Research on vision system of intelligent sorting robot based on deep learning

It is an important step to realize automatic and intelligent production of coal mine to use intelligent sorting robot instead of manual. The vision system, as the “eye” of the intelligent sorting robot, completes the rapid identification, positioning and grouping of the sorting target. Based on YOLO...

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Bibliographic Details
Published in:Metalurgija
Main Authors: Z. X. Li, Q. Zhang, B. W. Huang, Y. X. Miao
Format: Article
Language:English
Published: Croatian Society for Materials Protection 2025-01-01
Subjects:
intelligent sorting robot
lightweight model design
detection model
vision system
Online Access:https://hrcak.srce.hr/file/462243
Description
Summary:It is an important step to realize automatic and intelligent production of coal mine to use intelligent sorting robot instead of manual. The vision system, as the “eye” of the intelligent sorting robot, completes the rapid identification, positioning and grouping of the sorting target. Based on YOLOv5, the vision system uses GhostNet to carry out the lightweight design of the model, aiming to ensure the detection accuracy while making the entire model more lightweight, so as to improve the model recognition speed and reduce the operating cost. The model recognition speed of Ghost-YOLOv5 designed and developed is 33FPS, the model size is only 4,2 Mb, and the average detection accuracy is 96,7 %.
ISSN:0543-5846
1334-2576

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