An efficient solution to the simultaneous localisation and mapping problem

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dc.contributor.author Williams, Stefan en_US
dc.contributor.author Dissanayake, Gamini en_US
dc.contributor.author Durrant-Whyte, Hugh en_US
dc.contributor.editor Hamel WR, Maciejewski AA en_US
dc.date.accessioned 2009-11-09T05:36:37Z
dc.date.available 2009-11-09T05:36:37Z
dc.date.issued 2002 en_US
dc.identifier 2004003404 en_US
dc.identifier.citation Williams Stefan, Dissanayake Gamini, and Durrant-Whyte Hugh 2002, 'An efficient solution to the simultaneous localisation and mapping problem', Institute of Electrical and Electronic Engineering, Washington DC, USA, pp. 406-411. en_US
dc.identifier.issn 0-7803-7272-7 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/2768
dc.description.abstract This paper presents a novel approach to the simultaneous localisation and mapping algorithm that exploits the manner in which observations are fused into the global map of the environment to manage the computational complexity of the algorithm and improve the data association process. Rather than incorporating every observation directly into the global map of the environment, the constrained local submap filter relies on creating an independent, local submap of the features in the immediate vicinity of the vehicle. This local submap is then periodically fused into the global map of the environment using appropriately formulated constraints between the common feature estimates. This approach is shown to be effective in reducing the computational complexity of maintaining the global map estimates as well as improving the data association process. en_US
dc.publisher Institute of Electrical and Electronic Engineering en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/ROBOT.2002.1013394 en_US
dc.title An efficient solution to the simultaneous localisation and mapping problem en_US
dc.parent Proceedings of IEEE International Conference on Robotics and Automation - vol 1 en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Washington DC, USA en_US
dc.identifier.startpage 406 en_US
dc.identifier.endpage 411 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.conference.location Washington DC,USA en_US
dc.for 091303 en_US
dc.personcode 0000020153 en_US
dc.personcode 011224 en_US
dc.personcode 0000020154 en_US
dc.percentage 50 en_US
dc.classification.name Autonomous Vehicles en_US
dc.classification.type FOR-08 en_US
dc.custom IEEE International Conference on Robots and Automation en_US
dc.date.activity 20020511 en_US
dc.location.activity Washington DC,USA en_US
dc.description.keywords computational complexity filtering theory mobile robots navigation position control state estimation en_US


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