학술논문

Workpiece Intelligent Identification and Positioning System based on Binocular Machine Vision
Document Type
Conference
Source
2021 IEEE 9th International Conference on Computer Science and Network Technology (ICCSNT) Computer Science and Network Technology (ICCSNT), 2021 IEEE 9th International Conference on. :55-58 Oct, 2021
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Computer science
Visualization
Shape
Target recognition
Machine vision
Conferences
Object detection
Binocular machine vision
Workpiece detection
Language
ISSN
2690-5892
Abstract
In this paper, a workpiece detection and positioning system has been studied. Firstly, data sets of workpieces with three different shapes (cube, cylinder and sphere) are established, and the YOLOV3 target detection algorithm is used for deep learning to realize intelligent recognition of different shapes of workpieces. Then by the use of binocular machine vision technology, the key points position of workpieces can be successfully detected with relative error less than 2 %. This workpiece detection and positioning system can be introduced in the mechanical arm grabbing control system to make it have the visual ability similar to human in order to realize mechanical arm intelligent grabbing in complex environment.