提出三层次控制框架，提升机器人抗扰与故障容错能力
A Three-Level Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
- 用移动时域扩展状态观测器估计全身动态不确定性
- 三层次架构同时考虑有无扰动的运动规划，增强抗干扰能力
- 在仿真与实测中验证了对扰动和故障的强鲁棒性
本文提出一种控制框架，以增强腿式机器人在模型不确定性、外部扰动和故障情况下的稳定性与鲁棒性。该框架通过全状态反馈估计算法，对机器人全身动力学中的不确定性进行估计与补偿。首先，提出一种新型移动时域扩展状态观测器（MH-ESO），用于估计不确定性并抑制腿式系统中的噪声，可嵌入框架实现扰动补偿。其次，引入三层次全身扰动抑制控制框架（T-WB-DRC），不同于以往两层次方法，该框架同时考虑无扰动与有扰动下的全身动力学规划，显著提升载荷运输能力、外部扰动抑制能力及故障容错性能。第三，基于Gazebo仿真平台对人形与四足机器人进行了测试，验证了T-WB-DRC的有效性与通用性。最后，通过四足机器人大量实验，在多种扰动条件下验证了该系统的鲁棒性与稳定性。
原文摘要 · Abstract (English)
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.
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