Practical Course RoboCup@Home
|Language of instruction||English|
|Position within curricula||See TUMonline|
- 11.04.2018 15:00-16:30 -1005, Hydrauliklabor, Kick-off Meeting
- 18.04.2018 15:00-16:30 -1005, Hydrauliklabor
- 20.04.2018 15:00-16:30 -1005, Hydrauliklabor
- 25.04.2018 15:00-16:30 -1005, Hydrauliklabor
- 27.04.2018 15:00-16:30 -1005, Hydrauliklabor
- 02.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 04.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 09.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 11.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 16.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 18.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 23.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 25.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 30.05.2018 15:00-16:30 -1005, Hydrauliklabor
- 01.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 06.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 08.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 13.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 15.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 20.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 22.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 27.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 29.06.2018 15:00-16:30 -1005, Hydrauliklabor
- 04.07.2018 15:00-16:30 -1005, Hydrauliklabor
- 06.07.2018 15:00-16:30 -1005, Hydrauliklabor
- 11.07.2018 15:00-16:30 -1005, Hydrauliklabor
- 13.07.2018 15:00-16:30 -1005, Hydrauliklabor
"Upon successful competition of this practical course, students are able to: • Implement algorithms from different areas including perception, learning, and control in the context of service robots. • Evaluate these algorithms in simulation and on a real mobile robot. • Analyze and apply techniques in challenging and real scenarios such as homes or supermarkets. Beside the technical skills learned in this practical course, the students are able to organize and manage a large engineering project. Furthermore, the students will learn communication skills to explain the results achieved per groups. "
"We aim to form a team of students for the RoboCup@Home competition, which is the largest competition for service robots. The focus of this competition is on challenging scientific problems such as human-robot interaction, mobile manipulation and cognition. Then, the student team needs to design, implement and test perception, learning, and robot control algorithms for these challenges. The overall goal is to provide students with enough practical background to participate in the international annual competition of the RoboCup@Home league. The service robot needs to demonstrate its abilities through the following functionalities: navigation, mapping of environments, person and object recognition, cognition to understand current situations, etc. Hence, this practical course is split as follows: - Kick-off meeting: The students meet with a supervisor to form groups according to the students' knowledge. The students designate a team leader (preferably a master student) who stays in touch with one of the supervisors of this course. - Hands-on tutorials: The students get introductory tutorials regarding methods, software and equipment used for this course. These tutorials will assure that all students have the same general knowledge of the used methods. - Development and test phase: The students design and implement algorithms to solve the above tests. This development goes hand in hand with the validation/test phase. - Final phase: Final test scenarios on a mobile robot are evaluated using one scenario from a previous competition to measure the performance of the robots abilities. This practical project aims to select those students who are motivated enough to continue working on developing algorithms to address the tests of the competition throughout the year. This practical course should contribute to the long-term goal of establishing a RoboCup@Home student team to participate in the official competition. "
"On the theoretical level, bachelor students must have passed their first two semesters. It is highly recommended to have basic knowledge in control, vision, or learning methods. On the practical level, students must have: - Strong C++ programming skills. - Background on ROS is highly advised. - Prior basic knowledge on AI (PROLOG) and Robotics is also highly recommended. "
Teaching and learning methods
"Following teaching methods are used: - Introductory tutorials (encompassing control, perception, and learning) - Independent student work (including work in the laboratory with simulations and real robots) - Teams integration and management with follow-up meetings. "
"This practical course is evaluated with laboratory assignments and a final group project. Each introductory tutorial session is composed of one or more exercises and students need to solve them individually. Then, students are split into groups and each group needs to implement algorithms to solve different problems according to the competition requirements in order to enable different fuctionalities to a mobile robot. The teams' final projects are evaluated with a presentation and live-demonstration of the implemented algorithms to summarize their accomplishments. In addition to the technical implementations, each team needs to deliver a written report which should reflect the ability to analyze and understand scientific and technical problems related to service robots. The final grade is composed as follows: A) final group project, including presentation and final report : 70% B) individual laboratory assignments : 30%"
"• RoboCup@Home: Analysis and results of evolving competitions for domestic and service robots, Iocchi L., Holz D., Ruiz-del-Solar J. , Sugiura K. and van der Zant T. Artificial Intelligence, Volume 229, December 2015, Pages 258–281, DOI: http://dx.doi.org/10.1016/j.artint.2015.08.002 • Artificial Intelligence: A modern approach. Stuart Russell and Peter Norvig. Pearson Ed. • Springer Handbook of Robotics. Bruno Siciliano and Oussama Khatib. 2007. Springer-Verlag New York, Inc., Secaucus, NJ, USA. • Machine Learning. Tom Mitchell. McGrawHill • Robot modeling and control. M.W. Spong, S. Hutchinson, and M. Vidyasagar. John Wiley & Sons, 2006. "