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Flood Disaster Mitigation: A Real-World Challenge Problem for Multi-agent Unmanned Surface Vehicles

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journal contribution
posted on 01.05.2011, 00:00 authored by Paul Scerri, Balajee Kannan, Prasanna Velagapudi, Kate Macarthur, Peter Stone, Matt Taylor, John M. Dolan, Alessandro Farinelli, Archie Chapman, M. Bernardine Dias, George Kantor

As we advance the state of technology for robotic systems, there is a need for defining complex real-world challenge problems for the multi-agent/robot community to address. A well-defined challenge problem can motivate researchers to aggressively address and overcome core domain challenges that might otherwise take years to solve. As the focus of multi-agent research shifts from the mature domains of UGV and UAVs to USVs, there is a need for outlining well-defined and realistic challenge problems. In this position paper, we define one such problem, flood disaster mitigation. The ability to respond quickly and effectively to disasters is essential to saving lives and limiting the scope of damage. The nature of floods dictates the need for a fast-deployable fleet of low-cost and small autonomous boats that can provide situational awareness (SA), damage assessment and deliver supplies before more traditional emergency response assets can access affected areas. In addition to addressing an essential need, the outlined application provides an interesting challenge problem for advancing fundamental research in multi-agent systems (MAS) specific to the USV domain. In this paper, we define a technical statement of this MAS challenge problem based and outline MAS specific technical constraints based on the associated real-world issues. Core MAS sub-problems that must be solved for this application include coordination, control, human interaction, autonomy, task allocation, and communication. This problem provides a concrete and real-world MAS application that will bring together researchers with a diverse range of expertise to develop and implement the necessary algorithms and mechanisms.




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