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Vision Algorithms for Mobile Robotics (University of Zurich)
Last Updated: 2026-06-03 00:07:37
Abstract
For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the key computer vision algorithms used in mobile robotics, such as feature extraction, structure from motion, dense reconstruction, tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithms behind Hololens, Oculus Quest, and the NASA Mars rovers).
Objective
Learn the fundamental computer vision algorithms used in mobile robotics, in particular: filtering, feature extraction, structure from motion, multiple view geometry, dense reconstruction, tracking, image retrieval, event-based vision, and visual-inertial odometry and Simultaneous Localization And Mapping (SLAM) (the algorithms behind Hololens, Facebook-Oculus Quest, and the NASA Mars rovers).
Content
Each lecture will be followed by a lab session where you will learn to implement a building block of a visual odometry algorithm in Matlab. By the end of the course, you will integrate all these building blocks into a working visual odometry algorithm.
Resources
Lecture Notes
Lecture slides will be made available on the course official website:http://rpg.ifi.uzh.ch/teaching.html
Literature
[1] Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010. [2] Robotics Vision and Control: Fundamental Algorithms, by Peter Corke 2011. [3] An Invitation to 3D Vision, by Y. Ma, S. Soatto, J. Kosecka, S.S. Sastry. [4] Multiple view Geometry, by R. Hartley and A. Zisserman. [5] Introduction to autonomous mobile robots 2nd Edition, by R. Siegwart, I.R. Nourbakhsh, and D. Scaramuzza, February, 2011
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Vision Algorithms for Mobile Robotics (University of Zurich)
**Course at University of Zurich**
Follow the instructions on how to apply on the official course website:
|
No time listed | 2 h weekly |
| exercise |
Vision Algorithms for Mobile Robotics (University of Zurich)
**Course at University of Zurich**
Follow the instructions on how to apply on the official course website:
|
No time listed | 2 h weekly |
Offered In
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Core Courses (The Core Courses in the Master’s program Mechanical Engineering listed below are indicative and include courses designed by the Department at the Master's level. With the approval of the tutor, students may also select Master's-level courses offered by other departments at ETH. These courses will be marked as non-regular in the LAG, but their categorization as Core Courses is possible if included in the approved LAG.)
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed. All courses listed as core courses (not electives) for one of the following ETH MSc programmes, MSc Statistics, MSc Physics, MSc Computer Science, MSc (Applied) Mathematics, MSc Neural Systems and Computation, MSc Robotics, Systems, and Control, MSc Data Science, MSc Electrical Engineering and Information Technology, can be taken as an elective course in the MSc CSE without prior permission.)
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Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
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Deep Track Earth Observation (These courses can be credited either as a specialization subject or as an elective subject.)
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Deep Track Robotics (These courses can be credited either as a specialization subject or as an elective subject.)
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