700.740 (16W) Vision Based State Estimation and Sensor Fusion
Überblick
- Lehrende/r
- LV-Titel englisch Vision Based State Estimation and Sensor Fusion
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 14 (300 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- mögliche Sprache/n der Leistungserbringung Deutsch , Englisch , Spanisch , Französisch
- LV-Beginn 01.10.2016
- 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
This lecture is closely linked to its practical counterpart (i.e. exercises) KU 700.741 "Vision Based State Estimation and Sensor Fusion". Students are highly encouraged to enroll in that course since the theoretical aspects in 700.740 (this lecture) will be deepened in the practical course.
Inhalt/e
This is the first time this lecture will take place. Feedback from the students is highly encouraged to ensure and improve the quality of this lecture. Below is a tentative agenda:
Date | Chapter | Content |
---|---|---|
05.10.2016 | Overview | Overview Sensor Modeling Overview Camera Overview |
12.10.2016 | Camera I | Distortion Epipolar Geometry |
19.10.2016 | Camera II | Camera Matrix Camera Calibration |
02.11.2016 | Camera III | Features Pose Estimation |
09.11.2016 | Camera IV | N-Point Algorithm Ransac |
16.11.2016 | Sensors | Barometer Model GPS Model IMU Model Continous/Discrete |
23.11.2016 | Filter I | State Estimation Overview Filter Overview Maximum Likelihood Wiener Filter |
30.11.2016 | Filter II | Kalman Filter Extended Kalman Filter |
07.12.2016 | Filter III | Unscented Kalman Filter Iterative Extended Kalman Filter Sensor Fusion Overview Simplifications of H |
14.12.2016 | Bundle Adjustment | Bundle Adjustment Matrix sparsety/Factor Graphs (Simplification of H) IMU-preintegration |
21.12.2016 | Observability Analysis | Observability Analysis Linear OA Nonlinear OA |
11.01.2016 | SLAM/VIO | SLAM/VIO |
18.01.2016 | Case Study | Case Study |
25.01.2016 | Exam Preparation | 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)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 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)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 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)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 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)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 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)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 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)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 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)
-
1.1-1.3 Vorlesung mit Kurs oder Vorlesung mit Seminar (
6.0h VK/VS / 12.0 ECTS)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 ECTS)
-
1.1-1.3 Vorlesung mit Kurs oder Vorlesung mit Seminar (
6.0h VK/VS / 12.0 ECTS)
-
Fach: Technischer Schwerpunkt (Control and Measurement Systems)
(Pflichtfach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Technische Ergänzung I
(Pflichtfach)
-
2.1-2.2 Vorlesung mit Kurs oder Vorlesung mit Seminar (
4.0h VK/VS / 8.0 ECTS)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 ECTS)
-
2.1-2.2 Vorlesung mit Kurs oder Vorlesung mit Seminar (
4.0h VK/VS / 8.0 ECTS)
-
Fach: Technische Ergänzung I
(Pflichtfach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Technische Ergänzung II
(Pflichtfach)
-
3.1-3.3 Vorlesung mit Kurs oder Vorlesung mit Seminar (
6.0h VK/VS / 12.0 ECTS)
- 700.740 Vision Based State Estimation and Sensor Fusion (2.0h VC / 4.0 ECTS)
-
3.1-3.3 Vorlesung mit Kurs oder Vorlesung mit Seminar (
6.0h VK/VS / 12.0 ECTS)
-
Fach: Technische Ergänzung II
(Pflichtfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Wintersemester 2022/23
- 700.740 VC Vision Based State Estimation and Sensor Fusion (2.0h / 4.0ECTS)
-
Wintersemester 2021/22
- 700.740 VC Vision Based State Estimation and Sensor Fusion (2.0h / 4.0ECTS)
-
Wintersemester 2020/21
- 700.740 VC Vision Based State Estimation and Sensor Fusion (2.0h / 4.0ECTS)
-
Wintersemester 2019/20
- 700.740 VC Vision Based State Estimation and Sensor Fusion (2.0h / 4.0ECTS)
-
Wintersemester 2018/19
- 700.740 VC Vision Based State Estimation and Sensor Fusion (2.0h / 4.0ECTS)
-
Wintersemester 2017/18
- 700.740 VC Vision Based State Estimation and Sensor Fusion (2.0h / 4.0ECTS)