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dc.contributor.supervisorStoelen, Martin
dc.contributor.authorMelidis, Christos
dc.contributor.otherSchool of Engineering, Computing and Mathematicsen_US
dc.date.accessioned2017-09-29T15:41:10Z
dc.date.issued2017
dc.date.issued2017
dc.identifier10487957en_US
dc.identifier.urihttp://hdl.handle.net/10026.1/9998
dc.description.abstract

This thesis puts forward a novel way of control for robotic morphologies. Taking inspiration from Behaviour Based robotics and self-organisation principles, we present an interfacing mechanism, capable of adapting both to the user and the robot, while enabling a paradigm of intuitive control for the user. A transparent mechanism is presented, allowing for a seamless integration of control signals and robot behaviours. Instead of the user adapting to the interface and control paradigm, the proposed architecture allows the user to shape the control motifs in their way of preference, moving away from the cases where the user has to read and understand operation manuals or has to learn to operate a specific device. The seminal idea behind the work presented is the coupling of intuitive human behaviours with the dynamics of a machine in order to control and direct the machine dynamics. Starting from a tabula rasa basis, the architectures presented are able to identify control patterns (behaviours) for any given robotic morphology and successfully merge them with control signals from the user, regardless of the input device used. We provide a deep insight in the advantages of behaviour coupling, investigating the proposed system in detail, providing evidence for and quantifying emergent properties of the models proposed. The structural components of the interface are presented and assessed both individually and as a whole, as are inherent properties of the architectures. The proposed system is examined and tested both in vitro and in vivo, and is shown to work even in cases of complicated environments, as well as, complicated robotic morphologies. As a whole, this paradigm of control is found to highlight the potential for a change in the paradigm of robotic control, and a new level in the taxonomy of human in the loop systems.

en_US
dc.language.isoen
dc.publisherUniversity of Plymouth
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectHuman-robot interactionen_US
dc.subjectRecurrent neural networksen_US
dc.subjectAdaptive systemsen_US
dc.subjectIntuitive robot controlen_US
dc.subjectSelf-organisationen_US
dc.subjectBehavioural couplingen_US
dc.subjectBehaviour based roboticsen_US
dc.subject.classificationPhDen_US
dc.titleAdaptive Neural Architectures for Intuitive Robot Controlen_US
dc.typeThesis
plymouth.versionpublishableen_US
dc.identifier.doihttp://dx.doi.org/10.24382/670
dc.rights.embargodate2018-09-29T15:41:10Z
dc.rights.embargoperiod12 monthsen_US
dc.type.qualificationDoctorateen_US
rioxxterms.versionNA


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