Qu, H. orcid.org/0000-0002-1643-8926 and Veres, S.M. (2016) Verification of logical consistency in robotic reasoning. Robotics and Autonomous Systems, 83. pp. 44-56. ISSN 0921-8890
Abstract
Most autonomous robotic agents use logic inference to keep themselves to safe and permitted behaviour. Given a set of rules, it is important that the robot is able to establish the consistency between its rules, its perception-based beliefs, its planned actions and their consequences. This paper investigates how a robotic agent can use model checking to examine the consistency of its rules, beliefs and actions. A rule set is modelled by a Boolean evolution system with synchronous semantics, which can be translated into a labelled transition system (LTS). It is proven that stability and consistency can be formulated as computation tree logic (CTL) and linear temporal logic (LTL) properties. Two new algorithms are presented to perform realtime consistency and stability checks respectively. Their implementation provides us a computational tool, which can form the basis of efficient consistency checks on-board robots.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Elsevier. This is an author produced version of a paper subsequently published in Robotics and Autonomous Systems. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Stability analysis; Robot programming; Formal verification |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 18 Jul 2016 13:59 |
Last Modified: | 18 Jul 2017 15:42 |
Published Version: | http://dx.doi.org/10.1016/j.robot.2016.06.005 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.robot.2016.06.005 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:102508 |