Collaborative models for autonomous systems controller synthesis

Fraser, D., Giaquinta, R., Hoffmann, R., Ireland, M., Miller, A. and Norman, G. (2020) Collaborative models for autonomous systems controller synthesis. Formal Aspects of Computing, 32, pp. 157-186. (doi: 10.1007/s00165-020-00508-1)

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We show how detailed simulation models and abstract Markov models can be developed collaboratively to generate and implement effective controllers for autonomous agent search and retrieve missions. We introduce a concrete simulation model of an Unmanned Aerial Vehicle (UAV). We then show how the probabilistic model checker PRISM is used for optimal strategy synthesis for a sequence of scenarios relevant to UAVs and potentially other autonomous agent systems. For each scenario we demonstrate how it can be modelled using PRISM, give model checking statistics and present the synthesised optimal strategies. We then show how our strategies can be returned to the controller for the simulation model and provide experimental results to demonstrate the effectiveness of one such strategy. Finally we explain how our models can be adapted, using symmetry, for use on larger search areas, and demonstrate the feasibility of this approach.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Norman, Dr Gethin and Miller, Professor Alice and Giaquinta, Dr Ruben and Fraser, Mr Douglas and Hoffmann, Dr Ruth
Authors: Fraser, D., Giaquinta, R., Hoffmann, R., Ireland, M., Miller, A., and Norman, G.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Formal Aspects of Computing
ISSN (Online):1433-299X
Published Online:16 April 2020
Copyright Holders:Copyright The Author(s) © 2020
First Published:First published in Formal Aspects of Computing 32:157–186
Publisher Policy:Reproduced under a Creative Commons license

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