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)

Abstract

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
• Status: Published
• Refereed: Yes
• 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
• Publisher: Springer
• ISSN: 0934-5043
• 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