Collaborative attack task assignment for distributed UAV swarm using competition cooperation mechanism

Wenjia Su; Min Gao; Xinbao Gao; Zhaolong Xuan

doi:10.1117/12.3006777

10 October 2023 Collaborative attack task assignment for distributed UAV swarm using competition cooperation mechanism

Wenjia Su, Min Gao, Xinbao Gao, Zhaolong Xuan

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127993L (2023) https://doi.org/10.1117/12.3006777
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Unmanned aerial vehicle (UAV) swarm has sparked heated debate around the world in recent years. There are various stages to the battle of UAV swarm. This paper focuses on the attack task assignment after being cast or launched over the battlefield. In order to describe the process of task assignment for UAV swarm, a model introducing multiple constraints, such as limited detection range and imperfect communications, is established first. Then, inspired by contract network algorithm, we proposed a mechanism including competition for local revenue and cooperation for global revenue. And the premise of this mechanism is that UAV swarm is distributed, whose task is assigned by itself, not any other UAV. Finally, the advantages of our mechanism are illustrated by the contrast of different methods on the same issue.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenjia Su, Min Gao, Xinbao Gao, and Zhaolong Xuan "Collaborative attack task assignment for distributed UAV swarm using competition cooperation mechanism", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127993L (10 October 2023); https://doi.org/10.1117/12.3006777

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KEYWORDS

Unmanned aerial vehicles

Target detection

Data transmission

Reconnaissance

Reflection

Matrices

Motion models

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