Development of ucav fleet autonomy by reinforcement learning in a wargame simulation environment

Burak Yuksek, Mustafa Umut Demirezen, Gokhan Inalhan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In this study, we develop a machine learning based fleet autonomy for Unmanned Combat Aerial Vehicles (UCAVs) utilizing a synthetic simulation-based wargame environment. Aircraft survivability is modeled as Markov processes. Mission success metrics are developed to introduce collision avoidance and survival probability of the fleet. Flight path planning is performed utilizing the proximal policy optimization (PPO) based reinforcement learning method to obtain attack patterns with a multi-objective mission success criteria corresponding to the mission success metrics. Performance of the proposed system is evaluated by utilizing the Monte Carlo analysis in which a wider initial position interval is used when compared to the defined interval in the training phase. This provides a preliminary insight about the generalization ability of the RL agent.

Original languageEnglish
Title of host publicationAIAA Scitech 2021 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
Pages1-14
Number of pages14
ISBN (Print)9781624106095
Publication statusPublished - 2021
Externally publishedYes
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021 - Virtual, Online
Duration: 11 Jan 202115 Jan 2021

Publication series

NameAIAA Scitech 2021 Forum

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021
CityVirtual, Online
Period11/01/2115/01/21

Bibliographical note

Publisher Copyright:
© 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

Funding

The authors would like to thank Mustafa Demir at Istanbul Technical University Aerospace Research Center for his support and advice on implementation issues in Python.

FundersFunder number
Istanbul Technical University Aerospace Research Center

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