LMPath: Language-Mediated Priors and Path Generation for Aerial Exploration
Traditional autonomous UAV search missions rely on geometric coverage patterns that ignore the semantic context of the target, leading to significant time waste in large-scale environments. In this paper we present LMPath, a pipeline for generating language-mediated exploration priors for Unmanned Aerial Vehicle (UAV) search missions that leverages semantics. Given a basic geofence and an object of interest prompt, LMPath uses generative language models to determine what regions of the environment should contain that object and a foundation vision model ran over satellite imagery to segment sub-regions that form the exploration prior. This prior can then be used to generate UAV paths with...
| Authors | Jonathan A. Diller, Fernando Cladera, Camillo J. Taylor et al. |
|---|---|
| Primary category | cs.RO |
| Published | 13 May 2026 |
| Last updated at source | 13 May 2026 |
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