SOURCE-LINKED INTELLIGENCE
Towards Embodied Air-Ground Cooperative Object Search: Benchmark, Dataset and Agentic Method
Air-Ground Object Search (AGOS) in urban environments is a challenging embodied task, which requires an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) to jointly search for and verify a specified target vehicle from multi-view visual references. To study this underexplored problem, we introduce AGOS-Bench, the first dedicated benchmark for evaluating whether general-purpose Vision-Language Models (VLMs) can integrate aerial discoveries and ground-level verification through UAV-UGV cooperation. We further provide AGOS-Dataset as the companion resource of exemplary trajectori
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T08:13:00.000Z
First collected: 2026-09-20T20:22:01.598Z. This is not the publication date.