SOURCE-LINKED INTELLIGENCE
Visual Cue Guided Video Planning for Generalizable Robot Navigation
Generative video models can serve as a promising backbone for robot navigation by predicting future observations as video plans. Recent approaches often condition video planning on short-horizon guidance and recover geometric waypoints through scene reconstruction, leaving longer-horizon planning and precise video-to-action translation less explored. We present CueNav, a video model-based navigation framework combining visual cue guided video planning with an embodiment-specific Inverse-Dynamics Model (IDM). As visual cues, we use a Bird's-Eye View (BEV) map to convey global task context and r
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T07:11:21.000Z
First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.