Machine Learning and Robotics Seminar Course

Wissenschaftliches Seminar

In this course, teams of up to 2 students will jointly perform a literature review on a topic in the field of Machine Learning and Robotics. This includes discussing the fundamental ideas and concepts of state-of-the-art methods as well as their current impact and limitations. Topics will vary each term.

Learning Objectives

Students will learn to conduct a thorough literature review, contrast different ideas and concepts, identify their impact and limitations, and communicate their findings in written and oral form. Furthermore, students will learn to structure their findings by identifying the main research threads in a particular field and engaging in group discussions and collaborative writing. 

Prerequisites

The prerequisites for this course are fundamental knowledge of robotics, machine learning, control theory, and computer vision. We also expect project teams to have a strong mathematics background.

Teaching and Learning Approach

Students will be given introductory lectures and guided through the process of finding relevant literature and discussing it. Regular meetings with a scientific advisor will support this process. In particular, the advisor will provide an introduction to the topic, an initial set of relevant literature, and early feedback on the report and presentation.

Evaluation

The evaluation for this course is composed of a written report (50%, length of the report: up to 3 double-column pages per team member) and a presentation followed by questions and a discussion (50%, length of presentation: 5 minutes per team member).