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Field and Service Robotics pp 455–467Cite as

Aerial Vehicle Path Planning for Monitoring Wildfire Frontiers

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Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 113))

Abstract

This paper explores the use of unmanned aerial vehicles (UAVs) in wildfire monitoring. To begin establishing effective methods for autonomous monitoring, a simulation (FLAME) is developed for algorithm testing. To simulate a wildfire, the well established FARSITE fire simulator is used to generate realistic fire behavior models. FARSITE is a wildfire simulator that is used in the field by Incident Commanders (IC’s) to predict the spread of the fire using topography, weather, wind, moisture, and fuel data. The data obtained from FARSITE is imported into FLAME and parsed into a dynamic frontier used for testing hotspot monitoring algorithms. In this paper, points of interest along the frontier are established as points with a fireline intensity (British-Thermal-Unit/feet/second) above a set threshold. These interest points are refined into hotspots using the Mini-Batch K-means Clustering technique. A distance threshold differentiates moving hotspot centers and newly developed hotspots. The proposed algorithm is compared to a baseline for minimizing the sum of the max time untracked J(t). The results show that simply circling the fire performs poorly (baseline), while a weighted-greedy metric (proposed) performs significantly better. The algorithm was then run on a UAV to demonstrate the feasibility of real world implementation.

This work was supported in part by NASA grant NNX14AI10G and ONR grant N00014-14-1-0509.

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Authors and Affiliations

  1. Robot Decision Making Laboratory, School of Mechanical, Industrial & Manufacturing Engineering, Oregon State University, Corvallis, OR, 97331, USA

    Ryan C. Skeele & Geoffrey A. Hollinger

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  1. Ryan C. Skeele
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  2. Geoffrey A. Hollinger
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Correspondence to Ryan C. Skeele .

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Editors and Affiliations

  1. Robotics Institute, Carnegie Mellon, Pittsburgh, Pennsylvania, USA

    David S. Wettergreen

  2. Inst for Aerospace Studies, Univ of Toronto, Toronto, Ontario, Canada

    Timothy D. Barfoot

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Skeele, R.C., Hollinger, G.A. (2016). Aerial Vehicle Path Planning for Monitoring Wildfire Frontiers. In: Wettergreen, D., Barfoot, T. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-319-27702-8_30

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  • DOI: https://doi.org/10.1007/978-3-319-27702-8_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27700-4

  • Online ISBN: 978-3-319-27702-8

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