SOURCE-LINKED INTELLIGENCE
Physico-Geospatial Grounded Scene Interpretation for Mobile Robotics
Recent advancements in deep learning allow robotic agents to interact with dynamic and unstructured environments. Of special interest is the integration of physico-geospatial world knowledge into such systems, either by using physics-aware machine learning models, knowledge graphs to model relationships or spatio-temporal and logical reasoning. In the present work, we introduce an approach to augment the output of pre-trained, unmodified VLMs used for scene interpretation by integrating semantic descriptions, OpenStreetMap building data and street information with positional, temporal and metr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-06T14:24:43.000Z
First collected: 2026-09-20T21:12:06.801Z. This is not the publication date.