3D UAV Trajectory Planning for IoT Data Collection Over 3D Terrain Features

Citations

WEB OF SCIENCE

1
Citations

SCOPUS

4

초록

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.

키워드

Energy minimization; matrix-based evolutionary computation; sensor networks; UAV trajectory optimization; unmanned aerial vehicle (UAV) communication
제목
3D UAV Trajectory Planning for IoT Data Collection Over 3D Terrain Features
저자
Sun, Pei-Fa; Song, Yujae; Gao, Kangyu; Wang, Yukai; Zhou, Changjun; Jeon, Sang-Woon; Zhang, Jun
DOI
10.1109/VTC2025-Spring65109.2025.11174485
발행일
2025-09
유형
Proceedings Paper
저널명
IEEE Vehicular Technology Conference (VTC)