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dc.contributor.authorIndelman, Vadim
dc.contributor.authorCarlone, Luca
dc.contributor.authorDellaert, Frank
dc.date.accessioned2015-08-13T14:06:56Z
dc.date.available2015-08-13T14:06:56Z
dc.date.issued2014
dc.identifier.citationIndelman, V.; Carlone, L.; & Dellaert, F. (2014). "Planning Under Uncertainty in the Continuous Domain: A Generalized Belief Space Approach". IEEE International Conference on Robotics and Automation (ICRA 2014), May 31 2014-June 7 2014, pp. 6763-6770.en_US
dc.identifier.urihttp://hdl.handle.net/1853/53725
dc.description© 2014 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.en_US
dc.descriptionDOI: 10.1109/ICRA.2014.6907858
dc.description.abstractThis work investigates the problem of planning under uncertainty, with application to mobile robotics. We propose a probabilistic framework in which the robot bases its decisions on the generalized belief , which is a probabilistic description of its own state and of external variables of interest. The approach naturally leads to a dual-layer architecture: an inner estimation layer, which performs inference to predict the outcome of possible decisions, and an outer decisional layer which is in charge of deciding the best action to undertake. The approach does not discretize the state or control space, and allows planning in continuous domain. Moreover, it allows to relax the assumption of maximum likelihood observations: predicted measurements are treated as random variables and are not considered as given. Experimental results show that our planning approach produces smooth trajectories while maintaining uncertainty within reasonable bounds.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectGeneralized belief spaceen_US
dc.subjectInner estimation layeren_US
dc.subjectInner inference layeren_US
dc.subjectMobile roboticsen_US
dc.subjectOuter decisional layeren_US
dc.subjectOuter inference layeren_US
dc.titlePlanning Under Uncertainty in the Continuous Domain: A Generalized Belief Space Approachen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Institute for Robotics and Intelligent Machinesen_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computingen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Interactive Computingen_US
dc.publisher.originalInstitute of Electrical and Electronics Engineers
dc.identifier.doi10.1109/ICRA.2014.6907858
dc.embargo.termsnullen_US


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