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Technical University of Munich

IN2106 Dodo Alive! - Resurrecting the Dodo with Robotics and AI: Mechanism Design & Control

Lecturer (assistant)
Alexander König [L]
Fajar Budiman
Fernando Diaz Ledezma
Furkan Erdem
Quang Hoan Le
Dennis Ossadnik
Vasilije Rakcevic
Number 0000001898
Type practical training
Duration 6 SWS
Term Wintersemester 2025/26
Language of instruction English
Position within curricula See TUMonline

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. For the course registration, priorities will be given to students who provide their CV and several sentences on Motivation (not more than half of the A4 page) via the email: vasilije.rakcevic@tum.de. Use [Dodo Application Supporting Documents] in subject line.

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.

Prerequisites

Participation in the laboratory “Dodo Alive! HW/SW Components Development” is recommended but not necessary. We expect sound knowledge in one or more of the following fields:

- Modeling and Control (Matlab/Simulink)
- Mechanics, robotics and multi body systems
- Mechanism design (CAD)
- Electronics (PCB layout design, bus systems, microcontroller programming)
- Programming (C, C++)
- Perception

Teaching and learning methods

- Introductory classes
- 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.

In addition to the tasks mentioned above, the students of the Faculty of Informatics work on a chosen publication in the field of legged robots. The students summarize the content via a 10-minute presentation.

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.

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