DOI

In order for Automated Guided Vehicles (AGV’s) to handle KLT bins (Kleinladungsträger, Small Load Carrier) in a flexible way, a robust bin detection algorithm has to be developed. This paper presents a solution to the KLT bin detection and pose estimation task. The Mask R-CNN network is used to detect a KLT bin on color images, while a simple plane fitting approach is used to estimate its 5DoF position. This combination gives promising results in a typical use case scenario when the KLT bin is aligned with the camera view.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blecic, David Taniar, Bernady O. Apduhan, Ana Maria A.C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca
PublisherSpringer Nature
Pages105-118
Number of pages14
ISBN (Print)9783030588168
DOIs
StatePublished - 2020
Event20th International Conference on Computational Science and Its Applications, ICCSA 2020 - Cagliari, Italy
Duration: 1 Jul 2020 → 4 Jul 2020
http://iccsa.org/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12254 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science and Its Applications, ICCSA 2020
Abbreviated titleICCSA 2020
Country/TerritoryItaly
CityCagliari
Period1/07/20 → 4/07/20
Internet address

    Research areas

  • Industry 4.0, Instance segmentation, KLT bin picking, Object detection, Plane fitting, Pose estimation

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 70614972