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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 2/2015

01-06-2015 | Research Project

TRADR Project: Long-Term Human-Robot Teaming for Robot Assisted Disaster Response

Authors: Ivana Kruijff-Korbayová, Francis Colas, Mario Gianni, Fiora Pirri, Joachim de Greeff, Koen Hindriks, Mark Neerincx, Petter Ögren, Tomáš Svoboda, Rainer Worst

Published in: KI - Künstliche Intelligenz | Issue 2/2015

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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 duration of a mission. 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.
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Footnotes
1
Cf. the authors’ list for full names of the institutes listed here only by an abbreviation. For more information on the partners, please visit the project website: www.tradr-project.eu
 
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Metadata
Title
TRADR Project: Long-Term Human-Robot Teaming for Robot Assisted Disaster Response
Authors
Ivana Kruijff-Korbayová
Francis Colas
Mario Gianni
Fiora Pirri
Joachim de Greeff
Koen Hindriks
Mark Neerincx
Petter Ögren
Tomáš Svoboda
Rainer Worst
Publication date
01-06-2015
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2/2015
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-015-0352-5

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