Visual Feedback Control and Transfer Learning-Based CNN for a Pick and Place Robot on a Sliding Rail

Fusaomi Nagata, Kohei Miki, Keigo Watanabe, Maki K. Habib

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Among the various types of deep neural networks (DNNs), convolutional neural networks (CNNs) have ingenious structures and are widely used for image recognition and/or defect inspection. The authors already developed a design, training and test tool for CNNs and support vector machines (SVMs) to support defect detection of various kinds of manufactured products, while showing the effectiveness and the userfriendliness through classification experiments using images of actual products. The tool further enables to view where the most activated area in each classified image is. Besides the tool, a desktop-sized pick and place (PP) robot was also proposed while implementing a pixel-based visual feedback (VF) controller to autonomously reach target objects. In addition, a CNN designed based on transfer learning concept was developed to estimate objects' orientations. In this paper, a sliding rail is considered to allow the articulated robot to move around in a wider working range. The VF controller is extended to utilize the sliding rail. The usefulness and userfriendliness of the robot system using the sliding rail is confirmed through PP experiments of randomly put objects on a table.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Mechatronics and Automation, ICMA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages697-702
Number of pages6
ISBN (Electronic)9781665441001
DOIs
Publication statusPublished - Aug 8 2021
Event18th IEEE International Conference on Mechatronics and Automation, ICMA 2021 - Takamatsu, Japan
Duration: Aug 8 2021Aug 11 2021

Publication series

Name2021 IEEE International Conference on Mechatronics and Automation, ICMA 2021

Conference

Conference18th IEEE International Conference on Mechatronics and Automation, ICMA 2021
Country/TerritoryJapan
CityTakamatsu
Period8/8/218/11/21

Keywords

  • convolutional neural network
  • pick and place
  • robot
  • transfer learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

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