Show simple item record

IMPLEMENTATION OF KALMAN FILTER TO TRACKING CUSTOM FOUR-WHEEL DRIVE FOUR-WHEEL-STEERING ROBOTIC PLATFORM

dc.contributor.advisorDavis, Christopher Cen_US
dc.contributor.authorStanley, Michael Patricken_US
dc.date.accessioned2010-10-07T05:32:12Z
dc.date.available2010-10-07T05:32:12Z
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1903/10762
dc.description.abstractVehicle tracking is an important component of autonomy in the robotics field, requiring integration of hardware and software, and the application of advanced algorithms. Sensors are often plagued with noise and require filtering. Additionally, no single sensor is sufficient for effective tracking. Data from multiple sensors is needed in order to perform effective tracking. The Kalman Filter provides a convenient and efficient solution for filtering and fusing sensor data as well as estimating noise error covariances. Consequently, it has been essential in tracking algorithms since its introduction in 1960. This thesis presents an application of the Kalman filter to tracking of a custom four-wheel-drive four-wheel-steering vehicle using a limited sensor suite. Sensor selection is discussed, along with the characteristics of the sensor noise as related to meeting the requirements of the Kalman filter for guaranteeing optimality. The filter requires the development of a dynamical model, which is derived using empirical data methods and evaluated. Tracking results are presented and compared to unfiltered data.en_US
dc.titleIMPLEMENTATION OF KALMAN FILTER TO TRACKING CUSTOM FOUR-WHEEL DRIVE FOUR-WHEEL-STEERING ROBOTIC PLATFORMen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentElectrical Engineeringen_US
dc.subject.pqcontrolledEngineering, Electronics and Electricalen_US
dc.subject.pqcontrolledEngineering, Mechanicalen_US
dc.subject.pquncontrolled4WSen_US
dc.subject.pquncontrolledKalman Filteren_US
dc.subject.pquncontrolledSensor Fusionen_US
dc.subject.pquncontrolledtrackingen_US
dc.subject.pquncontrolledwheel speeden_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record