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151-0634-00L 4 Credits MSC D-ITET , D-MAVT , D-ERDW , D-INFK , D-PHYS

Perception and Learning for Robotics

Lecturers & Examiners: Dr. Cesar Dario Cadena Lerma, Dr. Andrei Cramariuc

Number of participants limited to 30 To apply for the course please create a CV in pdf of max. 2 pages, including your machine learning and/or robotics experience. Please send the pdf to for approval.

VVZ CR n/a

Last Updated: 2026-06-03 00:14:36

Abstract

"Project-based Education (PBE)", This course covers tools from statistics and machine learning enabling the participants to deploy these algorithms as building blocks for perception pipelines on robotic tasks. All mathematical methods provided within the course will be discussed in context of and motivated by example applications mostly from robotics.

Objective

Applying Machine Learning methods for solving real-world robotics problems.

Content

Deep Learning for Perception; (Deep) Reinforcement Learning; Graph-Based Simultaneous Localization and Mapping

Resources

Lecture Notes

Slides will be made available to the students.

Literature

Will be announced in the first lecture.

General Information

Language: English
Levels: MSC
Frequency: Yearly recurring

Examination

Type: graded semester performance

The grade is based on the realization of a project, presentation and demo (50%), the project report (40%) and quizzes/exercises during the lecture block (10%).

Registration & Places

Signup End: 08.02.2026

Course Components

Type	Title	Time & Place	Hours
lecture	Perception and Learning for Robotics • Monday 23.02.2026 from 14:15 to 18:00 • Wednesday 25.02.2026 from 14:15 to 18:00 • Friday 27.02.2026 from 14:15 to 18:00	23.02 Date 14:15-18:00 (HG E 23) 25.02 Date 14:15-18:00 (HG E 23) 27.02 Date 14:15-18:00 (HG F 26.1)	12 h semesterly
independent project	Perception and Learning for Robotics	No time listed	90 h semesterly
lecture with exercise	Perception and Learning for Robotics	No time listed	90 h semesterly

Offered In

Mechanical Engineering Master
- 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.)
Robotics, Systems and Control Master
- Core Courses
Space Systems Master
- Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
  - Robotics
    - Deep Track Robotics (These courses can be credited either as a specialization subject or as an elective subject.)