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
2015/6
Journal
KI-Künstliche Intelligenz
Volume
29
Pages
193-201
Publisher
Springer Berlin Heidelberg
Description
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.
Total citations
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Scholar articles
I Kruijff-Korbayová, F Colas, M Gianni, F Pirri… - KI-Künstliche Intelligenz, 2015