EgoRecovery: Acquiring Failure Recovery Ability Through Human Recovery Demonstration
Robust embodied robots should be able to recover from failures and retry tasks in order to operate reliably in unstructured and noisy real-world environments. Achieving this capability requires training policies on data that captures recovery behaviors. However, collecting such data through robot teleoperation is difficult to scale, as it is time-consuming to induce diverse failure states, perform corrective actions, and reset the environment. This challenge is further exacerbated by the high diversity of failure modes, which demands substantially more recovery data than success demonstrations. In this work, we show that egocentric human data capturing failure recovery processes provides ...
| Authors | Zuhao Ge, Yuchen Zhou, Weitao Zhou et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 July 2026 |
| Last updated at source | 23 July 2026 |
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