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dc.contributor.authorHewitt, Robert A.en
dc.contributor.authorMarshall, Joshua A.en
dc.date.accessioned2016-02-24T15:51:38Z
dc.date.available2016-02-24T15:51:38Z
dc.date.issued2016-02-24
dc.identifier.otherhttp://dx.doi.org/10.1109/IROS.2015.7353634
dc.identifier.urihttp://hdl.handle.net/1974/14050
dc.description.abstractAlthough passive sensors are widely used for many mobile robotics applications that perform mapping and localization functions, there are many environments (e.g., mining and planetary) where active sensors are more practical. However, at present, most 3D SLAM algorithms that do use LiDAR and/or time-of-flight (ToF) sensors exploit only range and bearing information associated with these measurements, but not intensity information. This paper presents a new approach that attempts to explicitly incorporate an intensity model as part of a sparse bundle adjustment (SBA) estimation problem. An observability analysis shows that a solution exists, and simulation results verify its potential utility.en
dc.language.isoenen
dc.subjectCamerasen
dc.subjectComputational Modelingen
dc.subjectLaser Radaren
dc.subjectQuaternionsen
dc.subjectSimultaneous Localizaion and Mappingen
dc.titleTowards Intensity-Augmented SLAM with LiDAR and ToF Sensorsen
dc.typejournal articleen


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