Quadrature Kalman Filters with Applications to Robotic Manipulators

Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31254

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DC Field	Value	Language
dc.contributor.author	Al-Shabi M	-
dc.contributor.author	Cataford A	-
dc.contributor.author	Gadsden SA	-
dc.date.accessioned	2025-03-01T15:33:47Z	-
dc.date.available	2025-03-01T15:33:47Z	-
dc.date.issued	2017-10-01	-
dc.identifier.uri	http://hdl.handle.net/11375/31254	-
dc.description.abstract	In this work, well known Quadrature Kalman Filters (QKFs), namely 2-point QKF (SeQKF), 3-point QKF (ThQKF), and 4-point QKF (FoQKF), were used to monitor a 4- degree of freedom prismatic-revolute-revolute-revolute (PRRR) manipulator. This manipulator represents a well-known industrial arm robot. These methods are applied on a PRRR robot, and are compared in terms of stability, robustness, computation time, complexity, and the quality of the optimality. For completeness, the results were compared to those obtained from the popular Unscented Kalman Filter (UKF) and a special form of the UKF known as the Cubature Kalman Filter (CKF).	-
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)	-
dc.subject	4007 Control Engineering, Mechatronics and Robotics	-
dc.subject	40 Engineering	-
dc.subject	4010 Engineering Practice and Education	-
dc.title	Quadrature Kalman Filters with Applications to Robotic Manipulators	-
dc.type	Article	-
dc.date.updated	2025-03-01T15:33:46Z	-
dc.contributor.department	Mechanical Engineering	-
dc.identifier.doi	https://doi.org/10.1109/iris.2017.8250108	-
Appears in Collections:	Mechanical Engineering Publications

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