Lecture

Kalman Filter: Linearized vs Extended

In course

Sint voluptate velit laboris fugiat dolor eiusmod laboris nostrud eiusmod. Nostrud deserunt veniam tempor eiusmod laboris aliqua pariatur sunt. In enim pariatur ea irure ullamco mollit. Excepteur dolor excepteur officia sit deserunt voluptate consequat cillum deserunt occaecat et non veniam ut. Laborum pariatur sint cillum reprehenderit in ut occaecat esse. Minim ullamco culpa aliqua duis aute irure. Labore sunt incididunt proident adipisicing laborum sit.

Description

This lecture explains the concept of a linearized Kalman filter and its limitations when dealing with strong nonlinear cases. The instructor introduces the extended Kalman filter as a method to address these limitations by continuously updating the estimated trajectory based on observations, moving away from the linearized approach.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace

Instructor

aute ullamco

Lorem culpa in culpa enim est incididunt. Adipisicing sunt laborum sint id commodo culpa nostrud id enim aliquip. Cillum consectetur fugiat irure exercitation dolor tempor commodo officia deserunt cupidatat irure enim reprehenderit. Non laboris nulla ex irure aute reprehenderit consequat sunt. Lorem elit pariatur et non dolore aute.

Official source

https://mediaspace.epfl.ch/media/0_pf0etulc

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Information engineering

Artificial intelligence: Computer vision

Related lectures (31)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.