Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81170
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Mechanical Engineering-
dc.creatorNavarro-Alarcon, D-
dc.creatorZahra, O-
dc.creatorTrejo, C-
dc.creatorOlguín-Díaz, E-
dc.creatorParra-Vega, V-
dc.date.accessioned2019-08-16T06:05:23Z-
dc.date.available2019-08-16T06:05:23Z-
dc.identifier.urihttp://hdl.handle.net/10397/81170-
dc.language.isoenen_US
dc.publisherFrontiers Research Foundationen_US
dc.rightsCopyright © 2019 Navarro-Alarcon, Zahra, Trejo, Olguín-Díaz and Parra-Vega. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US
dc.rightsThe following publication Navarro-Alarcon D, Zahra O, Trejo C, Olguín-Díaz E and Parra-Vega V (2019) Computing Pressure-Deformation Maps for Braided Continuum Robots. Front. Robot. AI 6:4, 1-6 is available at https://dx.doi.org/10.3389/frobt.2019.00004en_US
dc.subjectContinuum robotsen_US
dc.subjectSelf-organizing mapsen_US
dc.subjectAdaptive systemsen_US
dc.subjectSensorimotor modelsen_US
dc.subjectNeural networksen_US
dc.titleComputing pressure-deformation maps for braided continuum robotsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage6en_US
dc.identifier.volume6en_US
dc.identifier.doi10.3389/frobt.2019.00004en_US
dcterms.abstractThis paper presents a method for computing sensorimotor maps of braided continuum robots driven by pneumatic actuators. The method automatically creates a lattice-like representation of the sensorimotor map that preserves the topology of the input space by arranging its nodes into clusters of related data. Deformation trajectories can be simply represented with adjacent nodes whose values smoothly change along the lattice curve; this facilitates the computation of controls and the prediction of deformations in systems with unknown mechanical properties. The proposed model has an adaptive structure that can recalibrate to cope with changes in the mechanism or actuators. An experimental study with a robotic prototype is conducted to validate the proposed method.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationFrontiers in robotics and AI, Feb. 2019, v. 6, 4, p. 1-6-
dcterms.isPartOfFrontiers in robotics and AI-
dcterms.issued2019-02-05-
dc.identifier.scopus2-s2.0-85068508514-
dc.identifier.ros2018005619-
dc.identifier.eissn2296-9144en_US
dc.identifier.artn4en_US
dc.description.validate201908 bcrcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera0352-n01en_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Navarro-Alarcon_Computing_Pressure-Deformation_Maps.pdf1.8 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

142
Last Week
0
Last month
Citations as of Apr 14, 2024

Downloads

112
Citations as of Apr 14, 2024

SCOPUSTM   
Citations

2
Citations as of Apr 19, 2024

WEB OF SCIENCETM
Citations

3
Citations as of Apr 18, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.