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Interactive Robotics Laboratory
Yu Gu, Professor

Tutorial: Understanding Nonlinear Kalman Filters, Part II: An Implementation Guide

Kalman filters provide an important technique for estimating the states of engineering systems. With several variations of nonlinear Kalman filters, there is a lack of guidelines for filter selection with respect to a specific research or engineering application. This creates a need for an in-depth discussion of the intricacies of different nonlinear Kalman filters. Particularly of interest for practical state estimation applications are the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). This tutorial is divided into three self-contained articles. Part II presents detailed information about the implementation of EKF and UKF, including equations, tips, and example codes.

Tutorial: Understanding Nonlinear Kalman Filters, Part II: An Implementation Guide

Authors: Matthew Rhudy, Yu Gu 

Document History: V1.0 uploaded on June 28, 2013.

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