Energy-Aware Robotics: Review of Path Planning and Power Optimization for Long-Endurance UAVs

There is no gain saying of the obvious fact that Long-endurance, Unmanned Aerial Vehicles are critical not only for surveillance and precision agriculture, but also for disaster response, and environmental monitoring. However, battery capacity remains the primary constraint, with most multirotor UAVs limited to about 25–45 minutes of flight time. This review examines 2020–2026 research on energy-aware robotics, focusing on path planning and power optimization strategies that has the potential to extend UAV endurance. Following PRISMA 2020 guidelines, 112 peer-reviewed studies from IEEE Xplore, ACM, and Scopus were analyzed. Findings show three dominant approaches: 1. wind- and terrain-aware path planning, 2. hybrid energy systems including solar and fuel cells, and 3. learning-based power management. Results indicate that integrating environmental models with trajectory optimization can reduce energy consumption by 18–34%, while hybrid platforms achieve 2–8 times flight time over battery-only systems. Key gaps still persist in real-time energy prediction, multi-UAV coordination under energy constraints, and standardized energy benchmarks. However, we propose a four-layer framework: Environmental Modeling to Energy-Predictive Planning to Adaptive Control and to Fleet Energy Management. The review concludes that no single method is sufficient on its own alone hence long-endurance UAVs require co-design of hardware, algorithms, and mission planning.