A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots

TL;DR

This paper tackles the challenge of maintaining stability for legged robots in the presence of model uncertainties, external disturbances, and faults. It introduces a three-level whole-body disturbance rejection control framework (T-WB-DRC) that integrates a moving horizon extended state observer (MH-ESO) for uncertainty estimation, a robust model predictive control (MPC) mid-level planner, and a hierarchical low-level controller. The MH-ESO enhances noise robustness over a traditional ESO, enabling effective disturbance compensation, while the robust MPC accounts for uncertainties in the centroidal dynamics, improving payload handling, disturbance rejection, and fault tolerance. Simulations on humanoid and quadruped models and real-world experiments on a Unitree A1 validate the framework’s improvements in robustness, stability, and fault tolerance across diverse disturbance scenarios, including payloads and terrain variability.

Abstract

This paper presents a control framework designed to enhance the stability and robustness of legged robots in the presence of uncertainties, including model uncertainties, external disturbances, and faults. The framework enables the full-state feedback estimator to estimate and compensate for uncertainties in the whole-body dynamics of the legged robots. First, we propose a novel moving horizon extended state observer (MH-ESO) to estimate uncertainties and mitigate noise in legged systems, which can be integrated into the framework for disturbance compensation. Second, we introduce a three-level whole-body disturbance rejection control framework (T-WB-DRC). Unlike the previous two-level approach, this three-level framework considers both the plan based on whole-body dynamics without uncertainties and the plan based on dynamics with uncertainties, significantly improving payload transportation, external disturbance rejection, and fault tolerance. Third, simulations of both humanoid and quadruped robots in the Gazebo simulator demonstrate the effectiveness and versatility of T-WB-DRC. Finally, extensive experimental trials on a quadruped robot validate the robustness and stability of the system when using T-WB-DRC under various disturbance conditions.

Figures (17)

• Figure 1: A block diagram of a typical two-level control framework for legged robots.
• Figure 2: Block diagram of the proposed T-WB-DRC.
• Figure 3: Block diagram of three-level control in T-WB-DRC.
• Figure 4: Frobenius norm of the uncertainties $\hat{f}$ estimated by MH-ESO when the robot, carrying a 10kg load, is standing in place.
• Figure 5: The Frobenius norms of the uncertainties estimated by MH-ESO or ESO.