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Antonin Segault, Federico Tajariol, & Ioan Roxin. (2015). #geiger : Radiation Monitoring Twitter Bots for Nuclear Post-Accident Situations. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: In the last decade, people have increasingly relied on social media platforms such as Twitter to share information on the response to a natural or a man-made disaster. This paper focuses on the aftermath of the Fukushima Daiichi nuclear disaster. Since the disaster, victims and volunteers have been sharing relevant information about radiation measurements by means of social media. The aim of this research is to explore the diffusion of information produced and shared by Twitter bots, to understand the degree of popularity of these sources and to check if these bots deliver original radiation measurements.
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Antonin Segault, Federico Tajariol, Yang Ishigaki, & Ioan Roxin. (2016). #geiger 2: Developing Guidelines for Radiation Measurements Sharing on Social Media. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Radiation measurements are key information in post-nuclear accident situations. Automated Twitter accounts have been used to share the readings, but often in an incomplete way from the perspective of data sharing and risk communication between citizen and radiation experts. In this paper, we investigate the requirements for radiation measurements completeness, by analyzing the perceived usefulness of several metadata items that may go along the measurement itself. We carried out a benchmark of existing uses, and conducted a survey with both experts and lay citizens. We thus produced a set of guidelines regarding the metadata that should be used, and the way to publish it.
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Corine H.G. Horsch, Nanja J. J. M. Smets, Mark A. Neerincx, & Raymond H. Cuijpers. (2013). Comparing performance and situation awareness in USAR unit tasks in a virtual and real environment. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 556–560). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: A convenient way to test Urban Search And Rescue (USAR) robots would be in virtual environments (VEs). Evaluations in VEs are generally accepted as alternative for real scenarios. There are obvious differences between operation in a real and virtual environment. Nonetheless, the current experiment showed no significant differences in situation awareness (SA) and performance during several elementary tasks (e.g. slalom) between a virtual world and a previous experiment in reality (Mioch, Smets, & Neerincx, 2012). Only small dependencies between the unit tasks were found. The effect of individual differences (like gender, km driven per year, and gaming experience), were significant for certain elementary tasks. Testing robots in virtual environments could still be useful even if differences between VE and reality exist, since comparisons of different conditions in VE seems to have the same results as the same comparison in the field (Bishop & Rohrmann, 2003; Van Diggelen, Looije, Mioch, Neerincx, & Smets, 2012).
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Van Tuan Le, Serge Stinckwich, Noury Bouraqadi, & Arnaud Doniec. (2012). Role-based dynamic coalitions of multi-tasked rescue robots. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Organizations allow structuring and coordinating the activities of robots that take part in a multi-robot system (MRS). Within a given organization, each robot is assigned to a role that governs its behavior and its interactions with the other members of the MRS. In this paper; we investigate in a class of problems where role allocation must be done dynamically. This applies, for example in the context of rescue robotic applications where neither the number of robots nor characteristics are known a priori. Furthermore, tasks to be performed are not necessarily all known or at least a portion of the information remains to be discovered (e.g. locations of victims). Finally, some robots may temporarily leave the MRS (for battery recharging) or permanently due to failure or breakage. We propose a solution that can dynamically allocate roles to robots and revise the allocation. This revision takes place in case of failure of agents or in case of discovery of a new task. This allocation allows agents to participate in several tasks. © 2012 ISCRAM.
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Rosemarijn Looije, Mark A. Neerincx, & Geert-Jan M. Kruijff. (2007). Affective collaborative robots for safety & crisis management in the field. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 497–506). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The lack of human-robot collaboration currently presents a bottleneck to widespread use of robots in urban search & rescue (USAR) missions. The paper argues that an important aspect of realizing human-robot collaboration is collaborative control, and the recognition and expression of affect. Affective collaborative robots can enhance joint human-robot performance by adapting the robot's (social) role and interaction to the user's affective state and the context. Current USAR robots lack these capabilities. This paper presents theory, application domains, and requirements for affective collaborative robots based on the current state of the art. With methods from cognitive architectures, affective computing, and human-robot interaction, three core functions of affective collaborative robots can be realized: sliding autonomy, affective communication, and adaptive attitude. These robot functions can substantially enhance the efficiency and effectiveness of rescue workers and meanwhile reduce their cognitive workload. Furthermore, robots with such functions can approach civilians in the field appropriately.
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Sanfilippo, F., & Rañó, I. (2023). Mimicking the Sense of Smell of Search and Rescue (SAR) Dogs: a Bio-inspired Steering Framework for Quadruped Robots. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 892–901). Omaha, USA: University of Nebraska at Omaha.
Abstract: Due to their sense of smell and ability to explore areas for missing people, dogs are valuable for search and rescue (SAR). Canines can discover humans under water, under snow, and even beneath crumbling structures because they can smell human scent. Building unmanned autonomous quadruped robots with canine agility is an attractive step to fully replicate the capabilities of dogs. Robots with legs are already capable of mimicking some of the physical traits of dogs, such as the capacity to traverse rough terrain. However, they would need to replicate also the level of sensory perception of a dog to successfully perform SAR operations. To achieve this, a navigation strategy that uses a direct sensor-motor coupling by following the principles of the Braitenberg vehicles is adopted in this work. This paper represents one of the first steps towards the connection of bio-inspired sensor-based steering mechanisms and bio-inspired locomotion for quadruped robots.
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Vladimir Zadorozhny, Pei-Ju Lee, & Michael Lewis. (2015). Collaborative Information Sensemaking for Multi-Robot Search and Rescue. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: In this paper, we consider novel information sensemaking methods for search and rescue operations that combine principles of information fusion and collective intelligence in scalable solutions. We will elaborate on several approaches that originated in different areas of information integration, sensor data management, and multi-robot urban search and rescue missions.
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Martin Voshell, & Stijn Oomes. (2006). Coordinating (Shared) perspectives in robot assisted search & rescue. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 188–196). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: From high fidelity field exercises to disaster response deployments, search and rescue robots are being readily integrated into rescue operations. Previous research has proposed that for such new technology to be successful in an operation the organization architecture needs to support the coordination of shared perspectives between the human team members and the robotic platforms. For this, the robot platforms need to be effective team players in the field of practice. Based on this conceptual model, this paper introduces a novel software interface utilizing virtual position and orientation indicators to alleviate perceptual ambiguities and navigation problems experienced by robot handlers and problem holders. By actively orchestrating and sharing these indicators between handler and operator displays, the interface caters to user expertise and to the natural competency of the human perceptual system. These probes provide a basic tool for aiding robot navigation and way-finding fundamental to effective team coordination and communication in urban search and rescue missions.
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