Bharadwaj, S., Dimitrova, R. and Topcu, U. (2019) Synthesis of surveillance strategies via belief abstraction. In: 2018 IEEE Conference on Decision and Control (CDC). 2018 IEEE Conference on Decision and Control (CDC), 17-19 Dec 2018, Miami Beach, FL, USA. IEEE , pp. 4159-4166. ISBN 9781538613962
Abstract
We provide a novel framework for the synthesis of a controller for a robot with a surveillance objective, that is, the robot is required to maintain knowledge of the location of a moving, possibly adversarial target. We formulate this problem as a one-sided partial-information game in which the winning condition for the agent is specified as a temporal logic formula. The specification formalizes the surveillance requirement given by the user by quantifying and reasoning over the agent's beliefs about a target's location. We also incorporate additional non-surveillance tasks. In order to synthesize a surveillance strategy that meets the specification, we transform the partial-information game into a perfect-information one, using abstraction to mitigate the exponential blow-up typically incurred by such transformations. This transformation enables the use of off-the-shelf tools for reactive synthesis. We evaluate the proposed method on two case-studies, demonstrating its applicability to diverse surveillance requirements.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Feb 2020 11:58 |
Last Modified: | 05 Feb 2020 15:46 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/cdc.2018.8619353 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156426 |