Paper

Meridian: Metric-Semantic Primitive Matching for Cross-View Geo-Localization Beyond Urban Environments

arXiv:2606.06312v1 Announce Type: new Abstract: Successful robot automation requires accurate global localization to support repeatability, task planning, goal specification, and safe operation. However, reliable localization in GNSS-denied environments remains an open problem. Overhead aerial imagery offers a promising solution, but existing approaches primarily target structured urban environments and have been rarely demonstrated in unstructured natural terrain. Limitations of the state-of-the-art include a reliance on models trained for specific environments, as well as difficulty handlin…

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