LP model adaptively. Without any tuning, numerical optimization or off-line data, our walking gaits are scalable with respect to body properties and gait parameters. We can change various parameters such as body mass and height, walking direction, speed, frequency, double support time, torso style, ground clearance and terrain inclination. We can also simulate the effect of constant external dragging forces or momentary perturbations. The proposed framework offers closed-form solutions in all the three stages which enable simulation speeds orders of magnitude faster than real time. This can be used for video games and animations on portable electronic devices with a limited power. It also gives insights for generation of more human-like walking gaits with humanoid robots.