Autonomous Search and Rescue with Modeling and Simulation and Metrics

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dc.contributor.authorBihl, Trevor
dc.contributor.authorCox, Chadwick
dc.contributor.authorAdams, Yuki
dc.contributor.authorPennington, James
dc.date.accessioned2022-12-27T19:01:10Z
dc.date.available2022-12-27T19:01:10Z
dc.date.issued2023-01-03
dc.description.abstractUnmanned Aerial Vehicles (UAVs) provide rapid exploration capabilities in search and rescue missions while accepting more risks than human operations. One limitation in that current UAVs are heavily manpower intensive and such manpower demands limit abilities to expand UAV use. In operation, manpower demands in UAVs range from determining tasks, selecting waypoints, manually controlling platforms and sensors, and tasks in between. Often, even a high level of autonomy is possible with human generated objectives and then autonomous resource allocation, routing, and planning. However, manually generating tasks and scenarios is still manpower intensive. To reduce manpower demands and move towards more autonomous operations, the authors develop an adaptive planning system that takes high level goals from a human operator and translates them into situationally relevant tasking. For expository simulation, the authors further describe constructing a scenario around the 2018 Hawaii Puna lava natural disaster.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2023.223
dc.identifier.isbn978-0-9981331-6-4
dc.identifier.urihttps://hdl.handle.net/10125/102853
dc.language.isoeng
dc.relation.ispartofProceedings of the 56th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDisaster Information, Resilience, for Emergency and Crisis Technologies
dc.subjectartificial intelligence
dc.subjectautonomy
dc.subjectdisaster response
dc.subjectdrones
dc.subjectsimulation
dc.titleAutonomous Search and Rescue with Modeling and Simulation and Metrics
dc.type.dcmitext
prism.startingpage1768

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