Force and Topography Reconstruction Using GP and MOR for the TACTIP Soft Sensor System
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @InProceedings{deBoer2016,
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author = "G {de Boer} and H Wang and M Ghajari and
A Alazmani and R Hewson and P Culmer",
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title = "Force and Topography Reconstruction Using {GP} and
{MOR} for the {TACTIP} Soft Sensor System",
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booktitle = "Proceedings of the 17th Annual Conference Towards
Autonomous Robotic Systems, TAROS 2016",
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year = "2016",
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editor = "Lyuba Alboul and Dana Damian and Jonathan M. Aitken",
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volume = "9716",
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series = "Lecture Notes in Computer Science",
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pages = "65--74",
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address = "Sheffield, UK",
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month = jun # " 26--" # jul # " 1",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Model Order
Reduction",
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bibsource = "OAI-PMH server at eprints.whiterose.ac.uk",
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contributor = "L Alboul and D Damian and J. M. Aitken",
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oai = "oai:eprints.whiterose.ac.uk:101732",
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isbn13 = "978-3-319-40379-3",
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URL = "https://doi.org/10.1007/978-3-319-40379-3_7",
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DOI = "doi:10.1007/978-3-319-40379-3_7",
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size = "10 pages",
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abstract = "Sensors take measurements and provide feedback to the
user via a calibrated system, in soft sensing the
development of such systems is complicated by the
presence of nonlinearities, e.g. contact, material
properties and complex geometries. When designing
soft-sensors it is desirable for them to be inexpensive
and capable of providing high resolution output. Often
these constraints limit the complexity of the sensing
components and their low resolution data capture, this
means that the usefulness of the sensor relies heavily
upon the system design. This work delivers a force and
topography sensing framework for a soft sensor. A
system was designed to allow the data corresponding to
the deformation of the sensor to be related to outputs
of force and topography. This system used Genetic
Programming (GP) and Model Order Reduction (MOR)
methods to generate the required relationships. Using a
range of 3D printed samples it was demonstrated that
the system is capable of reconstructing the outputs
within an error of one order of magnitude.",
- }
Genetic Programming entries for
Greg de Boer
Haixin Wang
Mazdak Ghajari
Ali Alazmani
Robert Hewson
Pete Culmer
Citations