@inproceedings{df7c3399d00d4fe997153ac0e37aae46,
title = "Enhancing Exploration Efficiency of Fixed-Wing UAVs Through Intelligent Decision-Making and Advanced Control Integration",
abstract = "With the ongoing development of intelligent technologies, fixed-wing unmanned aerial vehicles (UAVs) are gaining prominence across diverse sectors. This study focuses on complex environment exploration. It employs the Dyna-Q reinforcement learning algorithm to derive optimal waypoints in obstacle-rich settings. These waypoints are pivotal for task allocation, ensuring judicious deployment of UAV clusters for targeted exploration. Concurrently, B-spline techniques refine these waypoints into feasible flight trajectories for UAVs. Subsequently, distributed model predictive control (DMPC) is utilized to maintain a designated cluster configuration. This DMPC controller ensures trajectory tracking along optimized paths, facilitating thorough area exploration. Then the approach is validated and evaluated through simulation experiments using a laboratory-developed simulation platform.",
keywords = "DMPC, dyna-q learning, intelligent decision",
author = "Yibo Zhang and Liang Han and Xiaoduo Li and Haoyang Yu and Zhang Ren",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023 ; Conference date: 24-11-2023 Through 27-11-2023",
year = "2024",
doi = "10.1007/978-981-97-3340-8\_21",
language = "英语",
isbn = "9789819733392",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "231--242",
editor = "Guo-Ping Jiang and Mengyi Wang and Zhang Ren",
booktitle = "Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Guidance Technologies",
address = "德国",
}