Off-line error prediction, diagnosis and recovery using virtual assembly systems

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{Baydar:2001:ICRA,

• author = "Cem M. Baydar and Kazuhiro Saitou",
• title = "Off-line error prediction, diagnosis and recovery using virtual assembly systems",
• booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2001",
• year = "2001",
• volume = "1",
• pages = "818--823",
• address = "Seoul, Korea",
• month = "21-26 " # may,
• publisher = "IEEE",
• 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",
• ISSN = "1050-4729",
• ISBN = "0-7803-6576-3",
• DOI = "doi:10.1109/ROBOT.2001.932651",
• size = "6 pages",
• 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.",
• notes = "GP creates code in RAPID language. Also known as \cite{932651}",

}

Genetic Programming entries for Cem M Baydar Kazuhiro Saitou

Citations