Course syllabus

Course-PM

TRA455 Artistic Intelligence in Robotics, LP4, Spring 2026 (7.5 hp)

The course is offered by the Division of Dynamics, Department of Mechanics and Maritime Sciences.

Contact details

Teaching Staff

Shivesh Kumar, e-mail: shivesh.kumar@chalmers.se (examiner, lectures, consultation)

Petri Piiroinen, e-mail: petri.piiroinen@chalmers.se (lectures, consultation)

Joan Badia i Torres, e-mail: joan.badia@chalmers.se (tutorials, consultation)

Sahánd Wagemakers, e-mail: sahand.wagemakers@chalmers.se (tutorials, consultation)

Raphael Stöckner, e-mail: stockner@chalmers.se (tutorials, consultation)

Division and Department

Division of Dynamics, Department of Mechanics and Maritime Sciences.
Visit: Hörsalsvägen 7A, Floor 3
Contact: Use email or visit us (We all have our offices on the same floor). Do not use chat or inside-canvas messaging as it is not as frequently read.

Course purpose:

Traditional robots today (such as the ones used in factories) have a fixed base and are fully actuated under their operating conditions. However, modern robots inspired by animals (such as hoppers, quadruped, humanoids) are not bound to one place and are always under-actuated. Like animals, these robots can perform dynamic movements, demonstrate compliance, and are robust to contact during their movements. Robots of the future will be able to move more dynamically and safely in a rugged environment shared with humans. To develop such robots, it is crucial to focus on the athletic intelligence in robots. This course aims to provide the fundamentals of athletic intelligence in robotics to enable robust sensorimotor control in underactuated mechanical systems. Students will put this knowledge into practice during tutorials and exercise sheets using Python implementation and robot simulations. The course is enriched with practical examples of the use of the theory in modern day robots. With the conclusion of this course, the students will be able to get some insights into the behaviour generation and control of various modern athletic robots like Atlas (Boston Dynamics), Digit (Agility Robotics), Unitree Go2 quadruped etc.

Schedule: TimEdit (Link to an external site.) 

Course literature

[1] Underactuated Robotics: Algorithms for Walking, Running, Swimming, Flying, and Manipulation, Russ Tedrake, MIT 2023. (https://underactuated.csail.mit.edu/index.html)
[2] Modern Robotics: Mechanics, Planning, and Control, Kevin M. Lynch and Frank C. Park, Cambridge University Press, 2017. (https://hades.mech.northwestern.edu/index.php/Modern_Robotics)
[3] Practical Methods for Optimal Control and Estimation Using Nonlinear Programming, Second Edition, John Betts, SIAM. (https://doi.org/10.1137/1.9780898718577)
[4] A Course in Reinforcement Learning, Dimitri P. Bertsekas, Athena Scientific, 2025 (https://www.mit.edu/~dimitrib/RLbook.html)

Course design

The course is run by a teaching team responsible for 17x lectures (L), 16x tutorials (T) and 9x consultancy sessions (C). The course is organized into six lecture blocks. At the end of first five blocks, the students will be asked to submit a group assignment that tests their knowledge and skills gained from the lecture block. At the end of the course, individual assessment of students will be made by oral examination. See the explanation of the grading below.

Lectures: Lectures are meant for delivery of the theoretical content of the course by the teacher. It is highly recommended that students attend these sessions.

Lecture	Teacher	Topic (chapter in [1])	Date and time
B1		Introduction
L1	Shivesh	Introduction to Athletic Intelligence in Robots (Ch. 1)	Mon 23 March, 08:00-09:45
L2	Shubham (Guest)	Building Blocks of Athletic Robots (Ch. 1)	Wed 25 March, 08:00-09:45
L3	Shivesh	Getting the Right Model of the Robot (App. B)	Wed 25 March, 13:15-15:00
B2		Robots as Dynamical Systems
L4	Petri	Continuous Dynamical Systems (Ch. 1, 2, 3)	Mon 30 March, 08:00-09:45
L5	Petri	Hybrid Dynamical Systems (Ch. 4)	Wed 1 April, 10:00-11:45
L6	Petri	Template Motion Models (Ch. 4, 5)	Mon 13 April, 08:00-09:45
B3		Behavior Generation
L7	Shivesh	Dynamic Programming (Ch. 7)	Wed 15 April, 10:00-11:45
L8	Shivesh	Trajectory Optimization (Ch. 10)	Mon 20 April, 08:00-09:45
L9	Petri	Planning through contacts (Ch. 17)	Wed 22 April, 10:00-11:45
B4		Reactive Control
L10	Shivesh	Instantaneous Stabilization	Mon 27 April, 08:00-09:45
L11	Shivesh	Stabilization over Horizon (Ch. 8)	Wed 29 April, 10:00-11:45
L12	Petri	Stability Analysis (Ch. 9)	Mon 4 May, 08:00-09:45
B5		Identification, Estimation & Learning
L13	Mihaela (Guest)	State Estimation (Ch. 19)	Wed 6 May, 10:00-11:45
L14	Konstantinos (Guest)	Reinforcement Learning	Mon 11 May, 08:00-09:45
L15	Shivesh	Sim2Real Gap (Ch. 18)	Wed 13 May, 10:00-11:45
B6		Advanced Topics
L16	Shivesh	Co-Design in Robotics	Mon 18 May, 08:00-09:45
L17	Shivesh	Links to Cognitive Intelligence	Wed 20 May, 10:00-11:45

Tutorial sessions: In tutorials, students typically work on a hands-on task where they apply the methods they learnt in the lecture with the help of the teaching assistant. It is highly recommended that students attend these sessions as a lot of actual learning happens here.

Session	Topics (tentative)	Date and Time
B1	Introduction
T1	Introduction to CloudPendulum & Robots at RAIL	Mon 23 March, 10:00-11:45
T2	Surgery of Unitree Go2 Quadruped	Wed 25 March, 10:00-11:45
T3	Getting the Right Model of the Robot	Wed 25 March, 15:15-17:00
B2	Robots as Dynamical Systems
T4	Simple Pendulum: Energy Shaping	Mon 30 March, 10:00-11:45
T5	Compass walker, rimless wheels	Wed 1 April, 13:15-15:00
T6	SLIP model, Hopper	Mon 13 April, 10:00-11:45
B3	Behaviour Generation
T7	Grid problem, car breaking, SpaceX	Wed 15 April, 13:15-15:00
T8	Brachiation with AcroMonk	Mon 20 April, 10:00-11:45
T9	Littledog, Atlas in a Japanese garden	Wed 22 April, 13:15-15:00
B4	Behaviour Stabilization
T10	Instantaneous Stabilization	Mon 27 April, 10:00-11:45
T11	Double Pendulum	Wed 29 April, 13:15-15:00
T12	Region of attraction analysis for pendulum	Mon 4 May, 10:00-11:45
B5	Identification, Estimation & Learning
T13	State Estimation for Quadruped	Wed 6 May, 15:45-17:00
T14	RL policy for Unitree Go2	Mon 11 May, 10:00-11:45
T15	System Identification of Double Pendulum	Wed 13 May, 13:15-15:00
B6	Advanced Topics
T16	Basketball and Ball Throwing Arm Codesign	Mon 18 May, 10:00-11:45

Consultancy sessions: The consultancy sessions provide a space for discussing any questions about the content of the lecture, tutorial or assignments. The teaching assistants are available to help you. The presence in these sessions is optional.

Session	Date and Time
C1	Wed 1 April, 15:15-17:00
C2	Wed 15 April, 15:15-17:00
C3	Wed 22 April, 15:15-17:00
C4	Wed 29 April, 15:15-17:00
C5	Wed 06 May, 15:15-17:00
C6	Wed 13 May, 15:15-17:00
C7	Wed 20 May, 13:15-17:00
C8	Mon 25 May, 08:00-11:45
C9	Wed 27 May, 10:00-17:00

Changes made since the last year

The course now has a 5^th lecture block on Estimation, Identification and Learning consisting of 3 lectures. The assignment in the 5^th lecture block has been mandatory and an optional mini project in the course has been introduced.

Learning objectives and Syllabus

General learning outcomes for Tracks courses:

• Critically and creatively identify and/or formulate advanced architectural or engineering problems.
• Master problems with open solutions spaces which includes to be able to handle uncertainties and limited information.
• Lead and participate in the development of new products, processes and systems using a holistic approach by following a design process and/or a systematic development process.
• Orally and in writing explain and discuss information, problems, methods, design/development processes and solutions.

Course specific learning:

At the end of the course, the student is expected to be able to: 

• Understand athletic intelligence and list its key aspects.
• Model a robot as a dynamical system and apply optimization and/or learning-based tools to generate complex behavior.
• Develop model-based controllers that can stabilize behavior in the presence of disturbances.
• Perform stability analysis of controllers.
• Familiarity with methods used for system identification and state estimation.
• Identify open challenges in robotics research and current trends in state-of-the-art.
• Communicate confidently using the terminology in the field of robotics.
• Cooperate and work in interdisciplinary teams to solve tasks.

Link to the syllabus on Studieportalen.

Examination form

The course is organized into six lecture blocks. At the end of first five blocks, the students will be asked to submit a mandatory group assignment which tests their knowledge and skills gained from the lecture block. At the end of the course, individual assessment of students will be made by oral examination. Completion of the first five mandatory group assignments (A1-A5) is required to pass the course with a grade of 3. Grade of 4 is given by additionally passing the optional mini-project or a successful oral exam. Grade 5 will be awarded by successful competition of all assignments (A1-A5), mini-project and a successful oral examination. See the grading matrix below.

Assignment	Release day	Submission day	Feedback by	Resubmission by
A1 (Mandatory)	Mon 23 March	Thu 2 April	16 April	29 May
A2 (Mandatory)	Mon 30 March	Mon 20 April	04 May	29 May
A3 (Mandatory)	Wed 15 April	Mon 27 April	11 May	29 May
A4 (Mandatory)	Wed 27 April	Fri 08 May	22 May	29 May
A5 (Mandatory)	Wed 6 May	Wed 27 May	02 June	29 May
Mini Project (optional)	Mon 27 April	Mon 04 May (Selection only) Thu 28 May (Submission)	Thu 28 May (Presentations)	Not Possible

 

Deadlines for mandatory assignments are to be respected strictly. Delayed submissions are only accepted in proven exceptional circumstances provided the teaching staff is informed well in advance. Groups should include a contribution statement at the end of their reports.

Grading

The course grade is determined as follows:

Requirements	Pass all mandatory group assignments (A1-A5).	Pass all mandatory group assignments (A1-A5) and a successful oral exam.  OR Pass all assignments (A1-A5) and mini project.	Pass all assignments (A1-A5), mini project and successful oral exam.
Grade	3	4	5

Oral examination will take place during the exam week (02.06.2026 to 05.06.26).