# 带自适应步态时序的容错行走学习

> 原文链接：https://robotics.hellobike.com/papers/2026-08-07-2608-07328
> 频道：papers | 更新日期：2026-08-07 | 标签：arxiv, cs.RO
> 核心摘要：针对执行器功率损失下的四足容错行走，提出带潜表示对齐和可学习步频的深度强化学习，并在仿真与实机验证。

# 带自适应步态时序的容错行走学习

::: v-pre
> 原文链接：[Learning Fault-Tolerant Locomotion with Adaptive Gait Timing](https://arxiv.org/abs/2608.07328)（arXiv 2608.07328 · 发布日期：2026-08-07）

**Learning Fault-Tolerant Locomotion with Adaptive Gait Timing**

针对执行器功率损失下的四足容错行走，提出带潜表示对齐和可学习步频的深度强化学习，并在仿真与实机验证。

## 核心要点

- 硬件故障会迫使腿式机器人快速重组协调和步态时序，以保持稳定与机动性。
- 采用非对称 actor-critic，训练时 critic 使用特权信息，actor 从本体感知重构潜表示。
- 引入潜表示对齐损失，并将可学习步态频率加入动作空间以自适应退化与地形。
- 在不平地形高保真仿真和 68 kg 四足机器人平地实机实验中进行了验证。

**验证范围与局限**：验证范围为不平地形高保真仿真和平地上的 68 kg 四足机器人实机实验。

## 英文摘要 (Abstract)

Hardware failures require legged robots to rapidly reorganize coordination and gait timing to maintain stability and mobility. This is particularly challenging for larger quadrupeds, where increased mass and tighter actuation limits reduce the feasibility of aggressive, high-frequency compensation strategies often observed on smaller platforms. In this work, we propose a deep reinforcement learning approach for fault-tolerant locomotion under actuator power loss. The method employs an asymmetric actor-critic architecture in which the critic has access to privileged information during training, while the actor learns to reconstruct a corresponding latent representation from proprioceptive observations. We introduce a latent-alignment loss that encourages consistency between actor and critic representations. Additionally, we augment the action space with a learnable gait frequency parameter, enabling adaptive gait timing in response to terrain variations and actuator degradation without predefined faulty-leg strategies. The approach is validated in high-fidelity simulation on uneven terrain and real-world experiments on flat ground using a 68 kg quadruped robot.

作者：Giovanbattista Gravina, Luca Rossini, Carlo Rizzardo, Arturo Laurenzi, Nikos G. Tsagarakis
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## 原始参考来源 (Sources)

- [arXiv 2608.07328：Learning Fault-Tolerant Locomotion with Adaptive Gait Timing](https://arxiv.org/abs/2608.07328)