UAV Route Planning for Environmental Monitoring Reviewed

Environmental monitoring tasks often rely on Unmanned Aerial Vehicles (UAVs), which necessitates sophisticated route planning to maximize the area covered while adhering to energy limitations, operational restrictions, and complex geometries. A systematic literature review (SLR) is underway to comprehensively analyze autonomous UAV route planning specifically for coverage-oriented environmental monitoring. This review follows the PRISMA 2020 framework, searching major scientific databases for relevant studies published between 2015 and 2026. The review protocol emphasizes various aspects, including path planning algorithms, metrics for coverage and energy, methods for handling obstacles, environmental representations, and specific constraints. Initial findings from the screening phase indicate a strong focus in existing research on formulations that prioritize coverage, coordination among multiple UAVs, and energy-aware optimization techniques. Fewer studies, however, explicitly address challenges like adverse weather conditions, environmental uncertainty, or highly obstacle-rich environments. The preliminary analysis also points to a prevalence of simulation-based validation, suggesting a potential gap between theoretical models and real-world deployment. Recent trends show growing interest in reinforcement learning, hybrid optimization, and geometry-aware planning.