Dodo Alive! - Resurrecting the Dodo with Robotics and AI: Simulation & Control
Lecturer (assistant) | |
---|---|
Number | 0000002659 |
Type | lecture |
Duration | 1 SWS |
Term | Wintersemester 2025/26 |
Language of instruction | English |
Position within curricula | See TUMonline |
- 17.07.2025 17:00-17:15 L022, Campus D, Seminarraum , It will be held online, please use the following Zoom link: https://tum-conf.zoom-x.de/j/7145507579
- 16.10.2025 13:30-17:00 L022, Campus D, Seminarraum
- 23.10.2025 13:30-17:00 L022, Campus D, Seminarraum
- 30.10.2025 13:30-17:00 L022, Campus D, Seminarraum
- 06.11.2025 13:30-17:00 L022, Campus D, Seminarraum
- 13.11.2025 13:30-17:00 L022, Campus D, Seminarraum
- 20.11.2025 13:30-17:00 L022, Campus D, Seminarraum
- 27.11.2025 13:30-17:00 L022, Campus D, Seminarraum
- 11.12.2025 13:30-17:00 L022, Campus D, Seminarraum
- 18.12.2025 13:30-17:00 L022, Campus D, Seminarraum
- 08.01.2026 13:30-17:00 L022, Campus D, Seminarraum
- 15.01.2026 13:30-17:00 L022, Campus D, Seminarraum
- 22.01.2026 13:30-17:00 L022, Campus D, Seminarraum
- 29.01.2026 13:30-17:00 L022, Campus D, Seminarraum
- 05.02.2026 13:30-17:00 L022, Campus D, Seminarraum
Admission information
See TUMonline
Note: To access your skill level, consider doing a self-evaluation! : Within the first week, everyone individually needs to complete the derivation of the double-pendulum kinematic properties. For that you will need to properly assign the mDH parameters to 2DoF and derive double pendulum kinematics. Additional individual tasks will follow, like deriving dynamics, lagrange formulation, etc. The first task is a good indicator of your skillset. If you consider it too difficult, you might need to invest a lot of time in the beginning.
Note: To access your skill level, consider doing a self-evaluation! : Within the first week, everyone individually needs to complete the derivation of the double-pendulum kinematic properties. For that you will need to properly assign the mDH parameters to 2DoF and derive double pendulum kinematics. Additional individual tasks will follow, like deriving dynamics, lagrange formulation, etc. The first task is a good indicator of your skillset. If you consider it too difficult, you might need to invest a lot of time in the beginning.
Objectives
Upon completion of this laboratory, the students have acquired profound knowledge in planning, design and control of dynamically walking bipedal robots both methodologically and practically. In addition to their problem-solving and teamworking capabilities, the students expand their management and organization skills
Description
Imagine that you are at the natural history museum. You wander around and take a look at different parts of the museum. Suddenly, a robot in the form of a long extinct species – the Dodo – moves towards you, starts talking to you and tells you about itself. This course covers constructing an autonomous, intelligent walking Dodo-like robot, which requires a combination of a wide spectrum of fields, including design, control, navigation, locomotion, perception and AI. During this laboratory course, the students will develop the necessary skills to design and construct various components of “Mecha-Dodo”, as part of a long-term, iterative project.
After some introductory classes, a practical phase will follow in which the students work closely together in interdisciplinary groups. The students will be divided into groups:
1. Modelling and Control in Matlab/Simulink;
2. BLDC motor control & electronics
3. Mechanical CAD design, which encompasses the mechanical design of links and frames as well as 3D printing of the respective parts.
4. Learning based locomotion
All components will be integrated in a unified prototype. The long-term goal is to bring the famous Dodo back to life within a collective effort.
After some introductory classes, a practical phase will follow in which the students work closely together in interdisciplinary groups. The students will be divided into groups:
1. Modelling and Control in Matlab/Simulink;
2. BLDC motor control & electronics
3. Mechanical CAD design, which encompasses the mechanical design of links and frames as well as 3D printing of the respective parts.
4. Learning based locomotion
All components will be integrated in a unified prototype. The long-term goal is to bring the famous Dodo back to life within a collective effort.
Prerequisites
For the realization of this project, proficiency in one or more of the following areas is required:
- Modeling and Control (Matlab/Simulink)
- Mechanics, Mechanism Design (CAD)
- Electronics
- Programming Languages
- Modeling and Control (Matlab/Simulink)
- Mechanics, Mechanism Design (CAD)
- Electronics
- Programming Languages
Teaching and learning methods
- Introductory classes
- Tutorials
- Independent student work
- Team work (including supervised and unsupervised work in the laboratory)
- Tutorials
- Independent student work
- Team work (including supervised and unsupervised work in the laboratory)
Examination
The examination consists of a practical group project, a ten-minute presentation and a written report. Within the final project, the students show that they are able to conceptualize, plan and realize the integration of complex mechatronic systems and to develop and implement the required control methods. The work is evaluated by the functionality of the students’ approach, the development and testing process and the understanding of the underlying theoretic concepts.
Recommended literature
- M. W. Spong, S. Hutchinson, M. Vidyasagar, ‘Robot Modeling and Control’, vol. 3, New York: Wiley, 2006.
- R. Alexander, ‘Locomotion of Animals’, Springer, 1982.
- R. M. N. Alexander, R. McNeill, G. Goldspink, ‘Mechanics and energetics of animal locomotion’, Chapman and Hall, 1977.
- 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.
- B. 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.
- C. M. Bishop, ‘Neural networks for pattern recognition’, Oxford university press, 1995.
- R. Alexander, ‘Locomotion of Animals’, Springer, 1982.
- R. M. N. Alexander, R. McNeill, G. Goldspink, ‘Mechanics and energetics of animal locomotion’, Chapman and Hall, 1977.
- 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.
- B. 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.
- C. M. Bishop, ‘Neural networks for pattern recognition’, Oxford university press, 1995.