Off-line error prediction, diagnosis and recovery using virtual assembly systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Baydar:2001:ICRA,
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author = "Cem M. Baydar and Kazuhiro Saitou",
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title = "Off-line error prediction, diagnosis and recovery
using virtual assembly systems",
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booktitle = "Proceedings of the IEEE International Conference on
Robotics and Automation, ICRA 2001",
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year = "2001",
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volume = "1",
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pages = "818--823",
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address = "Seoul, Korea",
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month = "21-26 " # may,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming, 3D model,
Bayesian reasoning, Monte Carlo simulation, assembly
line, automated assembly systems, error scenarios,
peg-in-hole assembly, unexpected failures, virtual
assembly systems, Bayes methods, Monte Carlo methods,
assembling, fault diagnosis, industrial robots,
inference mechanisms, robot programming",
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ISSN = "1050-4729",
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ISBN = "0-7803-6576-3",
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DOI = "doi:10.1109/ROBOT.2001.932651",
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size = "6 pages",
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abstract = "Automated assembly systems often stop their operation
due to the unexpected failures occurred during their
assembly process. Since these large-scale systems are
composed of many parameters, it is difficult to
anticipate all possible types of errors with their
likelihood of occurrence. Several systems were
developed in the literature, focusing on online
diagnosing and recovering the assembly process in an
intelligent manner based on the predicted error
scenarios. However, these systems do not cover all of
the possible errors and they are deficient in dealing
with the unexpected error situations. The proposed
approach uses Monte Carlo simulation of the assembly
process with the 3D model of the assembly line to
predict the possible errors in an offline manner. After
that, these predicted errors can be diagnosed and
recovered using Bayesian reasoning and genetic
programming. A case study composed of a peg-in-hole
assembly was performed and the results are discussed.
It is expected that with this new approach, errors can
be diagnosed and recovered accurately and costly
downtime of robotic assembly systems will be reduced.",
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notes = "GP creates code in RAPID language. Also known as
\cite{932651}",
- }
Genetic Programming entries for
Cem M Baydar
Kazuhiro Saitou
Citations