Centroidal Trajectory Generation and Stabilization based on Preview Control for Humanoid Multi-contact Motion

TL;DR

This paper introduces a computationally efficient centroidal trajectory generation and stabilization method for humanoid robots performing multi-contact motions, combining preview control with feedback and wrench distribution for robustness and constraint satisfaction.

Contribution

It presents a novel approach that reduces computational cost by replacing model predictive control with preview control, enabling stable multi-contact motions in humanoid robots.

Findings

Stable multi-contact motions demonstrated in simulation.

Significant reduction in computational cost.

Enhanced robustness through centroidal state feedback.

Abstract

Multi-contact motion is important for humanoid robots to work in various environments. We propose a centroidal online trajectory generation and stabilization control for humanoid dynamic multi-contact motion. The proposed method features the drastic reduction of the computational cost by using preview control instead of the conventional model predictive control that considers the constraints of all sample times. By combining preview control with centroidal state feedback for robustness to disturbances and wrench distribution for satisfying contact constraints, we show that the robot can stably perform a variety of multi-contact motions through simulation experiments.