UAV swarm control algorithm based on Kalman filter and particle swarm optimization

Hongyi Qiu; Tingting Yan; Long Ma; Guodong Yue

doi:10.1117/12.2685988

28 July 2023 UAV swarm control algorithm based on Kalman filter and particle swarm optimization

Hongyi Qiu, Tingting Yan, Long Ma, Guodong Yue

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 1275649 (2023) https://doi.org/10.1117/12.2685988
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

This paper studies the passive localization and control of two-dimensional planar UAV swarm under velocity information and azimuth information. We propose a UAV swarm control algorithm based on azimuth information and velocity information. This paper establishes a positioning model through azimuth information. On this basis, the IMU information is fused for attitude calculation. Moreover, the inertial navigation positioning is established by using the attitude angle and velocity information, so as to explore and use the optimal estimation theory. Through Kalman filter technology, the Gaussian noise interference in UAV positioning is greatly eliminated, and the positioning algorithm of UAV swarm is established. In addition, using the azimuth information, the particle swarm optimization is used for path planning, and the target path planning results with higher accuracy are obtained. Through computer simulation analysis, the algorithm has the characteristics of high positioning accuracy and fast iteration speed. The algorithm can better meet the practical engineering application requirements.

Citation Download Citation

Hongyi Qiu, Tingting Yan, Long Ma, and Guodong Yue "UAV swarm control algorithm based on Kalman filter and particle swarm optimization", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 1275649 (28 July 2023); https://doi.org/10.1117/12.2685988

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