This repository is associated with a senior capstone project on how Kalman filtering, particularly extended Kalman filter EKF and unscented Kalman filter UKF , can be applied to bioinformatics in order to accurately estimate states and parameters of a model given a dataset. Work fast with our official CLI. Learn more. If nothing happens, download GitHub Desktop and try again.
Robot Localization and Kalman Filters
Kalman filter - Wikipedia
In statistics and control theory , Kalman filtering , also known as linear quadratic estimation LQE , is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. The Kalman filter has numerous applications in technology. A common application is for guidance, navigation, and control of vehicles, particularly aircraft, spacecraft and dynamically positioned ships. Kalman filters also are one of the main topics in the field of robotic motion planning and control and can be used in trajectory optimization.
Kalman Filter is an easy topic. However, many tutorials are not easy to understand. Most of the tutorials require extensive mathematical background that makes it difficult to understand. As well, most of the tutorials are lacking practical numerical examples.
Kalman filter sanctuary - including continuous-discrete extended Kalman filter. Bring additional filters here for a bigger collection. Work fast with our official CLI.