Realtime Limb Trajectory Optimization for Humanoid Running Through Centroidal Angular Momentum Dynamics

TL;DR

This paper introduces a real-time nonlinear limb trajectory optimization method for humanoid robots to enhance stability during running, especially in flight phases, by managing angular momentum dynamics.

Contribution

It presents a novel real-time optimization framework for limb trajectories that accounts for centroidal angular momentum, improving humanoid running stability.

Findings

Optimized limb trajectories improve stability during flight phases.

The method is validated on two humanoid robot models in simulation.

Trajectories enhance robustness of running algorithms.

Abstract

One of the essential aspects of humanoid robot running is determining the limb-swinging trajectories. During the flight phases, where the ground reaction forces are not available for regulation, the limb swinging trajectories are significant for the stability of the next stance phase. Due to the conservation of angular momentum, improper leg and arm swinging results in highly tilted and unsustainable body configurations at the next stance phase landing. In such cases, the robotic system fails to maintain locomotion independent of the stability of the center of mass trajectories. This problem is more apparent for fast and high flight time trajectories. This paper proposes a real-time nonlinear limb trajectory optimization problem for humanoid running. The optimization problem is tested on two different humanoid robot models, and the generated trajectories are verified using a running algorithm for both robots in a simulation environment.