GRAVITAS: A model checking based planning and goal reasoning framework for autonomous systems

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Author(s)
Hou, Zhe
Year published
2021
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This work follow the verification as planning paradigm and propose to use model-checking techniques to solve planning and goal reasoning problems for autonomous systems with high-degree of assurance. It presents a novel modelling framework — Goal Task Network (GTN) that encompass both goal reasoning and planning under a unified formal description that enables the use of assurance tools. The paper provides a systematic method that highlights how an industrial model checker (PAT) can be used to solve goal reasoning and planning problems modelled by GTNs. Further, this paper also introduces the design of an automated system ...
View more >This work follow the verification as planning paradigm and propose to use model-checking techniques to solve planning and goal reasoning problems for autonomous systems with high-degree of assurance. It presents a novel modelling framework — Goal Task Network (GTN) that encompass both goal reasoning and planning under a unified formal description that enables the use of assurance tools. The paper provides a systematic method that highlights how an industrial model checker (PAT) can be used to solve goal reasoning and planning problems modelled by GTNs. Further, this paper also introduces the design of an automated system framework for Goal Reasoning And Verification for Independent Trusted Autonomous Systems (GRAVITAS). The proposed framework is demonstrated in an experiment that simulates a survey mission performed by the REMUS-100 autonomous underwater vehicle.
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View more >This work follow the verification as planning paradigm and propose to use model-checking techniques to solve planning and goal reasoning problems for autonomous systems with high-degree of assurance. It presents a novel modelling framework — Goal Task Network (GTN) that encompass both goal reasoning and planning under a unified formal description that enables the use of assurance tools. The paper provides a systematic method that highlights how an industrial model checker (PAT) can be used to solve goal reasoning and planning problems modelled by GTNs. Further, this paper also introduces the design of an automated system framework for Goal Reasoning And Verification for Independent Trusted Autonomous Systems (GRAVITAS). The proposed framework is demonstrated in an experiment that simulates a survey mission performed by the REMUS-100 autonomous underwater vehicle.
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Journal Title
Engineering Applications of Artificial Intelligence
Volume
97
Copyright Statement
© 2021 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Subject
Information and computing sciences
Engineering