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dc.contributor.authorWortham, RH
dc.contributor.authorGaudl, Swen
dc.contributor.authorBryson, JJ
dc.date.accessioned2019-10-30T10:26:44Z
dc.date.available2019-10-30T10:26:44Z
dc.date.issued2018-11-02
dc.identifier.issn1389-0417
dc.identifier.issn1389-0417
dc.identifier.urihttp://hdl.handle.net/10026.1/15085
dc.description.abstract

The Instinct Planner is a new biologically inspired reactive planner, based on an established behaviour based robotics methodology and its reactive planner component — the POSH planner implementation. It includes several significant enhancements that facilitate plan design and runtime debugging. It has been specifically designed for low power processors and has a tiny memory footprint. Written in C++, it runs efficiently on both ARDUINO (ATMEL AVR) and MICROSOFT VC++ environments and has been deployed within a low cost maker robot to study AI Transparency. Plans may be authored using a variety of tools including a new visual design language, currently implemented using the DIA drawing package.

dc.format.extent207-215
dc.languageen
dc.language.isoen
dc.publisherElsevier
dc.rightsAttribution-NonCommercial 4.0 International
dc.rightsAttribution-NonCommercial 4.0 International
dc.rightsAttribution-NonCommercial 4.0 International
dc.rightsAttribution-NonCommercial 4.0 International
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectReactive planning
dc.subjectInstinct
dc.subjectArduino
dc.subjectPOSH
dc.subjectBOD
dc.subjectBio-inspired
dc.titleInstinct: A biologically inspired reactive planner for intelligent embedded systems
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000470116200023&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.volume57
plymouth.publication-statusPublished
plymouth.journalCognitive Systems Research
dc.identifier.doi10.1016/j.cogsys.2018.10.016
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2018-10-06
dc.rights.embargodate9999-12-31
dc.identifier.eissn1389-0417
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1016/j.cogsys.2018.10.016
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc/4.0/
rioxxterms.licenseref.startdate2018-11-02
rioxxterms.typeJournal Article/Review


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