Weather-Integrated Optimization of Uncrewed Aerial System Routing for Precision Agriculture

Uncrewed aerial systems (UAS) are gaining traction in precision–agriculture missions, yet systematic tools for planning their flights remain sparse. Crop spraying illustrates the gap: an optimal mission must minimize flight distance and guarantee that every plant receives an adequate dose. We frame this dual goal as a coverage vehicle-routing problem (CoVRP) and solve it with a tiered decomposition that selects balanced launch sites, orders a compact set of routing centroids, and then joins independent coverage sub-tours into a single route. On two representative fields, a 3.25 meter active-node spacing—paired with a 3 meter spray radius and 4 to 5 high-level nodes—yields near-perfect coverage while keeping solve times below 1 minute on a desktop CPU; a wind-aware extension that replaces circular footprints with ellipses preserves this speed and trims in-field coverage by only 5%. A second application, field surveying, shows how a similar optimization engine can respect dynamic no-fly windows: wind forecasts are converted into a time-indexed availability matrix that activates or deactivates launch facilities as conditions change. In a prototype test case, the planner automatically routes around weather-induced closures and still produces a feasible survey schedule. These results mark a step toward end-to-end, real-time mission planning for weather-resilient precision agriculture.