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Massive Autonomous UAV Path Planning: A Neural Network Based Mean-Field Game Theoretic Approach
[article]
2019
arXiv
pre-print
This paper investigates the autonomous control of massive unmanned aerial vehicles (UAVs) for mission-critical applications (e.g., dispatching many UAVs from a source to a destination for firefighting). Achieving their fast travel and low motion energy without inter-UAV collision under wind perturbation is a daunting control task, which incurs huge communication energy for exchanging UAV states in real time. We tackle this problem by exploiting a mean-field game (MFG) theoretic control method
arXiv:1905.04152v1
fatcat:vfgqcfuvcnfh3kdvuyenuan4si