@inproceedings{021dc322e13a460d9e0b4b93164496e5,
title = "Binary Pigeon-Inspired Optimization for Quadrotor Swarm Formation Control",
abstract = "This paper proposes a binary pigeon-inspired optimization (BPIO) algorithm, for the quadrotor swarm formation control problem. The expected position is provided by the BPIO. Quadrotor moves to the position with control strategy, and the strategy is based on the proportional integral derivative (PID) control method. The BPIO algorithm which is based on pigeon-inspired optimization (PIO) algorithm can effectively solve the combination problem in the binary solution space. The BPIO keeps the fast convergence of the PIO, and can explore the space effectively at the same time. The parameters to be optimized are encoded with binary bits. A special fitness function is designed to avoid the happening of crash. The simulation experiment shows how the BPIO works. The results of simulation verify the feasibility and effectiveness of the BPIO to solve the swarm formation problem.",
keywords = "Binary pigeon-inspired optimization (BPIO), Quadrotor, Swarm formation",
author = "Zhiqiang Zheng and Haibin Duan and Chen Wei",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 11th International Conference on Swarm Intelligence, ICSI 2020 ; Conference date: 14-07-2020 Through 20-07-2020",
year = "2020",
doi = "10.1007/978-3-030-53956-6\_7",
language = "英语",
isbn = "9783030539559",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "71--82",
editor = "Ying Tan and Yuhui Shi and Milan Tuba",
booktitle = "Advances in Swarm Intelligence - 11th International Conference, ICSI 2020, Proceedings",
address = "德国",
}