700.205 (24S) Topics in Robotics: Visual Perception

Sommersemester 2024

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Erster Termin der LV
22.05.2024 09:00 - 12:00 S.2.37 On Campus
Nächster Termin:
22.05.2024 13:30 - 16:30 S.0.05 On Campus

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 17
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 22.05.2024
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

Curriculare Anmeldevoraussetzungen

        

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

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.

Prüfungsmethode/n

There will be a final written exam at the end of the lecture.

Prüfungsinhalt/e

All contents taught during the lecture is part of the exam.

Beurteilungskriterien/-maßstäbe

The scored points in the exam reflect the grades from 1-5. With 50% or more of the achievable points, the exam is passed.

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
  • 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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