机械与电子2024，Vol.42Issue(8)：40-45,6.
基于YOLOv8的无人机编队领航者检测算法
UAV Formation Leader Detection Algorithm Based on YOLOv8
黄祎闻 1甄子洋 1何佳璐1
作者信息
- 1. 南京航空航天大学自动化学院,江苏南京 211106
- 折叠
摘要
Abstract
The vision-based unmanned aerial vehicle(UAV)formation method has the advantage of being unaffected by communication disruptions and exhibits greater robustness compared to traditional for-mation algorithms,gradually becoming a research hotspot in the field.In the Leader-Follower UAV visual formation mode,followers achieve formation control by performing real-time target detection on the lead-er and calculating the relative positional relationship between the leader and the followers.This paper pro-poses an improved real-time object detection algorithm based on the YOLOv8n object detection model:convolution modules were added in the Neck module,a multi-head attention mechanism was added to en-hance feature extraction,apply data augmentation was applied in the training process.To validate the per-formance advantages of the algorithm proposed,two comparative tests were conducted.The experimental results indicate that the improved algorithm exhibits stronger feature extraction and higher detection accu-racy compared to the original algorithm.Finally,the improved object detection algorithm is applied to drone formation tasks,demonstrating the practical utility of the algorithm in this context.关键词
无人机编队/YOLOv8/可变形卷积/多头自注意力机制Key words
UAV formation/YOLOv8/deformable convolution/multi-head attention mechanism分类
信息技术与安全科学引用本文复制引用
黄祎闻,甄子洋,何佳璐..基于YOLOv8的无人机编队领航者检测算法[J].机械与电子,2024,42(8):40-45,6.
