A Genetic Programming Framework for Error Recovery in Robotic Assembly Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Saitou:2000:GECCOlb,
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author = "Kazuhiro Saitou and Cem M. Baydar",
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title = "A Genetic Programming Framework for Error Recovery in
Robotic Assembly Systems",
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pages = "346--351",
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booktitle = "Late Breaking Papers at the 2000 Genetic and
Evolutionary Computation Conference",
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year = "2000",
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editor = "Darrell Whitley",
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address = "Las Vegas, Nevada, USA",
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month = "8 " # jul,
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keywords = "genetic algorithms, genetic programming",
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broken = "http://www-personal.engin.umich.edu/~cbaydar/GECCO2000.pdf",
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URL = "http://citeseer.ist.psu.edu/cache/papers/cs/26330/http:zSzzSzwww-personal.engin.umich.eduzSz~cbaydarzSzGECCO2000.pdf/baydar00genetic.pdf",
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URL = "http://citeseer.ist.psu.edu/535952.html",
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abstract = "the advantages and performance of genetic programming
in use of error recovery planning in robotic assembly
systems is discussed. Existing systems use polynomial
time planning techniques or heuristics to produce error
recovery plans. However, these systems require
translation of the generated plans to working
controller codes. An alternative approach could be the
use of Genetic Programming to produce recovery plans in
robot language itself. A framework is developed and
coupled with a 3D robotic simulation software for the
generation of error recovery logic in assembly systems.
The developed architecture uses a genetic programming
system based on both deterministic and probabilistic
crossover and variable mutation schemes. Performance of
the system is evaluated with the simulations made on a
three dimensionally modeled automated assembly line.
The obtained results showed that the deterministic
crossover operator improves the evolution of the plans
and the system is efficient of generating robust
recovery plans for different error states.",
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notes = "Part of \cite{whitley:2000:GECCOlb}",
- }
Genetic Programming entries for
Kazuhiro Saitou
Cem M Baydar
Citations