Recent advances in quadrupedal robots have demonstrated impressive agility and the ability to traverse diverse terrains. However, hardware issues, such as motor overheating or joint locking, may occur during long-distance walking or traversing through rough terrains leading to locomotion failures. Although several studies have proposed fault-tolerant control methods for quadrupedal robots, there are still challenges in traversing unstructured terrains. In this paper, we propose DreamFLEX, a robust fault-tolerant locomotion controller that enables a quadrupedal robot to traverse complex environments even under joint failure conditions. DreamFLEX integrates an explicit failure estimation and modulation network that jointly estimates the robot's joint fault vector and utilizes this information to adapt the locomotion pattern to faulty conditions in real-time, enabling quadrupedal robots to maintain stability and performance in rough terrains. Experimental results demonstrate that DreamFLEX outperforms existing methods in both simulation and real-world scenarios, effectively managing hardware failures while maintaining robust locomotion performance.

翻译：近年来，四足机器人领域取得了显著进展，展现出令人印象深刻的敏捷性以及穿越多样化地形的能力。然而，在长距离行走或穿越崎岖地形时，可能会出现硬件问题，例如电机过热或关节锁死，从而导致运动失败。尽管已有若干研究提出了针对四足机器人的容错控制方法，但在穿越非结构化地形方面仍存在挑战。本文提出DreamFLEX，一种鲁棒的容错运动控制器，使四足机器人即使在关节故障条件下也能穿越复杂环境。DreamFLEX集成了一个显式的故障估计与调制网络，该网络联合估计机器人的关节故障向量，并利用该信息实时调整运动模式以适应故障条件，从而使四足机器人能够在崎岖地形中保持稳定性和性能。实验结果表明，无论是在仿真还是真实世界场景中，DreamFLEX均优于现有方法，能够有效管理硬件故障，同时保持鲁棒的运动性能。