IN2106 Praktikum Robot Modelling and Identification
|Language of instruction||German|
|Position within curricula||See TUMonline|
- 20.10.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 27.10.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 03.11.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 10.11.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 17.11.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 24.11.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 08.12.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 15.12.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 22.12.2022 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 12.01.2023 09:00-12:45 Online: Videokonferenz / Zoom etc.
- 19.01.2023 09:00-12:45 Online: Videokonferenz / Zoom etc.
After successfully completing this laboratory, students will be able to implement various actuator concepts, such as pneumatic actuators or DC motors, as well as common observation and control strategies, identification methods (linear + pseudoinverse and nonlinear + gradient based), a continuous and discrete PID controller, LQ controller, Luenberger observer and disturbance observer for collision detection, in Matlab/Simulink. They have theoretical-founded knowledge in cascaded control and impedance control and can apply it to a robot joint. They have the necessary knowledge to model serial kinematic robots in Maple and to control and identify them in Matlab/Simulink.
This laboratory deals with different mechatronic basic concepts of robotics with the focus on modelling, simulation and control using the numerical software Matlab/Simulink and the computer algebra system Maple. The laboratory comprises the modeling and control of a permanently excited DC motor and a pneumatic actuator, the time-discrete control of a DC motor, the controller design of an electric drive in the frequency domain, the identification of a robot joint, a controller and observer design for a robot joint, an impedance control for a robot joint, a force controller and collision observer, the dynamic/kinematic modeling of a serial robot kinematics as well as its identification and trajectory optimization.
Students should have sound knowledge in the following fields: - Automatic control - Mechanics and multi-body systems - Electrical drive technology - Robotics
Teaching and learning methods
- Preparation of theoretical basics Based on literature and scripts - Discussion of the theory in the oral exam interview - Practical realization and implementation of the exercises during the supervised laboratory times
The evaluation is based on the weekly laboratory performance. At the beginning of each practical, the theoretical understanding of the respective topic is tested in a 15-minute interview. The ability to implement or model the different concepts is measured by checking the source code developed during the practical at the end of the weekly practical. It will be checked for functionality and comprehensibility. This is created for the modeling of serial kinematic robots in Maple, for the other topics in Matlab/Simulink. Students from the Informatics department must carry out additional scientific and logistical investigation. The content and results of this work will be summarized in a 10-page report.
Introduction to Robotics: Mechanics and Control, 3rd Edition, John J. Craig, Pearson - H. Choset, K. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. Kavraki, S. Thrun, ‘Principles of Robot Motion: Theory, Algorithms, and Implementation’, MIT Press, 2005. - Siciliano, O. Khatib, ‘Springer Handbook of Robotics’, Springer, 2016. - M. W. Spong, S. Hutchinson, M. Vidyasagar, ‘Robot modeling and control’, vol. 3. New York: Wiley, 2006.