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

Authors

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

DOI:

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

Keywords:

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

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.

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