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Coordinated Control of UAVs for Human-Centered Active Sensing of Wildfires | IEEE Conference Publication | IEEE Xplore

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


Abstract:

Fighting wildfires is a precarious task, imperiling the lives of engaging firefighters and those who reside in the fire’s path. Firefighters need online and dynamic obser...Show More

Abstract:

Fighting wildfires is a precarious task, imperiling the lives of engaging firefighters and those who reside in the fire’s path. Firefighters need online and dynamic observation of the firefront to anticipate a wildfire’s unknown characteristics, such as size, scale, and propagation velocity, and to plan accordingly. In this paper, we propose a distributed control framework to coordinate a team of unmanned aerial vehicles (UAVs) for a human-centered active sensing of wildfires. We develop a dual-criterion objective function based on Kalman uncertainty residual propagation and weighted multi-agent consensus protocol, which enables the UAVs to actively infer the wildfire dynamics and parameters, track and monitor the fire transition, and safely manage human firefighters on the ground using acquired information. We evaluate our approach relative to prior work, showing significant improvements by reducing the environments cumulative uncertainty residual in firefront coverage performance to support human-robot teaming for firefighting. We also demonstrate our method on physical robots in a mock firefighting exercise.
Date of Conference: 01-03 July 2020
Date Added to IEEE Xplore: 27 July 2020
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ISSN Information:

Conference Location: Denver, CO, USA

I. Introduction

Fighting wildfires is a dangerous task and requires accurate online information regarding firefront location, scale, shape, and propagation velocity [1], [2]. Firefighters may lose their lives as a consequence of inaccurately anticipating information either due to inherent stochasticity in fire behavior or low-quality information provided, such as low-resolution satellite images [3]. Firefighters need frequent, high-quality images to monitor the fire propagation and plan accordingly. As such, Multi-robots teams capable of fast scheduling and task allocation [4], [5], [6] with analytical temporal upper- bounds [7], [8] are of particular interest for this applications. Due to recent advances in aerial robotic technology, UAVs have been proposed as a solution to overcoming the challenges of needing real-time information in fighting fires [9].

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