E-learning course overview

The practical course gives an introduction to mobile robotics with a focus on dynamical systems approaches. The open-source simulation environment Webots 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.

Enrollment:

From the 1st of February 2025 to the 1st of March 2025 interested students can apply for a place in the seminar. The allocation of places will take place via the following central Moodle course of the faculty: https://moodle.ruhr-uni-bochum.de/course/view.php?id=62179.
The places will be allocated by the 15th of March 2025 at the latest. Please complete your binding enrollment by registering for the seminar via FlexNow. Please note that it is mandatory to follow the above steps. Enrollment via FlexNow without prior registration via the central Moodle course is not permitted.

Non-informatics students: Please enroll through our e-learning system on www.ini.rub.de from 31st of March to 16th of May 2025. A decision on participation will be published shortly afterwards.

Lecturers

Details

Course type
Lab courses
Credits
3 CP
Term
Summer Term 2025
E-Learning
e-learning course available

The practical part of the lab course consists of a week of full-time work in which students solve programming tasks with simulated mobile robots. In the two weeks following the practical part, the students then write reports in which they describe and analyze the work they have done. The grade for the lab course is based on both the practical work and the report. Students will get support during programming.

About the INI

The Institut für Neuroinformatik (INI) is a interdisciplinary research unit of the Ruhr-Universität Bochum. We aim to understand fundamental principles that characterize how organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by insights into 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, theoretical approaches from physics, mathematics, and computer science, including, in particular, machine learning, artificial intelligence, autonomous robotics, and computer vision.

Contact

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

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

sekretariat@ini.rub.de
www.ini.rub.de