TRADR Project: Long-Term Human-Robot Teaming for Robot Assisted Disaster Response
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00235510" target="_blank" >RIV/68407700:21230/15:00235510 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s13218-015-0352-5" target="_blank" >http://dx.doi.org/10.1007/s13218-015-0352-5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s13218-015-0352-5" target="_blank" >10.1007/s13218-015-0352-5</a>
Alternative languages
Result language
angličtina
Original language name
TRADR Project: Long-Term Human-Robot Teaming for Robot Assisted Disaster Response
Original language description
Abstract This paper describes the project TRADR: Long- Term Human-Robot Teaming for Robot Assisted Disaster Response. Experience shows that any incident serious enough to require robot involvement will most likely involve a sequence of sorties over several hours, days and even months. TRADR focuses on the challenges that thus arise for the persistence of environment models, multi- robot action models, and human-robot teaming, in order to allow incremental capability improvement over the dura- tion of amission. TRADR applies a user centric design approach to disaster response robotics, with use cases involving the response to a medium to large scale industrial accident by teams consisting of human rescuers and several robots (both ground and airborne).This paper describes the fundamentals of the project: the motivation, objectives and approach in contrast to related work.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
KI - Künstliche Intelligenz, German Journal on Artificial Intelligence
ISSN
0933-1875
e-ISSN
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Volume of the periodical
29
Issue of the periodical within the volume
2
Country of publishing house
DE - GERMANY
Number of pages
9
Pages from-to
193-201
UT code for WoS article
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EID of the result in the Scopus database
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