700.741 (18W) Vision Based State Estimation and Sensor Fusion
Überblick
- Lehrende/r
- LV-Titel englisch Vision Based State Estimation and Sensor Fusion
- LV-Art Kurs (prüfungsimmanente LV )
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 3.0
- Anmeldungen 8 (20 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- mögliche Sprache/n der Leistungserbringung Englisch
- LV-Beginn 05.10.2018
- eLearning zum Moodle-Kurs
Zeit und Ort
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 inkl. Einsatz von eLearning-Tools
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 BenotungsschemaPosition 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)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
- 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)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
- 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)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
- 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)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
- 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)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Fach: Autonomous Systems and Robotics: Advanced (ASR)
(Wahlfach)
- 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)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Fach: Autonomous Systems and Robotics (WI)
(Wahlfach)
- 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)
-
1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
-
Fach: Technischer Schwerpunkt (Control and Measurement Systems)
(Pflichtfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Wintersemester 2022/23
- 700.741 KS Vision Based State Estimation and Sensor Fusion (2.0h / 3.0ECTS)
-
Wintersemester 2021/22
- 700.741 KS Vision Based State Estimation and Sensor Fusion (2.0h / 3.0ECTS)
-
Wintersemester 2020/21
- 700.741 KS Vision Based State Estimation and Sensor Fusion (2.0h / 3.0ECTS)
-
Wintersemester 2019/20
- 700.741 KS Vision Based State Estimation and Sensor Fusion (2.0h / 3.0ECTS)
-
Wintersemester 2017/18
- 700.741 KS Vision Based State Estimation and Sensor Fusion (2.0h / 3.0ECTS)
-
Wintersemester 2016/17
- 700.741 KS Vision Based State Estimation and Sensor Fusion (2.0h / 3.0ECTS)