Force and Topography Reconstruction Using GP and MOR for the TACTIP Soft Sensor System

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{deBoer2016,

• author = "G {de Boer} and H Wang and M Ghajari and A Alazmani and R Hewson and P Culmer",
• title = "Force and Topography Reconstruction Using {GP} and {MOR} for the {TACTIP} Soft Sensor System",
• booktitle = "Proceedings of the 17th Annual Conference Towards Autonomous Robotic Systems, TAROS 2016",
• year = "2016",
• editor = "Lyuba Alboul and Dana Damian and Jonathan M. Aitken",
• volume = "9716",
• series = "Lecture Notes in Computer Science",
• pages = "65--74",
• address = "Sheffield, UK",
• month = jun # " 26--" # jul # " 1",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Model Order Reduction",
• bibsource = "OAI-PMH server at eprints.whiterose.ac.uk",
• contributor = "L Alboul and D Damian and J. M. Aitken",
• oai = "oai:eprints.whiterose.ac.uk:101732",
• isbn13 = "978-3-319-40379-3",
• URL = "https://doi.org/10.1007/978-3-319-40379-3_7",
• DOI = "doi:10.1007/978-3-319-40379-3_7",
• size = "10 pages",
• 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