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.

翻译：本文提出一种控制框架，旨在增强腿式机器人在存在模型不确定性、外部扰动及故障等不确定因素时的稳定性和鲁棒性。该框架使全状态反馈估计器能够估计并补偿腿式机器人全身动力学中的不确定性。首先，我们提出一种新颖的移动水平扩展状态观测器（MH-ESO），用于估计腿式系统中的不确定性并抑制噪声，该观测器可集成至框架中实现扰动补偿。其次，我们引入一种三层级全身抗扰控制框架（T-WB-DRC）。与先前的双层方法不同，该三层级框架同时考虑了基于无不确定性全身动力学的规划与基于含不确定性动力学的规划，显著提升了负载运输、外部扰动抑制及容错能力。第三，在Gazebo仿真器中对人形与四足机器人进行的仿真实验证明了T-WB-DRC的有效性与普适性。最后，通过在四足机器人上开展的大量实验测试，验证了系统在采用T-WB-DRC框架时于多种扰动条件下的鲁棒性与稳定性。