Learning from sensory predictions for autonomous and adaptive exploration of object shape with a tactile robot

Martinez-Hernandez, U., Rubio-Solis, A. and Prescott, T.J. orcid.org/0000-0003-4927-5390 (2019) Learning from sensory predictions for autonomous and adaptive exploration of object shape with a tactile robot. Neurocomputing. ISSN 0925-2312

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 Elsevier B.V. This is an author produced version of a paper subsequently published in Neurocomputing. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Active and adaptive perception; Sensorimotor control; Autonomous tactile exploration; Bayesian inference
Dates:
  • Accepted: 9 October 2019
  • Published (online): 5 December 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
FunderGrant number
EUROPEAN COMMISSION - FP6/FP7EFAA - 270490
EUROPEAN COMMISSION - HORIZON 2020785907
Depositing User: Symplectic Sheffield
Date Deposited: 08 Jan 2020 13:26
Last Modified: 08 Jan 2020 13:26
Status: Published online
Publisher: Elsevier BV
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.neucom.2019.10.114

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Filename: Neurocomputing_Uriel_2019.pdf

Licence: CC-BY-NC-ND 4.0

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