Optimization of Flight Planning for Orthomosaic Generation Using Digital Twins and SITL Simulation

Farming plays a crucial role in the development of countries striving to achieve Sustainable Development Goals (SDGs). However, in developing nations, low productivity and poor food quality often result from a lack of modernization. In this context, precision agriculture (PA) introduces techniques to enhance agricultural management and improve production. Recent advancements in PA require higher-resolution imagery. Unmanned aerial vehicles (UAVs) have emerged as a cost-effective and highly capable tool for crop monitoring, offering high-resolution data (3–5 cm). However, operating UAVs in sensitive environments or during testing phases involves risks, and errors can lead to significant costs. To address these challenges, software-in-the-loop (SITL) simulation, combined with digital twins (DTs), allows for studying UAV behavior and anticipating potential risks. Furthermore, effective flight planning is essential to optimize time and resources, requiring certain mission parameters to be properly configured to ensure efficient generation of quality orthomosaics. Unlike previous studies, this article presents a novel methodology that integrates the SITL framework with the Gazebo simulator, a digital model of a multirotor UAV, and a digital terrain model of interest, which together allows for the creation of a digital twin. This approach serves as a low-cost tool to analyze flight parameters in various scenarios and optimize mission planning before field execution. Specifically, multiple flight missions were scheduled based on high-resolution requirements, different overlap configurations (40–70% and 30–60%), and variable wind conditions. The results demonstrate that the proposed parameters optimize mission planning in terms of efficiency and quality. Through both quantitative and qualitative evaluations, it was evident that, for low-altitude flights, the configurations with the lowest overlap produce high-resolution orthomosaics while significantly reducing operational time.