course-details-portlet

TK8102 - Nonlinear State Estimation

About

Examination arrangement

Examination arrangement: Oral examination and Report
Grade: Passed/Failed

Evaluation Weighting Duration Grade deviation Examination aids
Approved report 50/100
Oral examination 50/100 D

Course content

The course is given every second year, next time in the Spring 2022. The course presents state estimation techniques for nonlinear dynamic systems with an additional focus on Simultaneous Localization And Mapping (SLAM) methods, the underlying theoretic foundation and implementation skills. The course is given in English.

Learning outcome

KNOWLEDGE: * A thorough knowledge of theory and methods for state estimation of deterministic and stochastic nonlinear dynamical systems * Relevant definitions and properties of observability * State estimation techniques: Filtering and smoothing * Kalman-based techniques for stochastic systems: Bayesian formulation, error-state Kalman filter and canonical form * Graphical models, Factor-graph based SLAM techniques * Parameter estimation * Data association * Applications in sensor fusion  SKILLS: * Proficiency in analyzing the observability properties of nonlinear dynamical systems * Proficiency in independently assessing the advantages and disadvantages of different estimation methods, and make a qualified choice of method for a given system * Proficiency in independently applying the different methods for estimator design * Proficiency in designing SLAM systems. GENERAL COMPETENCE: * Skills in applying this knowledge and proficiency in new areas and complete advanced tasks and projects * Skills in communicating extensive independent work, and master the technical terms of nonlinear state estimation * Ability to contribute to innovative thinking and innovation processes

Learning methods and activities

Study groups and optional problem sets. Project with report.

Required previous knowledge

TTK4115 Linear Systems Theory or similar.

Course materials

A collection of papers, which will be given at the beginning of the semester.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Doctoral degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2022

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Engineering Cybernetics
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Engineering Cybernetics

Examination

Examination arrangement: Oral examination and Report

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Oral examination 50/100 D
Room Building Number of candidates
Autumn ORD Approved report 50/100
Room Building Number of candidates
Spring ORD Oral examination 50/100 D
Room Building Number of candidates
Spring ORD Approved report 50/100
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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