Multiple UAVs reconnaissance task allocation based on improved wolf pack algorithm

Hongchao Zhao; Zehui Wang; Tingting Ge

doi:10.1117/12.3038699

23 August 2024 Multiple UAVs reconnaissance task allocation based on improved wolf pack algorithm

Hongchao Zhao, Zehui Wang, Tingting Ge

Author Affiliations +

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 1325028 (2024) https://doi.org/10.1117/12.3038699
Event: Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

The large-scale reconnaissance task allocation problem of multiple unmanned aerial vehicles (UAVs) is researched. In order to simplify the problem, the task allocation process is divided into two independent stages: the cluster stage and the reconnaissance sequence allocation stage. In the first stage, a k-means cluster algorithm based on the azimuth angle is developed to group a large number of targets. The traditional wolf pack algorithm (WPA) does not fit the task allocation problem. In the second stage, an improved WPA is developed to decide the reconnaissance sequence of every group of targets. The improved WPA mainly modifies three behaviors in the traditional WPA, namely, wandering behavior, summoning behavior, and besieging behavior. Two simulation experiments are carried out. In the first experiment the algorithm in this paper is applied. In the second experiment the traditional k-means cluster based on the distance is applied to group the targets. The comparison of experiment results validates that the algorithm in this paper is more effective and outstanding.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongchao Zhao, Zehui Wang, and Tingting Ge "Multiple UAVs reconnaissance task allocation based on improved wolf pack algorithm", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 1325028 (23 August 2024); https://doi.org/10.1117/12.3038699

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE