EA-FCM: An Energy-Efficient 3D Path Planning Algorithm for Multiple UAVs

A multi-Unmanned Aerial Vehicle (UAV) system improves operational efficiency in applications, such as reconnaissance, disaster relief, agriculture, and logistics. Maintaining balanced energy consumption among UAVs is crucial for mission success, as energy imbalance can cause premature battery depletion and mission failure. This study proposes an optimization approach that enables balanced energy distribution during missions where multiple UAVs simultaneously cover an area, while also decoupling energy consumption into specific flight modes to allow for more precise energy calculations. Unlike previous research focused mainly on distance-based path optimization, this study prioritizes maintaining energy balance across UAVs. The proposed model is compared with an optimized Fuzzy C-Means clustering algorithm in terms of the energy consumption distribution among UAVs. Simulation results confirm the proposed model reduces both the variance and the coefficient of variation in energy consumption, enhancing mission efficiency across scenarios.