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151-0634-00L 4 Credits MSC D-ITET , D-MAVT , D-INFK
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Perception and Learning for Robotics

Lecturers & Examiners: Dr. Cesar Dario Cadena Lerma, Dr. Jen Jen Chung
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: 2026-02-05 15:41:34

Abstract

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. The main focus of this course are student projects on 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

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 during the lecture block (10%).

Registration & Places

Limited places (Special selection)
Signup End
09.02.2020

Course Components

Type Title Time & Place Hours
independent project Perception and Learning for Robotics
The lectures take place on the following days in the 2nd week of the Semester: - Monday 24.02.2020 at 14-18 - Wednesday 26.02.2020 at 14-18 - Friday 28.02.2020 at 14-18 The venue will be announced later.
  • 24.02 Date 14:15-18:00 (LEE C 114)
  • 26.02 Date 14:15-18:00 (HG F 26.3)
  • 28.02 Date 14:15-18:00 (LEE C 114)
120 h semesterly

Offered In