UAV Route Planning Review Reveals Gaps in Real-World Environmental Monitoring

A new systematic literature review from researchers at CLEI 2026 digs deep into autonomous UAV route planning for environmental monitoring. Led by Sebastian Jouannet-Contreras and Carola Figueroa-Flores, the SLR followed the PRISMA 2020 framework, searching Scopus and Web of Science for studies published between 2015 and 2026. From an initial pool of 562 records, 161 duplicates were removed, leaving 401 unique papers. After screening by title, abstract, and keywords, 247 studies passed to full-text eligibility assessment (235 eligible, 12 borderline). The review focuses on three route planning categories: path planning, coverage path planning, and informative path planning, with emphasis on algorithmic families, coverage/energy metrics, obstacle handling, geometric environment representations, and environmental constraints.

Preliminary findings paint a mixed picture. The field is heavily concentrated on coverage-oriented formulations, multi-UAV coordination, and energy-aware optimization. However, only a minority of studies explicitly tackle real-world complexities like adverse weather, sensor uncertainty, or obstacle-dense environments. Most validation relies on simulation, which raises a significant simulation-to-reality gap for actual deployment. Notably, recent publications show growing interest in reinforcement learning, hybrid optimization, and geometry-aware planning. The researchers conclude that the landscape is active but fragmented, and a structured synthesis is needed to identify mature techniques and unresolved gaps for realistic monitoring missions.