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dc.contributor.authorZia, Ali
dc.contributor.authorGulrez, Tauseef
dc.contributor.authorChaudhry, Tayyab
dc.date.accessioned2020-06-15T05:06:18Z
dc.date.available2020-06-15T05:06:18Z
dc.date.issued2010
dc.identifier.isbn9781424481347
dc.identifier.doi10.1109/isda.2010.5687048
dc.identifier.urihttp://hdl.handle.net/10072/394646
dc.description.abstractAn accurate model creation and path-planning of the environment has been found to be an important precondition for various robotics tasks such as search and rescue, manipulation and obstacle avoidance. Over the past few years, the topic of learning model representations has received considerable attention e.g. building city models, reconstruction of ancient art and building other environment models. Majority of the environmental modelling research relied upon single sensor like cameras or lasers, to acquire features data. In this paper we present an approach which fuses vision and range information together to learn an accurate and better environment approximation.
dc.publisherIEEE
dc.relation.ispartofconferencename2010 10th International Conference on Intelligent Systems Design and Applications (ISDA)
dc.relation.ispartofconferencetitle2010 10th International Conference on Intelligent Systems Design and Applications
dc.relation.ispartofdatefrom2010-11-29
dc.relation.ispartofdateto2010-12-01
dc.titleHeterogeneous sensor fusion framework for autonomous mobile robot obstacle avoidance
dc.typeConference output
dcterms.bibliographicCitationZia, A; Gulrez, T; Chaudhry, T, Heterogeneous sensor fusion framework for autonomous mobile robot obstacle avoidance, 2010 10th International Conference on Intelligent Systems Design and Applications, 2010
dc.date.updated2020-06-15T04:52:09Z
gro.hasfulltextNo Full Text
gro.griffith.authorZia, Ali


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    Contains papers delivered by Griffith authors at national and international conferences.

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