Routing for a Network of Drones with the Aim of Search and Rescue
Subject Areas : General
Atefeh Vasi
1
,
taha bazvand
2
,
Mohsen Nickray
3
1 - Master's degree, Computer Group, Faculty of Engineering University of Qom, Qom, Iran .
2 - Master's degree, Aerospace Group, Faculty of Aerospace Engineering, Malek Ashtar University of Technology, Tehran, Iran
3 - Assistant Professor, Computer Group, Faculty of Engineering University of Qom, Qom, Iran.
Keywords: Drone Routing-Genetic Algorithm- Q-Learning Algorithm- Network of Drones- Optimization. ,
Abstract :
Network routing of drones for search and rescue operations is a critical challenge. This challenge arises due to the physical limitations of drones, adverse environmental conditions, and time constraints. In this paper, a novel approach for network routing of drones using the Q-Learning algorithm is proposed. This algorithm enables drones to automatically determine optimal paths in complex environments and adapt to environmental changes. Simulation results demonstrate that the Q-Learning algorithm can find shorter and more efficient routes compared to genetic algorithms. These findings highlight Q-Learning as a promising method for improving network routing of drones in search and rescue operations
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