Vision-less Bin-Picking for Small Parts Feeding

Simon Mathiesen*, Iñigo Iturrate, Aljaz Kramberger

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

Part feeding remains a vital yet troublesome task. This is especially true for flexible manufacturing systems, where classical methods are less applicable due to constraints from small batch sizes and high part variance. In this paper, a novel approach to part feeding is presented, which is targeted at small parts, such as nuts and bolts, that commonly occur in assembly tasks. The approach is an alternative bin picking solution, where parts stored unordered in bins, are oriented and presented for further manipulation using a specially designed tool. The tool is manifested a scoop, which a robot can use to scoop parts from the bins without the use of external sensory input such as vision. Using solely mechanical orienting principles and the motion of the robot, the parts are sorted so only parts in a desired orientation remain in the scoop. The approach is tested on a number of different parts to benchmark its performance.
Original languageEnglish
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE
Publication date2019
Pages1657-1663
ISBN (Print)978-1-7281-0357-0
ISBN (Electronic)978-1-7281-0355-6, 978-1-7281-0356-3
DOIs
Publication statusPublished - 2019
Event15th IEEE International Conference on Automation Science and Engineering, CASE 2019 - Vancouver, Canada
Duration: 22. Aug 201926. Aug 2019

Conference

Conference15th IEEE International Conference on Automation Science and Engineering, CASE 2019
CountryCanada
CityVancouver
Period22/08/201926/08/2019
SponsorABB Robotics, University of Wisconsin–Madison, et al., IEEE, IEEE Robotics and Automation Society, National Science Foundation (NSF)
SeriesIEEE International Conference on Automation Science and Engineering
ISSN2161-8070

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