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dc.contributor.authorOtahal, Thomas J
dc.contributor.authorTanner, Herbert G
dc.date.accessioned2009-01-21T15:40:43Z
dc.date.available2009-01-21T15:40:43Z
dc.date.issued2009-01-21T15:40:43Z
dc.identifier.urihttp://hdl.handle.net/1928/7627
dc.description.abstractThe accurate estimation of robot position and orientation in real-time is one of the fundamental challenges in mobile robotics. The Extended Kalman Filter is a nonlinear real-time recursive time domain filter that combines available sensor data to produce an accurate estimate of state, and has been successfully applied to the localization problem in mobile robotics and aircraft navigation. This report describes an Extended Kalman Filter implementa- tion for the Khepera II mobile robotics platform that seeks to produce accurate localization estimates in real-time using wheel odometry data, IR sensor range data, and compass heading data.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesME-TRen_US
dc.relation.ispartofseries08-001en_US
dc.subjectMobile robotsen_US
dc.subjectlocalizationen_US
dc.titleExtended Kalman Filter Implementation for the Khepera II Mobile Roboten_US
dc.typeTechnical Reporten_US


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