Intelligent Exclusion Techniques for Unmanned Aircraft Swarms A Review of Research on Situational Awareness in Complex Scenarios

DOI: https://doi.org/10.62517/jike.202604110

Author(s)

Zishen Zhen

Affiliation(s)

School of Aeronautics and Astronautics, Nanchang Hangkong University, Nanchang, Jiangxi, China

Abstract

In order to cope with the practical needs of UAV swarm situational awareness in complex scenarios such as battlefield enemy screening and disaster area rescue, this paper systematically compiles the research progress of intelligent screening technology in the field of heterogeneous UAV swarm situational awareness. The research focuses on two core technology directions: first, analyzing the UAV target tracking and motion planning technology in complex environments, focusing on the multimodal target detection scheme integrating YOLOv5 algorithm and OpenPose attitude detection, and the spatial and temporal trajectory optimization method based on unconstrained Minimum Control Quantity trajectory (MINCO); second, exploring the key methods of cooperative control of UAV clusters, including distance division based coalition formation control algorithm, and hierarchical recursive distributed self-repair algorithm for UAV damage. By analyzing the existing research results, experimental data and simulation verification, we clarify the technical advantages and applicable scenarios, and provide theoretical support for the engineering application of UAV swarm intelligent inspection technology.

Keywords

Multimodal Fusion Detection; MINCO Trajectory Optimization; Distributed Self-Repair Algorithm; Intelligent Exclusion of Complex Scenes

References

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