Track-and-Complete: Learning Humanoid Skills from a Single Failed Human Video
Learning humanoid skills from videos typically requires a successful human demonstration, which often demands custom data collection. Although failures have traditionally been treated only as negative examples in robot learning, they can still reveal a usable trajectory prefix before the task fails, as well as the intended outcome. To leverage this information from a failed-attempt video, we propose TRACC, a pipeline that imitates the useful portion of the motion trajectory and then completes the task based on the inferred task outcome. The usable motion prefix serves as prior knowledge until the failure occurs, after which the task-completion reward guides the policy to learn the intende...
| Authors | Sarmad Idrees, Jongeun Choi |
|---|---|
| Primary category | cs.RO |
| Published | 29 September 2026 |
| Last updated at source | 29 September 2026 |
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