Iterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environments

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dc.citation.conferenceDate2013-04-08en_US
dc.citation.conferenceNameACM International Conference on Hybrid Systems: Computation and Controlen_US
dc.citation.journalTitleACM International Conference on Hybrid Systems: Computation and Controlen_US
dc.contributor.authorMaly, Matthew R.en_US
dc.contributor.authorLahijanian, Mortezaen_US
dc.contributor.authorKavraki, Lydia E.en_US
dc.contributor.authorKress-Gazit, Hadasen_US
dc.contributor.authorVardi, Moshe Y.en_US
dc.date.accessioned2013-04-17T15:57:01Zen_US
dc.date.available2014-04-18T05:10:04Zen_US
dc.date.issued2013en_US
dc.description.abstractThis paper considers the problem of motion planning for a hybrid robotic system with complex and nonlinear dynamics in a partially unknown environment given a temporal logic specification. We employ a multi-layered synergistic framework that can deal with general robot dynamics and combine it with an iterative planning strategy. Our work allows us to deal with the unknown environmental restrictions only when they are discovered and without the need to repeat the computation that is related to the temporal logic specification. In addition, we define a metric for satisfaction of a specification. We use this metric to plan a trajectory that satisfies the specification as closely as possible in cases in which the discovered constraint in the environment renders the specification unsatisfiable. We demonstrate the efficacy of our framework on a simulation of a hybrid second-order car-like robot moving in an office environment with unknown obstacles. The results show that our framework is successful in generating a trajectory whose satisfaction measure of the specification is optimal. They also show that, when new obstacles are discovered, the reinitialization of our framework is computationally inexpensive.en_US
dc.embargo.terms1 yearen_US
dc.identifier.citationMaly, Matthew R., Lahijanian, Morteza, Kavraki, Lydia E., et al.. "Iterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environments." <i>ACM International Conference on Hybrid Systems: Computation and Control,</i> (2013) ACM: http://dx.doi.org/10.1145/2461328.2461380.en_US
dc.identifier.doihttp://dx.doi.org/10.1145/2461328.2461380en_US
dc.identifier.urihttps://hdl.handle.net/1911/70941en_US
dc.language.isoengen_US
dc.publisherACMen_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.subject.keywordmotion planningen_US
dc.subject.keywordtemporal logicen_US
dc.subject.keywordformal synthesisen_US
dc.titleIterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environmentsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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