Autonomous Robotics

Limited number of participants! Please enroll through our e-learning system on www.ini.rub.de from 1st of April to 17th of May 2024. A decision on participation will be published shortly afterwards. Please also register with your examination office or via FlexNow. Enrollment periods: 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
Summer Term 2024
E-Learning
e-learning course available

Dates

Lab course
Takes place every day from 10:00 to 18:00 in room NB 02/77.
First appointment is on 02.09.2024
Last appointment is on 06.09.2024
Preliminary meeting
Takes place from 10:00 to 11:00 in room NB 02/77.
First appointment is on 29.08.2024
Last appointment is on 29.08.2024

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 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