Künstliche Intelligenz 29(2) - Mai 2015

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Zeitschriftenartikel
TRADR Project: Long-Term Human-Robot Teaming for Robot Assisted Disaster Response
(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Kruijff-Korbayová, Ivana; Colas, Francis; Gianni, Mario; Pirri, Fiora; Greeff, Joachim; Hindriks, Koen; Neerincx, Mark; Ögren, Petter; Svoboda, Tomáš; Worst, Rainer
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.