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Rigid 3D Geometry Matching for Grasping of Known Objects in Cluttered Scenes

Chavdar, Papazov and Haddadin, Sami and Parusel, Sven and Krieger, Kai and Burschka, Darius (2012) Rigid 3D Geometry Matching for Grasping of Known Objects in Cluttered Scenes. International Journal of Robotics Research, 31 (4), pp. 538-553. SAGE Publications. DOI: 10.1177/0278364911436019 ISSN 0278-3649

Full text not available from this repository.

Official URL: http://ijr.sagepub.com/content/31/4/538.full.pdf+html

Abstract

In this paper, we present an efficient 3D object recognition and pose estimation approach for grasping procedures in cluttered and occluded environments. In contrast to common appearance-based approaches, we rely solely on 3D geometry information. Our method is based on a robust geometric descriptor, a hashing technique and an efficient, localized RANSAC-like sampling strategy. We assume that each object is represented by a model consisting of a set of points with corresponding surface normals. Our method simultaneously recognizes multiple model instances and estimates their pose in the scene. A variety of tests shows that the proposed method performs well on noisy, cluttered and unsegmented range scans in which only small parts of the objects are visible. The main procedure of the algorithm has a linear time complexity resulting in a high recognition speed which allows a direct integration of the method into a continuous manipulation task. The experimental validation with a seven-degree-of-freedom Cartesian impedance controlled robot shows how the method can be used for grasping objects from a complex random stack. This application demonstrates how the integration of computer vision and soft-robotics leads to a robotic system capable of acting in unstructured and occluded environments.

Item URL in elib:https://elib.dlr.de/79905/
Document Type:Article
Title:Rigid 3D Geometry Matching for Grasping of Known Objects in Cluttered Scenes
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Chavdar, PapazovRobotics and Embedded Systems, Technische Universität München (TUM)UNSPECIFIED
Haddadin, SamiInstitute of Robotics and Mechatronics, German Aerospace Center (DLR)UNSPECIFIED
Parusel, SvenInstitute of Robotics and Mechatronics, German Aerospace Center (DLR)UNSPECIFIED
Krieger, KaiInstitute of Robotics and Mechatronics, German Aerospace Center (DLR)UNSPECIFIED
Burschka, DariusRobotics and Embedded Systems, Technische Universität München (TUM)UNSPECIFIED
Date:April 2012
Journal or Publication Title:International Journal of Robotics Research
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:31
DOI :10.1177/0278364911436019
Page Range:pp. 538-553
Editors:
EditorsEmail
Hollerbach, John Mjmh@cs.utah.edu
Publisher:SAGE Publications
ISSN:0278-3649
Keywords:Robot vision, 3D object recognition, grasping
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - RMC - Kognitive Intelligenz und Autonomie (old), R - RMC - Mechatronik und Telerobotik (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (until 2012)
Deposited By: Parusel, Sven
Deposited On:19 Dec 2012 11:04
Last Modified:06 Sep 2019 15:18

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