让机器人在电机故障时仍能稳定移动并完成抓取任务
FT-WBC: Learning Fault-Tolerant Whole-Body Control for Legged Loco-Manipulation

- 分上下身控制,通过故障估计算法识别损坏关节
- 根据故障情况自动调整身体姿态,避免摔倒且最大化手臂活动范围
- 仿真与实机测试均证明有效,无需训练直接适配真实机器人
腿式操作机器人结合了腿部平台的移动性与机械臂的操作能力。然而,手臂引起的质心偏移和动态扰动使系统在执行器故障时更容易失稳,可能导致跌倒、任务失败或安全风险。现有容错控制方法主要关注运动本身,未解决故障下全身稳定与手臂可达性的耦合问题。为此,我们提出FT-WBC,一种面向腿式操作的容错协同控制框架。该框架采用解耦的上下身策略架构,引入故障估计算法(FE)和姿态自适应模块(PAM)。FE基于下肢本体感知历史预测故障关节,PAM则利用故障信息调整由臂策略生成的基座姿态规划,将潜在不稳定的姿态请求转化为安全可执行的基座指令。通过这一故障感知的姿态自适应机制,FT-WBC可在执行器故障下合成补偿性步态,在保持全身稳定的同时尽可能保留手臂工作空间。仿真与真实实验表明,该方法显著提升了故障下的存活率与可用工作空间,并实现零样本迁移至真实腿式操作机器人。
原文摘要 · Abstract (English)
Legged manipulators combine the mobility of legged platforms with the manipulation capability of robotic arms. However, arm-induced Center-of-Mass shifts and dynamic disturbances make the system more prone to instability under actuator failures, potentially leading to falls, task failures, or safety risks. Existing fault-tolerant control methods mainly focus on locomotion alone, leaving the coupled problem of whole-body stability and arm reachability in fault-tolerant loco-manipulation largely unaddressed. To bridge this gap, we propose FT-WBC, a fault-tolerant loco-manipulation framework for robust whole-body control of legged manipulators under actuator failures. FT-WBC adopts a decoupled upper- and lower-body policy architecture and introduces two key modules: a Fault Estimator (FE) and a Posture Adaptation Module (PAM). The FE predicts faulty joints from lower-body proprioceptive histories, while the PAM uses this fault information to adapt the base posture plan generated by the arm policy, converting potentially unstable posture requests into safe and executable base posture commands. Through this fault-aware posture adaptation mechanism, FT-WBC synthesizes compensatory gaits under actuator failures and preserves as much arm workspace as possible while maintaining whole-body stability. Simulation and real-world experiments show that FT-WBC significantly improves survival rate and workspace under weakening or locked failures, and transfers zero-shot to a real legged manipulator in the real world.
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