Controlling stochastic growth processes on lattices: Wildfire management with robotic fire extinguishers
Name
cdc_2014.pdf
Size
1.09 MB
Format
Adobe PDF
Checksum (MD5)
f9a9413ae69d4661a6965d308b29ca82
Author(s) • •
Somanath, Amith
Karaman, Sertac
Youcef-Toumi, Kamal
Date Issued
February 2015
Journal
2014 IEEE 53rd Annual Conference on Decision and Control (CDC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Somanath, Amith, et al. "Controlling Stochastic Growth Processes on Lattices: Wildfire Management with Robotic Fire Extinguishers." 2014 IEEE 53rd Annual Conference on Decision and Control (CDC), 15-17 December, 2014, Los Angeles, California, IEEE, 2014, pp. 1432–37.
Version
Author's final manuscript
Abstract
Forest fires continue to cause considerable social and economic damage. Fortunately, the emergence of new robotics technologies, including capable autonomous unmanned aerial vehicles, may help improve wildfire management in the near future. In this paper, we characterize the number of vehicles required to combat wildfires, using a percolation-theoretic analysis that originated in the mathematical physics community. We model the wildfire as a stochastic growth process on a square lattice, where the local growth probabilities depend on the presence of robotic fire-extinguishing vehicles. We develop two control policies: First treats only a fraction of burning nodes at a given time, and the second treats burning nodes only at finite time intervals. We characterize the conditions under which these policies can stabilize a wildfire, i.e., ensure the fire stops eventually almost surely. We also provide computational results which demonstrate our theoretical analysis.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CDC.2014.7039602