Event
UAV-SwarmAgent: Generating Multi-UAV Reconnaissance Routes from a Single Sentence
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Oleg Sautenkov and other authors released a paper proposing UAV-SwarmAgent, a hierarchical multi-agent system: an operator issues a task in a single natural-language sentence, and a ground-station agent writes and executes code to convert it into routes for each UAV; a vision-language model locates inspection targets on an aerial map and evenly distributes the task among N UAVs according to route length, after which worker agents equipped with lightweight decision models verify events. The authors report that in simulations covering 4 types of events and 3 base models, the swarm located the event in 244 of 255 tasks (95.7%). Paired scaling experiments with 1 to 5 UAVs showed that flight time follows an Amdahl-type pattern: the second UAV contributed half of the achievable savings, and the speedup upper bound was 1.52x. The authors also state that user studies are still needed to evaluate the system.
Report timeline
- UAV-SwarmAgent: Multi-UAV reconnaissance and task allocation via code generation and vision-language reasoning
UAV-SwarmAgent is a hierarchical multi-agent system in which an operator issues a mission in one natural-language sentence, and a ground-station agent generates and executes code that turns it into routes for each UAV. The system uses a vision-language model to locate inspection targets on an aerial map, balances them among N UAVs by route length, and then worker agents equipped with lightweight decision models verify incidents.
arXiv cs.RO ·