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Perception Subsystem for Object Recognition and Pose Estimation in RGB-D Images

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Challenges in Automation, Robotics and Measurement Techniques (ICA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 440))

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Abstract

RGB-D sensors have become key components of all kind of robotic systems. In this paper we present a perception subsystem for object recognition and pose estimation in RGB-D images. The system is able to recognize many objects at once, disregarding whether they belong to one or many classes. Next to the detailed description of the principle of the system operation we present several off-line and on-line experiments validating the system, including verification in the task of picking up recognized objects with IRp-6 manipulator.

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Acknowledgments

This project was funded by the National Science Centre according to the decision number DEC-2012/05/D/ST6/03097. Tomasz Kornuta is supported by the IBM Research, Almaden through the IBM PostDoc/LTS Programme.

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Authors and Affiliations

  1. IBM Research, Almaden, 650 Harry Rd, San Jose, CA, 95120, USA

    Tomasz Kornuta

  2. Institute of Control and Computation Engineering, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Michał Laszkowski

Authors
  1. Tomasz Kornuta
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  2. Michał Laszkowski
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Corresponding author

Correspondence to Tomasz Kornuta .

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Editors and Affiliations

  1. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Roman Szewczyk

  2. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Cezary Zieliński

  3. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Małgorzata Kaliczyńska

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Kornuta, T., Laszkowski, M. (2016). Perception Subsystem for Object Recognition and Pose Estimation in RGB-D Images. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_52

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  • DOI: https://doi.org/10.1007/978-3-319-29357-8_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29356-1

  • Online ISBN: 978-3-319-29357-8

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