Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction
For natural human-robot interaction, a robot must understand human intent expressed not only through language but also through nonverbal signals such as gestures and gaze. However, current robot policies rely on language instructions as the sole interface for conveying intent, leaving nonverbal signals unused and placing the full burden of communication. In this work, we present EDITH, a robot framework that captures the human's nonverbal signals through continuous streams of first-person view and gaze from smart glasses, and uses them alongside language instructions as inputs to the robot policy. Our hardware system streams the human's first-person view, gaze, and speech to the robot in ...
| Authors | Dongjun Lee, Juheon Choi, Dong Kyu Shin et al. |
|---|---|
| Primary category | cs.RO |
| Published | 9 June 2026 |
| Last updated at source | 9 June 2026 |
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