E-learning course overview

Max. number of participants: 20

Please enroll through our e-learning system until November 15 2024. We moved this ahead to make a more timely decision about  participation as we have more requests than we can serve. So we wanted to make sure that you find an alternative if you are not accepted. 

Please also register with your examination office or via FlexNow in time. For enrolment periods in Computer Science see: https://informatik.rub.de/studium/pruefungsamt/pruefungstermine/

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. 

Lecturers

Details

Course type
Lab courses
Credits
3 CP
Term
Winter Term 2024/2025
E-Learning
e-learning course available

Dates

Preliminary meeting
Takes place on 06.02.2025 from 10:00 to 11:00 in room NB 02/77.
Lab course
Takes place every day from 10:00 to 18:00 in room NB 02/77.
First appointment is on 10.02.2025
Last appointment is on 14.02.2025

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. 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 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.

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