Among various considerations that affect path planning, weather may have the most significant
impact, as Unmanned Aerial Vehicles (UAVs) are sensitive to weather conditions such as wind, temperature, and precipitation. Our objective is to address this need by developing a decision support system for UAV path planning under the consideration of stochastic weather evolution.
Our proposed model is dynamic and data-driven, and allows for safe and effective path planning while also minimizing any involved costs during each mission.