Referring-Aware Visuomotor Policy Learning for Closed-Loop Manipulation
This paper addresses a fundamental problem of visuomotor policy learning for robotic manipulation: how to enhance robustness in out-of-distribution execution errors or dynamically re-routing trajectories, where the model relies solely on the original expert demonstrations for training. We introduce the Referring-Aware Visuomotor Policy (ReV), a closed-loop framework that can adapt to unforeseen circumstances by instantly incorporating sparse referring points provided by a human or a high-level reasoning planner. Specifically, ReV leverages the coupled diffusion heads to preserve standard task execution patterns while seamlessly integrating sparse referring via a trajectory-steering strate...
| Authors | Jiahua Ma, Yiran Qin, Xin Wen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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