3D UAV Trajectory Planning With Obstacle Avoidance for UAV-Enabled Time-Constrained Data Collection Systems

• Published in: IEEE transactions on vehicular technology Vol. 74; no. 1; pp. 1460 - 1474
• Main Authors: Zheng, Jun, Liu, Kai
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D trajectory planning; Algorithms; Approximation algorithms; Autonomous aerial vehicles; Completion time; Constraints; Data collection; Genetic algorithms; Hovering; Obstacle avoidance; Optimization; Planning; Sensors; Simulation; Spatial data; Three-dimensional displays; Trajectory; Trajectory optimization; Trajectory planning; UAV; Unmanned aerial vehicles
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2024.3419842

This paper investigates the three-dimensional (3D) unmanned aerial vehicle (UAV) trajectory-planning problem in a UAV-enabled data collection (DC) system, in which a UAV executes a mission to collect time-constrained data in a geographical area with spatial obstacles. For such a UAV trajectory-planning problem, how to timely collect data, avoid collisions with spatial obstacles, and complete DC with limited UAV onboard energy is a big challenge. To address this challenge, the investigated problem is formulated as an optimization problem aiming to minimize the UAV's total mission completion time subject to the time constraint of collected data, the avoidance of spatial obstacles, and the energy constraint of the UAV. To solve the formulated problem, the problem is decomposed into a visiting sequence optimization sub-problem, and a hovering position and flying path optimization sub-problem. Correspondingly, a genetic algorithm (GA) based algorithm, and a successive convex approximation (SCA) based algorithm are proposed to solve the sub-problems, respectively. Based on the two algorithms, a 3D trajectory optimization algorithm is further proposed to solve the main problem. Simulation results show that the UAV's trajectory planned with the proposed algorithm can effectively reduce the UAV's total mission completion time.