The route planning methods for environmental monitoring with unmanned aerial vehicles (UAVs) must maximize the covered area while addressing energy limits, operational constraints, and geometric complexity. This paper reports the protocol and preliminary results of an ongoing systematic literature review (SLR) on autonomous UAV route planning for coverage-oriented environmental monitoring. The review follows the PRISMA 2020 framework and searches Scopus and Web of Science for studies published between 2015 and 2026.
The protocol focuses on path planning, coverage path planning, and informative path planning, emphasizing algorithmic families, coverage and energy metrics, obstacle handling, geometric environment representations, and environmental constraints. At the current stage, 562 records have been identified, with 161 duplicates removed, resulting in 401 unique records screened by title, abstract, and keywords. From these, 247 studies were retained for full-text eligibility assessment (235 eligible and 12 borderline records to be resolved during the full-text review).
A preliminary analysis of the retained studies suggests a strong concentration on coverage-oriented formulations, multi-UAV coordination, and energy-aware optimization, while fewer studies explicitly address weather, uncertainty, or obstacle-rich environments. Most retained studies rely on simulation-based validation, highlighting a potential simulation-to-reality gap, and recent publications show increasing interest in reinforcement learning, hybrid optimization, and geometry-aware planning. These early findings indicate an active but fragmented research landscape and support the need for a structured synthesis to identify mature techniques and unresolved gaps for realistic environmental monitoring missions.
Blogger's Review: This paper provides an in-depth literature review on UAV applications in environmental monitoring, highlighting current research hotspots and gaps, especially in multi-UAV coordination and energy optimization. Future research should focus on bridging the gap between simulation and reality to enhance the practical effectiveness of UAV applications.