Intercepting Unmanned Aerial Vehicle Swarms with Neural- Network-Aided Game-Theoretic Target Assignment
| Autor: | Todd E. Humphreys, Nicholas G. Montalbano |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Game theoretic Artificial neural network Computer science Distributed computing 020208 electrical & electronic engineering Control (management) Process (computing) Swarm behaviour ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Drone 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Interception |
| Zdroj: | PLANS |
| DOI: | 10.1109/plans46316.2020.9110234 |
| Popis: | This paper examines the use of neural networks to perform low-level control calculations within a larger game-theoretic framework for drone swarm interception. As unmanned aerial vehicles (UAVs) become more capable and less expensive, their malicious use becomes a greater public threat. This paper examines the problem of intercepting rogue UAV swarms by exploiting the underlying game-theoretic nature of large-scale pursuit-evasion games to develop locally optimal profiles for target assignment. It paper also examines computationally efficient means to streamline this process. |
| Databáze: | OpenAIRE |
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