Robust Bipedal Locomotion Control Based on Model Predictive Control and Divergent Component of Motion

TL;DR

This paper presents a robust bipedal walking controller combining MPC and DCM concepts, capable of handling uneven terrains and limited stepping areas, verified through simulations.

Contribution

It introduces a unified MPC-based control scheme utilizing CoP, step adjustment, and CMP modulation, generalized for uneven surfaces and different robot control authorities.

Findings

Effective in simulation for uneven terrains

Outperforms existing methods in robustness

Versatile across different robot configurations

Abstract

In this paper, previous works on the Model Predictive Control (MPC) and the Divergent Component of Motion (DCM) for bipedal walking control are extended. To this end, we employ a single MPC which uses a combination of Center of Pressure (CoP) manipulation, step adjustment, and Centroidal Moment Pivot (CMP) modulation to design a robust walking controller. Furthermore, we exploit the concept of time-varying DCM to generalize our walking controller for walking in uneven surfaces. Using our scheme, a general and robust walking controller is designed which can be implemented on robots with different control authorities, for walking on various environments, e.g. uneven terrains or surfaces with a very limited feasible area for stepping. The effectiveness of the proposed approach is verified through simulations on different scenarios and comparison to the state of the art.