マルチエージェント強化学習による不正ドローンの協調探索・追跡
Cooperative Search and Track of Rogue Drones using Multiagent Reinforcement Learning
追跡UAVチームが強化学習で協調し、重要施設上空の不正ドローンを探索・検出・追跡する手法を提案し、シミュレーションで性能と拡張性を示した。
著者: Panayiota Valianti, Kleanthis Malialis, Panayiotis Kolios, Georgios Ellinas
分類: cs.MA, cs.AI, cs.RO, cs.SY, eess.SY
原文アブストラクト
This work considers the problem of intercepting rogue drones targeting sensitive critical infrastructure facilities. While current interception technologies focus mainly on the jamming/spoofing tasks, the challenges of effectively locating and tracking rogue drones have not received adequate attention. Solving this problem and integrating with recently proposed interception techniques will enable a holistic system that can reliably detect, track, and neutralize rogue drones. Specifically, this work considers a team of pursuer UAVs that can search, detect, and track multiple rogue drones over a sensitive facility. The joint search and track problem is addressed through a novel multiagent reinforcement learning scheme to optimize the agent mobility control actions that maximize the number of rogue drones detected and tracked. The performance of the proposed system is investigated under realistic settings through extensive simulation experiments with varying number of agents demonstrating both its performance and scalability.
