Applying Multi Agent System to Track Uav Movement
Abstract
The thesis introduces an innovative UAV detection system in five chapters. The first chapter introduces the current UAV market situation, the importance of the Counter UAV system (CUAS) and the reason to improve UAV detection. The commercial UAV market is booming. Meanwhile, the risks and threats from improper UAV usages are also booming. Although the government updates policies, there are other ways like CUAS to protect the public and facilities. The problem is a lack of an intelligent platform which can adapt many sensors for UAV detection. The hypothesis is that, the system can track the UAV’s movement by applying the multi-agent system (MAS) to UAV detection and track. The second chapter includes the literature reviews of the problems and multiple CUAS techniques. There are sensors for UAV detection and techniques for UAV interception. The following chapter proposes the investigation method overview, discussing the experiment design and the agent rules. The methods are inspired by the reviewed studies in the previous chapter. The last two chapter state the modifications for the final simulation. The processes, the scenarios, the logic flows and the result statistics of the experiment are explained. The experiment proves that the multi-agent system benefits the UAV track. At last, there is a brief discussion on conclusion and the future work of the project.
Degree
M.Sc.
Advisors
Matson, Purdue University.
Subject Area
Logic|Design|Artificial intelligence|Acoustics|Recreation|Aerospace engineering|Computer science|Electrical engineering|Law|Robotics|Transportation
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