Autonomous Search and Rescue with Modeling and Simulation and Metrics
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Date
2023-01-03
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1768
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Abstract
Unmanned 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.
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Disaster Information, Resilience, for Emergency and Crisis Technologies, artificial intelligence, autonomy, disaster response, drones, simulation
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10
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Proceedings of the 56th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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