Using spatial constraints for fast set-up of precise pose estimation in an industrial setting

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Abstract

This paper presents a method for high precision visual pose estimation along with a simple setup procedure. Robotics for industrial solutions is a rapidly growing field and these robots require very precise position information to perform manipulations. This is usually accomplished using e.g. fixtures or feeders, both expensive hardware solutions. To enable fast changes in production, more flexible solutions are required, one possibility being visual pose estimation. Although many current pose estimation algorithms show increased performance in terms of recognition rates on public datasets, they do not focus on actual applications, neither in setup complexity or high accuracy during object localization. In contrast, our method focuses on solving a number of specific pose estimation problems in a seamless manner with a simple setup procedure. Our method relies on a number of workcell constraints and employs a novel method for automatically finding stable object poses. In addition, we use an active rendering method for refining the estimated object poses, giving a very fine localization, suitable for robotic manipulation. Experiments with current state-of-the-art 2D algorithms and our method show an average improvement from 9~mm to 0.95~mm uncertainty. The method was also used by the winning team at the 2018 World Robot Summit Assembly Challenge
Original languageEnglish
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE
Publication date2019
Pages1308-1314
ISBN (Print)978-1-7281-0357-0
ISBN (Electronic)978-1-7281-0356-3, 978-1-7281-0355-6
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

Keywords

  • pose estimation
  • computer vision
  • template matching
  • stable pose

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  • Cite this

    Hagelskjær, F., Savarimuthu, T. R., Krüger, N., & Buch, A. G. (2019). Using spatial constraints for fast set-up of precise pose estimation in an industrial setting. In 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019 (pp. 1308-1314). IEEE. IEEE International Conference on Automation Science and Engineering https://doi.org/10.1109/COASE.2019.8842876