Autonomous Robotics

This course takes place in presence, at the Ruhr-University Bochum.

The number of participants is limited!

Please enroll through our e-learning system between October 2 and December 31, 2023. 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
Winter Term 2023/2024
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 26.02.2024
Last appointment is on 01.03.2024
Preliminary meeting
Takes place on 22.02.2024 from 10:00 to 11:00 in room NB 02/77.

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.

Documents

Exercises Report Template

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