ICUAS'17 Paper Abstract

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Paper FrA4.1

Ghamry, Khaled A. (Concordia University), Kamel, Mohamed A. (Military Technical College), Zhang, Youmin (Concordia University)

Multiple UAVs in Forest Fire Fighting Mission Using Particle Swarm Optimization

Scheduled for presentation during the "UAS Applications - VIII" (FrA4), Friday, June 16, 2017, 10:00−10:20, Lummus Island

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 25, 2024

Keywords UAS Applications, Environmental Issues, Technology Challenges

Abstract

This paper investigates forest fires fighting application using team(s) of unmanned aerial vehicles (UAVs), in view of UAVs having great advantages in performing such tasks. However, important challenges in fire fighting missions in general are to perform the task with high performance in minimum time. In this paper, it is assumed that the fire spots are already detected and their coordinates will be sent to the fire fighting UAVs teams. Once the fire fighting team(s) receive relevant information, the team begins to solve the task assignment problem using the auction-based algorithm. The objective of the algorithm is to assign each UAV to each fire spot according to their relative distances, to minimize the distance traveled between each UAV's initial position and its assigned fire spot. Then, each UAV will optimally plan its path to its assigned fire spot by using particle swarm optimization (PSO) algorithm. The proposed algorithm calculates the optimal control inputs while taking into consideration the control inputs constraints while avoiding potential UAVs collisions during motion.

 

 

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