@inproceedings{21f59096258d494f82a63d410b4f4175,
title = "Mixed game pigeon-inspired optimization for unmanned aircraft system swarm formation",
abstract = "This paper proposes a novel mixed game pigeon-inspired optimization (MGPIO) algorithm for unmanned aircraft system (UAS) swarm formation control. The outer loop controller based on artificial potential field method is designed to transform the UAS swarm formation into abstract movements in the potential field. The inner loop controller based on PIO is designed to solve the optimal UAS position. A novel pigeon-inspired optimization integrated with mixed game theory is proposed to enhance its capacity and convergence speed to solve complex problem while reducing the computational load. This method maintains the capability of the PIO to diversify the pigeons{\textquoteright} exploration in the solution space. Moreover, the proposed method improves the quality of the pigeons based on the situation. A series of simulation experiments are conducted compared with basic PIO and Particle Swarm Optimization (PSO) approach. The experimental results verify the feasibility and effectiveness of the proposed method.",
keywords = "Mixed game theory, Pigeon-inspired optimization, Swarm formation, Unmanned aircraft system",
author = "Haibin Duan and Bingda Tong and Yin Wang and Chen Wei",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 10th International Conference on Swarm Intelligence, ICSI 2019 ; Conference date: 26-07-2019 Through 30-07-2019",
year = "2019",
doi = "10.1007/978-3-030-26369-0\_40",
language = "英语",
isbn = "9783030263683",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "429--438",
editor = "Ying Tan and Yuhui Shi and Ben Niu",
booktitle = "Advances in Swarm Intelligence - 10th International Conference, ICSI 2019, Proceedings",
address = "德国",
}