@inproceedings{658939697bbc47a89cc12af8f27406e0,
title = "Research on Trajectory Tracking and Obstacle Avoidance Methods for UAV Swarm Based on Model Predictive Control",
abstract = "UAV swarm systems have been widely used in many fields. When performing formation flight missions in complex airspace environments, UAV swarms often encounter sudden obstacle threats. UAV swarms need to track predetermined trajectories while avoiding sudden obstacles. To address the three-dimensional path tracking control and obstacle avoidance problem of UAV swarms, a nonlinear model predictive control algorithm combined with adaptive artificial potential field method is proposed. A trajectory tracking and obstacle avoidance model for UAV swarms is established, and a cost function considering internal collisions of UAV swarms and external obstacles is designed. The algorithm achieves UAV swarm tracking of predetermined trajectories while maintaining formation and avoiding sudden obstacles. The feasibility and effectiveness of the algorithm are verified through simulation calculations.",
keywords = "Adaptive Artificial Potential Field Method, Model Predictive Control, Obstacle Avoidance, Trajectory Tracking, UAV Swarm",
author = "Haonan Li and Junsong Huang and Leting Wang and Teng Wang and Hairuo Zhang and Xiaoyang Li",
note = "Publisher Copyright: {\textcopyright} Chinese Institute of Command and Control 2024.; 12th China Conference on Command and Control, C2 2024 ; Conference date: 17-05-2024 Through 18-05-2024",
year = "2024",
doi = "10.1007/978-981-97-7774-7_32",
language = "英语",
isbn = "9789819777730",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "351--362",
booktitle = "Proceedings of 2024 12th China Conference on Command and Control",
}