Dodo Alive! - Resurrecting the Dodo with Robotics and AI: Hardware & Design

Lecturer (assistant)
  • Sami Haddadin [L]
  • Fajar Budiman
  • Quang Hoan Le
  • Dennis Ossadnik
  • Abdalla Swikir
Duration1 SWS
TermSommersemester 2023
Language of instructionEnglish
Position within curriculaSee TUMonline

Admission information


After completing this module, students should have gained broad knowledge in developing legged robots. They should also have acquired problem-solving and team-working skills. The students will have obtained practical and methodological skills to gain diverse competencies far beyond basic theory.


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 “Robo-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 three groups: 1. modeling and control in Matlab/Simulink; 2. hardware/software development, including design of the mechanical and electrical components, microcontroller programming and low-level motor control; and 3. CAD design, which encompasses the mechanical design of links and frames as well as 3D printing of the respective parts. 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.


We expect that the student is familiar with basic electronics and µC programming or some basic CAD.

Teaching and learning methods

- Introductory classes - Independent student work - Team work (including supervised and unsupervised work in the laboratory)


The module mark is determined by a final project work, in which the students demonstrate their ability to work in a team and to put theory into practice. This includes a 10 minute presentation and a written report (10-15 pages) in which the students present their results. Here the functionality of the final application is evaluated, as well as its development and testing process and the theoretical principles used for it.

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. - Cotton, Sebastien, et al. "Fastrunner: A fast, efficient and robust bipedal robot. concept and planar simulation." 2012 IEEE International Conference on Robotics and Automation. IEEE, 2012.