The Amatrice deployment is mentioned with pictures in the book “The Future of Robotics”
published by Ernst \& Young Advisory Co., Ltd. Japan in 2017. URL of the book (in Japanese):
Posts Tagged: ‘emergency management’
Workshop on sharing data & other resources for emergency response robotics at ERF
The premise of the workshop is that there still remains a gap between results obtained in development conditions (by both research and industry) and making the technology truly effective in real environments, addressing the real needs of responders in emergency situations. The goal of the workshop is to discuss measures that will help to bridge the gap, and how to implement them with the engagement of academia, industry and end users. Data sharing can be considered as one such measure. The workshop scope includes also sharing other resources and any other relevant measures that can help improve robot-assisted emergency response capability in Europe.
The Workshop on sharing data and other resources for emergency response robotics will take place
on March 15, 8:30-10:00
during the European Robotics Forum.
Organizers:
Ivana Kruijff-Korbayova, German Institute for Artificial Intelligence (DFKI), Germany
Hartmut Surmann, Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Germany
Amatrice 3D reconstructions datasets are now public
The TRADR consortium has recently made public some rosbags which were shot inside the churches of San Francesco and Sant Agostino in Amatrice. These rosbags are datasets containing timestamped videos plus additional robot data.
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/sanfrancesco/inside/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/sanfrancesco/outside/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/sanfrancesco/outside_min/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/santagostino/outside_med/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/santagostino/inside/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/santagostino/outside/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/sanfrancesco/outside/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/sanfrancesco/outside_min/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/santagostino/outside_med/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/santagostino/inside/
http://www.dis.uniroma1.it/~alcor/earthquake_amatrice/models/santagostino/outside/
TRADR team at Exercise Unified Response in London
Several members of the TRADR team participated as observers at the Exercise Unified Response in London, March 1-4.
It was a large scale training exercise taking place at several sites in and around London, involving about 70 agencies and disaster response teams not only from London Firebrigade, but also international help from Italy, Cyprus and Hungary. The exercise simulated a building collapse over the Waterloo underground station in central London. The scenario was built in a disused power station in Dartford, Kent. We got really good insight, especially at the various higher levels, what a response to such a serious incident involves. It was also extremely valuable to see such a complex scenario from close up and see the immense activity of the responders, the higher levels of tactical and strategic command and many of the other actors involved in the response.Last but not least, there were aspects of the evaluation worth taking inspiration from.
Introducing TRADR
TRADR is an integrated research project funded by the EU FP7 Programme, ICT: Cognitive systems, interaction, robotics (Project Nr. 60963).
Using a proven-in-practice user-centric design methodology, TRADR develops novel S&T for human-robot teams to assist in disaster response efforts, over multiple missions: The novel S&T makes experience persistent. Various kinds of robots collaborate with human team members to explore the environment, and gather physical samples. Throughout this collaborative effort, TRADR enables the team to gradually develop its understanding of the disaster area over, multiple possibly asynchronous missions (persistent environment models), to improve team members’ understanding of how to work in the area (persistent multi-robot action models), and to improve team-work (persistent human-robot teaming).
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