700.205 (23S) Topics in Robotics: Visual Perception

Sommersemester 2023

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Erster Termin der LV
17.05.2023 08:45 - 17:00 Z.1.09 On Campus
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Überblick

Lehrende/r
LV-Titel englisch Topics in Robotics: Visual Perception
LV-Art Vorlesung
LV-Modell Präsenzlehrveranstaltung
Semesterstunde/n 2.0
ECTS-Anrechnungspunkte 3.0
Anmeldungen 14
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 17.05.2023
eLearning zum Moodle-Kurs

Zeit und Ort

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LV-Beschreibung

Intendierte Lernergebnisse

The focus of this lecture is to provide a detailed overview of how visual perception is used in robotics to derive information of the environment a robot is operating in.

The class dives into the full image processing pipeline - from image formation to advanced computer vision methods, such as i.e. 3D perception, motion estimation, and scene reconstruction, with examples from autonomous robotic systems on Earth and in Space. An additional aspect will be an introduction on how to simulate vision sensors to enable the evaluation of algorithms that include visual perception.

At the end of the lecture, students will have a deep understanding of how images from on-board cameras are used in robotic visual perception.

An opportunity to apply the acquired knowledge in selected research projects is provided by the accompanying practical class “Hands on Robotics: Visual Perception”.

Lehrmethodik

Additional to the material presented in the lecture, a literature collection including research papers and books will be provided for students who are interested in extended study.

It is suggested to take the accompanying practical course (Labor) to this lecture. Both are strongly linked such that the learned theory can immediately put into practice.

Inhalt/e

  • Image formation – biological vision and camera systems
  • Low-level image processing
  • Visual features, feature detection and feature matching
  • 2 view geometry and outlier rejection
  • Stereo and multi-view vision for 3D perception
  • Visual odometry and SLAM systems
  • Mapping
  • Object detection/recognition
  • Modelling vision sensors in simulation and computer graphics

Erwartete Vorkenntnisse

  • Good knowledge of Mathematics (linear algebra).
  • Basic knowledge in Robotics

Literatur

Books:

  • Richard Szeliski: Computer Vision: Algorithms and Applications, 2nd ed. Paper or online.
  • David A. Forsyth: Computer vision: A modern approach. Paper or online.

Link auf weitere Informationen

https://campus.aau.at/studium/course/113410

Prüfungsinformationen

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 22W.1)
    • Fach: Informationstechnische Vertiefung (Wahlfach)
      • 11a.4 Ausgewählte LVen der Informationstechnik: Chip Design, Einf.in die Multimedia-Technik, Fundamentals of Image Processing, Measurement Signal Processing, Mobile Robot Programming, Systemsicherheit ( 0.0h VO, VC, KS, UE / 6.0 ECTS)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 3.0 ECTS)
          Absolvierung im 3., 4., 5., 6. Semester empfohlen
  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Fach: Informationstechnische Vertiefung (Wahlfach)
      • 10a.3 Wahl von Lehrveranstaltungen ( 0.0h VO/VC/KS/UE / 6.0 ECTS)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 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)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 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)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 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)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 22W.1)
    • Fach: Information and Communicatons Enginnering: Supplements (Wahlfach)
      • 1.3b Ausgewählte Lehrveranstaltungen (siehe Curriculum Seite 16) ( 0.0h VC, KS / 14.0 ECTS)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 22W.1)
    • Fach: Autonomous Systems and Robotics: Advanced (Wahlfach)
      • 2.2 Further Lectures for ASR Advanced ( 2.0h VC / 4.0 ECTS)
        • 700.205 Topics in Robotics: Visual Perception (2.0h VO / 3.0 ECTS)

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