Recognition and handling of clothes with different pattern by dual hand-eyes robotic system

Ryuki Funakubo, Khaing Win Phyu, Hongzhi Tian, Mamoru Minami

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

2 Citations (Scopus)

Abstract

Recently, robots have been used in clothing industries for mass production with countless merits. However, there remain many challenges for robots in recognition, pose (position and orientation) detection operations, especially when the working object is deformable and every working object has unique shape and color. In this paper, pose detection of clothes through 3D recognition is proposed for the task in which the manipulator recognizes clothes, estimates relative pose and performs pick and place function. In proposed cloth recognition system, a variety of models of different clothes with unique shape and color are generated as BMP (bit map file) format extracted from the camera. Using the photograph model, recognition of cloth is performed by using images from the two cameras that are fixed at the end effector of the robot arm. 12 varieties of different clothes samples are used for this experiment. The pose of individual cloth is estimated by Genetic Algorithm (GA). 1000 times recognition and handling experiment has been executed, having shown the effectiveness of proposed Photo-Model-Based pose recognition system.

Original languageEnglish
Title of host publicationSII 2016 - 2016 IEEE/SICE International Symposium on System Integration
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages742-747
Number of pages6
ISBN (Electronic)9781509033294
DOIs
Publication statusPublished - Feb 6 2017
Event2016 IEEE/SICE International Symposium on System Integration, SII 2016 - Sapporo, Japan
Duration: Dec 13 2016Dec 15 2016

Other

Other2016 IEEE/SICE International Symposium on System Integration, SII 2016
Country/TerritoryJapan
CitySapporo
Period12/13/1612/15/16

ASJC Scopus subject areas

  • Biomedical Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Artificial Intelligence
  • Hardware and Architecture
  • Control and Optimization

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