3D UAV Trajectory Planning for IoT Data Collection Over 3D Terrain Features
Pei-Fa Sun, Yujae Song, Kangyu Gao, Yukai Wang, Changjun Zhou, Sang-Woon Jeon, Jun Zhang · 2025
UAVs are increasingly essential in wireless communication applications, such as internet of things (IoT) and sensor networks, due to their agile mobility. However, planning three-dimensional (3D) UAV trajectories over a continuous temporal-spatial domain remains challenging due to the computational complexity of non-convex optimization. This paper addresses UAV-assisted IoT data collection, aiming to minimize total energy consumption while considering UAV capabilities, heterogeneous IoT data demands, and 3D terrain. We propose a matrix-based differential evolution with constraint handling (MDE-CH), a computationally efficient algorithm for solving constrained non-convex optimization problems. Numerical results show that MDE-CH efficiently generates continuous 3D UAV trajectories, significantly reducing energy consumption and outperforming the conventional fly-hover-fly model for 2D and 3D trajectory planning.