A Visual Question Answering-based Object Detection Framework using a Team of Multi-Agent UAVs
Year: 2025
Type: conference-paper
Abstract: This paper presents an autonomous multi-agent unmanned aerial vehicle (UAV) system designed to perform object detection through Visual Question Answering (VQA) using aerial imagery. The system utilizes an entropy-based distributed behavior model to coordinate UAV movements toward designated waypoints. A VQA model is used to analyze aerial footage for detection of objects of interest. The study investigates the impact of various distributed behavior configurations, including number of UAVs, UAV formations, flight altitude, and separation distance. After analysis, a final optimized configuration for maximizing surface area coverage and VQA model performance were found. These findings contribute to the development of aerial systems capable of collaborative visual reasoning in complex environments.
DOI: 10.5038/lijh5746
Authors: Stéphane Lee, Nathan Rayon, Hakki Sevil
Institution: University of West Florida
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411946531