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Narrow passage sampling in the observation of robotic assembly tasks

Nottensteiner, Korbinian and Sagardia, Mikel and Stemmer, Andreas and Borst, Christoph Hermann (2016) Narrow passage sampling in the observation of robotic assembly tasks. In: IEEE International Conference on Robotics and Automation ICRA. IEEE. IEEE International Conference on Robotics and Automation, 16.-21. Mai 2016, Stockholm, Schweden. DOI: 10.1109/ICRA.2016.7487125

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Abstract

The observation of robotic assembly tasks is required as feedback for decisions and adaption of the task execution on the current situation. A sequential Monte Carlo observation algorithm is proposed, which uses a fast and accurate collision detection algorithm as a reference model for the contacts between complex shaped parts. The main contribution of the paper is the extension of the classic random motion model in the propagation step with sampling methods known from the domain of probabilistic roadmap planning in order to increase the sample density in narrow passages of the configuration space. As a result, the observation Performance can be improved and a risk of sample impoverishment reduced. Experimental validation is provided for a peg-in-hole task executed by a lightweight- obot arm equipped with joint torque sensors.

Item URL in elib:https://elib.dlr.de/105314/
Document Type:Conference or Workshop Item (Speech)
Title:Narrow passage sampling in the observation of robotic assembly tasks
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Nottensteiner, Korbiniankorbinian.nottensteiner (at) dlr.deUNSPECIFIED
Sagardia, MikelMikel.Sagardia (at) dlr.deUNSPECIFIED
Stemmer, Andreasandreas.stemmer (at) dlr.deUNSPECIFIED
Borst, Christoph HermannChristoph.Borst (at) dlr.deUNSPECIFIED
Date:May 2016
Journal or Publication Title:IEEE International Conference on Robotics and Automation ICRA
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:Yes
DOI :10.1109/ICRA.2016.7487125
Publisher:IEEE
Status:Published
Keywords:sequential Monte Carlo, particle filter, robotics assembly, observation
Event Title:IEEE International Conference on Robotics and Automation
Event Location:Stockholm, Schweden
Event Type:international Conference
Event Dates:16.-21. Mai 2016
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 - Vorhaben Intelligente Mobilität
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Deposited By: Nottensteiner, Korbinian
Deposited On:19 Jul 2016 09:23
Last Modified:09 Feb 2017 19:22

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