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International Conference on Mining Intelligence and Knowledge Exploration

MIKE 2018: Mining Intelligence and Knowledge Exploration pp 205–214Cite as

Industry 4.0, Intelligent Visual Assisted Picking Approach

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11308))

Abstract

This work deals with a novel intelligent visual assisted picking task approach, for industrial manipulator robot. Intelligent searching object algorithm, around the working area, by RANSAC approach is proposed. After that, the image analysis uses the Sobel operator, to detect the objects configurations; and finally, the motion planning approach by Screw theory on SO(3), allows to pick up the selected object to move it, to a target place. Results and whole approach validation are discussed.

Supported by UNAD, Convocatoria 007.

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Author information

Authors and Affiliations

  1. Universidad Nacional Abierta y a Distancia (UNAD), Bogota, 111511, Colombia

    Mario Arbulu, Paola Mateus & Manuel Wagner

  2. Graduate School of Engineering Science, Department of Systems Innovation, Osaka University, 1-3 Machikaneyama, Toyonaka, 560-8531, Japan

    Cristian Beltran & Kensuke Harada

Authors
  1. Mario Arbulu
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  2. Paola Mateus
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  3. Manuel Wagner
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  4. Cristian Beltran
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  5. Kensuke Harada
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Corresponding authors

Correspondence to Mario Arbulu , Paola Mateus , Manuel Wagner , Cristian Beltran or Kensuke Harada .

Editor information

Editors and Affiliations

  1. Technical University of Cluj-Napoca, Cluj-Napoca, Romania

    Adrian Groza

  2. Indian Institute of Information Technology, Sri City, India

    Rajendra Prasath

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Arbulu, M., Mateus, P., Wagner, M., Beltran, C., Harada, K. (2018). Industry 4.0, Intelligent Visual Assisted Picking Approach. In: Groza, A., Prasath, R. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2018. Lecture Notes in Computer Science(), vol 11308. Springer, Cham. https://doi.org/10.1007/978-3-030-05918-7_18

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  • DOI: https://doi.org/10.1007/978-3-030-05918-7_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05917-0

  • Online ISBN: 978-3-030-05918-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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