700.741 (18W) Vision Based State Estimation and Sensor Fusion

Wintersemester 2018/19

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Erster Termin der LV
05.10.2018 08:00 - 10:00 , L4.1.02 ICT-Lab
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Überblick

Lehrende/r
LV-Titel englisch
Vision Based State Estimation and Sensor Fusion
LV-Art
Kurs (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
3.0
Anmeldungen
8 (20 max.)
Organisationseinheit
Unterrichtssprache
Englisch
mögliche Sprache/n der Leistungserbringung
Englisch
LV-Beginn
05.10.2018
eLearning
zum Moodle-Kurs

LV-Beschreibung

Intendierte Lernergebnisse

In this lecture, the student will acquire knowledge on how to model sensors with their uncertainties and how to use these models for probabilistic state estimation through non-linear estimators and non-linear optimization methods. In particular, the student will learn how to model a camera and use it as a sensor to track the pose in 6DoF. Furthermore, the lecture will discuss the non-linear observability analysis of said estimators.

Lehrmethodik

Theory from the lecture "Vision Based State Estimation and Sensor Fusion" (700.740) will be deepened in this practical course  with excercices (KU 700.741 ).

Inhalt/e

    Overview:

        Sensor Modeling Overview

        Camera Overview

    Camera I:

        Distortion

        Epipolar Geometry

    Camera II:

        Camera Matrix

        Camera Calibration

    Camera III:

        Features

        Pose Estimation

    Camera IV:

        N-Point Algorithm

        Ransac

    Sensors:

        Barometer Model

        GPS Model

        IMU Model

        Continous/Discrete

    Filter I:

        State Estimation Overview

        Filter Overview

        Maximum Likelihood

        Wiener Filter

    Filter II:

        Kalman Filter

        Extended Kalman Filter

    Filter III:

        Unscented Kalman Filter

        Iterative Extended Kalman Filter

        Sensor Fusion Overview

        Simplification of H

    Bundle Adjustment:

        Bundle Adjustment

        Matirx sparsety/FactorGraphs (Simplification of H)

        IMU-preintegration

    Observability Analysis:

        Observability Analysis

        Linear OA

        Nonlinear OA

    SLAM/VIO

    Exam Preparation

Prüfungsinformationen

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Autonomous Systems and Robotics: Advanced (ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (siehe Anhang 3) ( 0.0h VK, VO / 30.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Autonomous Systems and Robotics (WI) (Wahlfach)
      • Wahl aus dem LV-Katalog (siehe Anhang 3) ( 0.0h VK, VO / 30.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Technischer Schwerpunkt (Control and Measurement Systems) (Pflichtfach)
      • 1.4-1.5 Kurs oder Labor ( 4.0h KU / 6.0 ECTS)
        • 700.741 Vision Based State Estimation and Sensor Fusion (2.0h KS / 3.0 ECTS)

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