FT-WBC：学习腿式操作任务的容错全身控制
FT-WBC: Learning Fault-Tolerant Whole-Body Control for Legged Loco-Manipulation
AI总结：
针对腿式机械臂在致动器故障下易失稳的问题，提出FT-WBC框架，通过故障估计器和姿态适应模块实现容错全身控制，提升生存率和操作空间。
摘要：
腿式机械臂结合了腿式平台的移动性和机械臂的操作能力。然而，手臂引起的质心偏移和动态扰动使得系统在致动器故障下更容易失稳，可能导致跌倒、任务失败或安全风险。现有的容错控制方法主要关注纯运动，而容错腿式操作中全身稳定性和手臂可达性的耦合问题尚未得到充分解决。为填补这一空白，我们提出FT-WBC，一种用于腿式机械臂在致动器故障下鲁棒全身控制的容错操作框架。FT-WBC采用解耦的上肢和下肢策略架构，并引入两个关键模块：故障估计器（FE）和姿态适应模块（PAM）。FE从下肢本体感受历史中预测故障关节，而PAM利用该故障信息适应由手臂策略生成的基础姿态计划，将潜在不稳定的姿态请求转换为安全可执行的基础姿态指令。通过这种故障感知的姿态适应机制，FT-WBC在致动器故障下合成补偿步态，并在保持全身稳定性的同时尽可能保留手臂工作空间。仿真和真实世界实验表明，FT-WBC在弱化或锁定故障下显著提高了生存率和工作空间，并零样本迁移到真实腿式机械臂上。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
