SOURCE-LINKED INTELLIGENCE
NavPatch: Evidence-Guided Object-Level Costmap Correction with Vision-Language Models
Mobile robots typically rely on geometric maps for obstacle avoidance and path planning, but the resulting obstacle representation does not always match how an object should affect navigation. A low lying cable may be missed, a flexible curtain may create spurious blockage, and a traffic cone may require an exclusion region larger than its observed footprint. We present NavPatch, an object level correction layer that assigns ADD, REMOVE, or EXTEND to navigation relevant object categories through periodic scene understanding with a vision-language model. Open vocabulary grounding localizes obje
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T14:30:55.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.