Uni-LaViRA: Language-Vision-Robot Actions Translation for Unified Embodied Navigation
Embodied navigation requires an agent to map language and visual observations to a stream of spatial actions that drive a real robot through environments it has never seen. The dominant approach has been to scale vision-language-action (VLA) foundation models on ever-larger collections of robot trajectories. This paper argues that, for navigation specifically, generality can be obtained structurally, not only through data scale. The underlying decision structure of navigation reduces to a single Language-Vision-Robot Actions Translation. The language action emits semantic-level directional command and the vision action emits a pixel-level visual target. Both outputs lie inside the natural...
| Authors | Hongyu Ding, Sizhuo Zhang, Ziming Xu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 26 May 2026 |
| Last updated at source | 26 May 2026 |
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