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

Tomasz Michał Kornuta , Michał Laszkowski

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.
Author Tomasz Michał Kornuta IAiIS
Tomasz Michał Kornuta,,
- The Institute of Control and Computation Engineering
, Michał Laszkowski IAiIS
Michał Laszkowski,,
- The Institute of Control and Computation Engineering
Pages597-607
Publication size in sheets0.5
Book Szewczyk Roman, Kaliczyńska Małgorzata, Zieliński Cezary: Challenges in Automation, Robotics and Measurement Techniques. Proceedings of AUTOMATION-2016, March 2-4, 2016, Warsaw, Poland, Advances in Intelligent Systems and Computing, vol. 440, 2016, Springer International Publishing, ISBN 978-3-319-29356-1, [978-3-319-29357-8], 919 p., DOI:10.1007/978-3-319-29357-8
Keywords in EnglishRGB-D image SIFT Object recognition Pose estimation Object picking
DOIDOI:10.1007/978-3-319-29357-8_52
URL http://link.springer.com/chapter/10.1007/978-3-319-29357-8_52
projectMethodology of design and implementation of multi-sensory robotic systems for service purposes. Project leader: Winiarski Tomasz, , Phone: 7649, 7117, start date 01-02-2013, planned end date 31-01-2016, end date 03-10-2016, 505M/1031/0043, Completed
WEiTI Projects financed by NSC [Projekty finansowane przez NCN]
Languageen angielski
File
Kornuta Laszk Aut-16 rgbd-grasping.pdf (file archived - login or check accessibility on faculty) Kornuta Laszk Aut-16 rgbd-grasping.pdf 5.06 MB
Score (nominal)15
ScoreMinisterial score = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
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