Introduction to Computer Vision & Robotics

Details

In this course, concepts important for robotic applications will be taught as e.g.:

• Sensors and actuators
• Robot control
• Movement generation methods
• Path planning
• Learning algorithms in robotics
• Image filtering
• Line, Circle & Feature Detection
• Image segmentation techniques

Module: B.Phy.5668 Credits: 3 CP

Link to StudIP

Organizers:

Tomas Kulvicius, tkulvic@gwdg.de, E.01.104

Schedule

The lecture will be held via BBB weekly on wednesdays 10:15 - 11:45. Link to the BBB event: see StudIP link above.

The 1st exam (written, in person) will take place on 16.02.2022 at 15:00 in HS1 and HS2.

The 2nd exam (written, in person) will take place on 06.04.2022 at 15:00 in HS5.

Lecture 1 27.10.2021 Introduction of course and tutors
Lecture 2 03.11.2021 R1. Introduction to Robotics. Sensors and actuators	Presentation Video Kalman Filter Demo
Lecture 3 10.11.2021 R2. Robot kinematics and control	Presentation Video Denavit-Hartenberg Convention Control Demo Kinematics Demo
Lecture 4 17.11.2021 CV1. Thresholding, Filtering & Connected Components	Presentation Video Jupyter Notebook
Lecture 5 24.11.2021 CV2. Bilateral Filtering, Morphological Operators & Edge Detection	Presentation Video Jupyter Notebook
Lecture 6 01.12.2021 CV3. Corner Detection & Non-Local Filtering	Presentation Video Jupyter Notebook Corner Detection Non local Means
Lecture 7 08.12.2021 R3. Path planning algorithms	Video Part 1 Video Part 2 Presentation Papers Dijkstra Demo
Lecture 8 15.12.2021 R4. Movement generation methods	Presentation Video DMP Demo
Lecture 9 22.12.2021 CV4. Line/Circle Detection, Template Matching & Feature Detection	Presentation Video Jupyter Notebook
Lecture 10 12.01.2022 CV5. Face Detection, Pedestrian Tracking	Presentation Video Jupyter Notebook
Lecture 11 19.01.2022 CV6. Segmentation & Computer Vision in 3D	Presentation Video Jupyter Notebook
Lecture 12 26.01.2022 R5. Learning algorithms in robotics I: Supervised and unsupervised learning	Presentation Video Correlation Learning Demo
Lecture 13 02.02.2022 R6. Learning algorithms in robotics II: Reinforcement learning	Presentation Video PI2 Demo Q-Learning Demo RL Tutorial
Lecture 14 09.02.2022 Q&A