Trajectory generation for multi-contact momentum-control

TL;DR

This paper introduces a trajectory optimization method using full momentum equations for humanoid robots, enabling complex terrain locomotion with independent contact force control and angular momentum management.

Contribution

It extends previous models by incorporating full momentum dynamics into planning and control, allowing for more versatile and accurate humanoid robot locomotion.

Findings

Fast computational performance in simulations

Effective planning for complex terrains

Good tracking performance in humanoid control

Abstract

Simplified models of the dynamics such as the linear inverted pendulum model (LIPM) have proven to perform well for biped walking on flat ground. However, for more complex tasks the assumptions of these models can become limiting. For example, the LIPM does not allow for the control of contact forces independently, is limited to co-planar contacts and assumes that the angular momentum is zero. In this paper, we propose to use the full momentum equations of a humanoid robot in a trajectory optimization framework to plan its center of mass, linear and angular momentum trajectories. The model also allows for planning desired contact forces for each end-effector in arbitrary contact locations. We extend our previous results on LQR design for momentum control by computing the (linearized) optimal momentum feedback law in a receding horizon fashion. The resulting desired momentum and the associated feedback law are then used in a hierarchical whole body control approach. Simulation experiments show that the approach is computationally fast and is able to generate plans for locomotion on complex terrains while demonstrating good tracking performance for the full humanoid control.