Finding an optimized flight path for an UAV to seed a fire affected area.

Authors

  • Abhishek Kaushikkar Leland High School
  • Joshua Whitman

DOI:

https://doi.org/10.47611/jsrhs.v12i1.3866

Keywords:

Travelling Salesman, Path Planning, UAV, Autonomous

Abstract

Fires have devastated and cleared many areas of vegetation, and much of the terrain impacted is inaccessible by foot. As a result it is difficult and inefficient to re-seed these areas from the ground. One way of getting around this problem is by using an Unmanned Aerial Vehicle(UAV). Aerial vehicles are not hindered by topographical and organic features. However UAVs cannot remain in flight for extended periods of time. To maximize the UAVs potential, steps must be taken to limit its flight time. Our paper aims to find an algorithm that computes the most energy efficient path for the UAV to follow in order to re-seed the fire cleared areas in a forest and we calculate based on a few constraints. These constraints being that the UAV can only seed a circular area with a fixed radius, the UAV can translate in straight lines, the area is an N*N square, and the terrain varies in altitude, and the UAV translates at a constant velocity. We first calculate an array of nodes that the UAV can seed over, to get maximum coverage of the un-vegetated areas in the field. We then test three different algorithms to find the path that consumes the least amount of energy, based on our energy consumption model. We then compare the algorithms based on the energy consumption of their calculated paths, and their computation time.

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Author Biography

Joshua Whitman

Doctor of Philosophy in Mechanical Engineering. Graduate Research Assistant at University of Illinois at Urbana-Champaign

References or Bibliography

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Prateek, Peter, Ss, Emmanuel Goossaert, Hakim, Alim, and Zahra Nekudari. “Simulated Annealing Applied to the Traveling Salesman Problem: Code Capsule.” Code Capsule | A blog by Emmanuel Goossaert, July 15, 2014. https://codecapsule.com/2010/04/06/simulated-annealing-traveling-salesman/#:~:text=Simulated%20annealing%20is%20an%20optimization,designed%20specifically%20for%20this%20problem.

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Published

02-28-2023

How to Cite

Kaushikkar, A., & Whitman, J. (2023). Finding an optimized flight path for an UAV to seed a fire affected area. Journal of Student Research, 12(1). https://doi.org/10.47611/jsrhs.v12i1.3866

Issue

Section

HS Research Projects