Density-Driven Multi-Agent Coordination for Efficient Farm Coverage and Management in Smart Agriculture
Sungjun Seo, Kooktae Lee

TL;DR
This paper introduces a density-driven multi-UAV coordination framework using optimal transport theory to improve efficiency, reduce chemical use, and enhance scalability in large-scale precision agriculture.
Contribution
It presents a novel D2OC framework integrating OT with multi-UAV control, accounting for infestation severity and UAV dynamics for efficient farm coverage.
Findings
Outperforms uniform spraying in coverage efficiency.
Reduces chemical application compared to traditional methods.
Enhances operational sustainability and scalability.
Abstract
The growing scale of modern farms has increased the need for efficient and adaptive multi-agent coverage strategies for pest, weed, and disease management. Traditional methods such as manual inspection and blanket pesticide spraying often lead to excessive chemical use, resource waste, and environmental impact. While unmanned aerial vehicles (UAVs) offer a promising platform for precision agriculture through targeted spraying and improved operational efficiency, existing UAV-based approaches remain limited by battery life, payload capacity, and scalability, especially in large fields where single-UAV or uniformly distributed spraying is insufficient. Although multi-UAV coordination has been explored, many current frameworks still assume uniform spraying and do not account for infestation severity, UAV dynamics, non-uniform resource allocation, or energy-efficient coordination. To…
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Taxonomy
TopicsUAV Applications and Optimization · Plant Surface Properties and Treatments · Smart Agriculture and AI
