Machine Vision-Based Laser-Powered Unmanned Aerial Vehicle System

Boyu Shan; Zhigang Di; Shuolin Xu; Zengshuai Song; Shengbo Zhang; Yuhan Chen; Zengqi Zhang

doi:10.6919/ICJE.202602_12(2).0002

Machine Vision-Based Laser-Powered Unmanned Aerial Vehicle System

Boyu Shan, Zhigang Di, Shuolin Xu, Zengshuai Song, Shengbo Zhang, Yuhan Chen, Zengqi Zhang

International Core Journal of Engineering, (2026), Vol.12, No.2, pp.10-18

Published: February 28, 2026

DOI: 10.6919/ICJE.202602_12(2).0002

PDF: Download Full Text PDF

Abstract

To address the issues of short flight endurance and lengthy charging times for drones, a laser-powered drone system based on machine vision has been designed.This system centers on machine vision technology, integrating laser wireless power transmission. It employs the YOLOv11 object detection algorithm enhanced with an attention mechanism to improve detection accuracy for photovoltaic cells on drones, while utilizing PID control to optimize laser targeting precision.Experimental testing indicates that the system achieves over 95% confidence in detecting photovoltaic cell targets, with an inference time of 10.9 milliseconds per frame.This system features high recognition accuracy, rapid identification speed, and precise tracking, making it a portable and efficient laser-powered unmanned aerial vehicle system.

Keywords: Machine Vision; Attention Mechanism; YOLOv11 Algorithm; PID Control.

APA Citation: Boyu Shan, Zhigang Di, Shuolin Xu, Zengshuai Song, Shengbo Zhang, Yuhan Chen, Zengqi Zhang (2026). Machine Vision-Based Laser-Powered Unmanned Aerial Vehicle System. International Core Journal of Engineering, 12(2), 10-18. https://doi.org/10.6919/ICJE.202602_12(2).0002

References

Kai Huang. Research on the Application of Laser Power Supply Technology in UAV Endurance[D].Three Gorges University,2020.DOI:10.27270/d.cnki.gsxau.2020.000488.(In Chinese)
Husheng Tang.Laser-Powered Unmanned Aerial Vehicle Systems and Their Application Prospects[J].China Science and Technology Information,2021,(12):24-27.(In Chinese)
Xiaoyang C ,Yanji H ,Xing J .Energy management strategy for laser-powered near space aircraft[C]//IETP-Association.Abstracts of 2015 International Conference on Structural,Mechanical and Materials Engineering(ICSMME 2015).State Key Laboratory of Laser Propulsion &Application, Academy of Equipment;,2015:26.
He X ,Zhong Y ,Li H .Distributed Robust Routing Optimization for Laser-Powered UAV ClusterwithTemporaryParkingCharging[J].AppliedSciences,2025,15(17):9676-9676.DOI:10.3390/APP15179676.
Jianhua Yuan,Kai Huang,Husheng Hong,et al.An Optimized Tracking Algorithm for Laser-Powered Unmanned Aerial Vehicles[J].Applied Optics,2020,41(01):194-201.(In Chinese)
Yao Y ,Qiao G ,Zhang S , et al.Research on Morphometric Methods for Larimichthys crocea BasedonYOLOv11-CBAMX-RayImaging[J].Fishes,2025,10(12):641-641.DOI:10.3390/FISHES10120641.
Song L ,Tao Y.Occluded Small Target Detection for UAVs Based on YOLOv11[J].Engineering Letters,2026,34(1).
Linlin Ma,Jianxin Ma,Jiafang Han,et al.Research on Object Detection Algorithms Based on YOLOv5s[J].ComputerKnowledgeandTechnology,2021,17(23):100-103.DOI:10.14004/j.cnki.ckt.2021.2402.(In Chinese)
Adli T ,Bujaković M D ,Bondžulić P B , et al.Robustness of YOLO models for object detectioninremotesensingimages[J].JournalofElectricalEngineering,2025,76(5):429-442.DOI:10.2478/JEE-2025-0045.
Xiaobo Li ,Yanggui Li ,Ning Guo , et al.YOLOv5 Mask Detection Algorithm with Integrated Attention Mechanism[J].Journal of Graphics,2023,44(01):16-25.(In Chinese)