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Coordinated Control of UAVs for Human-Centered Active Sensing of Wildfires

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Document pages: 8 pages

Abstract: Fighting wildfires is a precarious task, imperiling the lives of engagingfirefighters and those who reside in the fire s path. Firefighters need onlineand dynamic observation of the firefront to anticipate a wildfire s unknowncharacteristics, such as size, scale, and propagation velocity, and to planaccordingly. In this paper, we propose a distributed control framework tocoordinate a team of unmanned aerial vehicles (UAVs) for a human-centeredactive sensing of wildfires. We develop a dual-criterion objective functionbased on Kalman uncertainty residual propagation and weighted multi-agentconsensus protocol, which enables the UAVs to actively infer the wildfiredynamics and parameters, track and monitor the fire transition, and safelymanage human firefighters on the ground using acquired information. We evaluateour approach relative to prior work, showing significant improvements byreducing the environment s cumulative uncertainty residual by more than $ 10^2$ and $ 10^5 $ times in firefront coverage performance to support human-robotteaming for firefighting. We also demonstrate our method on physical robots ina mock firefighting exercise.

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