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dc.contributor.authorKortik, Sitaren_US
dc.contributor.authorSaranlı, U.en_US
dc.coverage.spatialHong Kong, China
dc.date.accessioned2016-02-08T12:03:06Z
dc.date.available2016-02-08T12:03:06Z
dc.date.issued2014-06-07en_US
dc.identifier.urihttp://hdl.handle.net/11693/27855
dc.descriptionDate of Conference: 31 May-7 June 2014
dc.descriptionConference name: 2014 IEEE International Conference on Robotics and Automation (ICRA)
dc.description.abstractIn this paper, we introduce a novel logic language and theorem prover for robotic task planning. Our language, which we call Linear Planning Logic (LPL), is a fragment of linear logic whose resource-conscious semantics are well suited for reasoning with dynamic state, while its structure admits efficient theorem provers for automatic plan construction. LPL can be considered as an extension of Linear Hereditary Harrop Formulas (LHHF), whose careful design allows the minimization of nondeterminism in proof search, providing a sufficient basis for the design of linear logic programming languages such as Lolli. Our new language extends on the expressivity of LHHF, while keeping the resulting nondeterminism in proof search to a minimum for efficiency. This paper introduces the LPL language, presents the main ideas behind our theorem prover on a smaller fragment of this language and finally provides an experimental illustration of its operation on the problem of task planning for the hexapod robot RHex. © 2014 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleIEEE International Conference on Robotics and Automationen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICRA.2014.6907404en_US
dc.titleLinear planning logic: An efficient language and theorem prover for robotic task planningen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage3764en_US
dc.citation.epage3770en_US
dc.identifier.doi10.1109/ICRA.2014.6907404en_US
dc.publisherIEEEen_US


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