Computer Science Science
Basic concepts and algorithms for locomotion, perception, and intelligent navigation. This self-study course is not actively moderated. You can view the course for free, but questions will not be answered and there is no guarantee that the content will be available or updated.

Course Details

Language English
Duration 10 weeks
Effort 2 hrs/week

Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is put on mobile robot locomotion and kinematics, environment perception, probabilistic map based localization and mapping, and motion planning. The lectures and exercises of this course introduce several types of robots such as wheeled robots, legged robots and drones.

This lecture closely follows the textbook Introduction to Autonomous Mobile Robots by Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, second edition 2011.

What you will learn

In the course you wil learn:

  • Be able to describe the basic concepts and algorithms required for mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning

  • Be able to apply these concepts for the design and implementation of autonomous mobile robots acting in complex environment

Course instructors

Davide Scaramuzza

Davide Scaramuzza (born in 1980, Italian) is Professor of Robotics and Perception at both departments of Informatics (University of Zurich) and Neuroinformatics (University of Zurich and ETH Zurich), where he does research at the intersection of robotics,…

Marco Hutter

Marco Hutter is a professor in robotics and intelligent systems at the mechanical engineering department of ETH Zurich.

Margarita Chli

Margarita Chli is an Assistant Professor at ETH Zurich, Switzerland, and head of the Vision for Robotics Lab ( Originally coming from Greece and Cyprus, she received both her Bachelor and Master degrees in Information and Computing Engin…

Martin Rufli

Martin Rufli is a Research Scientist at IBM Research Zurich. He received his B.Sc. and M.Sc. degrees in mechanical engineering and the Ph.D. degree in robotics, all from ETH Zurich, Switzerland, in 2006, 2008, and 2012, respectively. From September 2012 t…

Nicholas Lawrance

Nicholas Lawrance is a senior researcher in robotics at the Autonomous Systems Lab with Professor Roland Siegwart. He is interested in planning and modelling with uncertainty, with a particular interest in fixed-wing aerial vehicles (especially soaring fl…

Roland Siegwart

Roland Siegwart is a Professor of Autonomous Systems at ETH Zurich. After studying mechanics and mechatronics he was engaged in starting up a spin-off company, spent ten years as professor for autonomous microsystems at EPFL Lausanne and he held visiting …

ETH Zurich

Freedom and individual responsibility, entrepreneurial spirit and open-mindedness: ETH Zurich stands on a bedrock of true Swiss values. Our university for science and technology dates back to the year 1855, when the founders of modern-day Switzerland crea…

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