Autonomous Robotics

Important update: After careful evaluation of the conditions for performing such a lab class under the current "reduced operation" Corona rules, we have come to the conclusion that the paedagogical goals of the lab course cannot be reached. In particular, the cooperation in small groups is critical for the learning experience, but very difficult to arrange. 

So, to our regret, we announce that we will cancel this class for this summer. We aim to have the lab course again in its normal form for the Winter semester, so occuring in February/March 2021 after the semster has ended. By that time, conditions should be back to allow group work. 

Please interact with to any questions.

The practical course gives an introduction to mobile robotics with a focus on dynamical systems approaches. In the exercises, the computing environment Matlab is used to control e-puck miniature mobile robots, equipped with a differential drive, combined infrared/proximity sensors and a video camera. The course covers elementary problems in robot odometry, use of sensors and motor control. It then teaches basic dynamic methods for robot navigation, in which the robot's sensors are used for obstacle avoidance and approach to a target location.



Course type
Lab courses
3 CP
Summer Term 2020


Lab course
Takes place every day from 09:00 to 17:00 in room NB 02/77.
First appointment is on 21.09.2020
Last appointment is on 25.09.2020
Preliminary meeting
Takes place on 20.08.2020 from 10:15 in room NB 3/57.

The practical part of the lab course consists of a week of full-time work in which students solve programming tasks with mobile robots. The students then write reports in which they describe and analyze the work they have done. The grade for the lab course is based both on the programming and on the reports. Students will get support during programming and can receive feedback on their writing.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210