_:n62a0251cce17434fab2843caf5fa4858xb45
<http://schema.org/description>
"Fighting wildfires is a precarious task, imperiling the lives of engaging\nfirefighters and those who reside in the fire's path. Firefighters need online\nand dynamic observation of the firefront to anticipate a wildfire's unknown\ncharacteristics, such as size, scale, and propagation velocity, and to plan\naccordingly. In this paper, we propose a distributed control framework to\ncoordinate a team of unmanned aerial vehicles (UAVs) for a human-centered\nactive sensing of wildfires. We develop a dual-criterion objective function\nbased on Kalman uncertainty residual propagation and weighted multi-agent\nconsensus protocol, which enables the UAVs to actively infer the wildfire\ndynamics and parameters, track and monitor the fire transition, and safely\nmanage human firefighters on the ground using acquired information. We evaluate\nour approach relative to prior work, showing significant improvements by\nreducing the environment's cumulative uncertainty residual by more than 10^2 and 10^5 times in firefront coverage performance to support human-robot\nteaming for firefighting. We also demonstrate our method on physical robots in\na mock firefighting exercise."
<https://deepai.org/profile/esmaeil-seraj>