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

• Published in: KI. Künstliche Intelligenz (Oldenbourg) 2015-06, Vol.29 (2), p.193-201
• Main Authors: Kruijff-Korbayová, Ivana, Colas, Francis, Gianni, Mario, Pirri, Fiora, de Greeff, Joachim, Hindriks, Koen, Neerincx, Mark, Ögren, Petter, Svoboda, Tomáš, Worst, Rainer
• Format: Magazinearticle
• Language: English
• Subjects: Artificial Intelligence; Computer Science; Disaster response robotics; Persistent environment models; Persistent human-robot teaming; Persistent multi-robot action models; Persistent multi-robot collaboration models; Research Project; Robotics; Software Engineering/Programming and Operating Systems; User-centric design
• ISSN: 0933-1875; 1610-1987; 1610-1987; 0933-1875
• DOI: 10.1007/s13218-015-0352-5

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.