This course aims to provide the fundamentals of athletic intelligence in robotics to enable robust sensorimotor control in robots. Students will learn to put this knowledge into practice during tutorials and in exercise sheets using Python implementation and robot simulations and/or hardware experiments.
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.
The course includes practical examples demonstrating how the theory applies to modern robotics. By the end of the course, students will gain valuable insights into behavior generation and control strategies used in contemporary athletic robots, such as Atlas (Boston Dynamics), Digit (Agility Robotics), and the Unitree Go2 quadruped.
Prerequisites
It is preferable, but not essential, to have a good understanding of mechanics, control theory, linear algebra, advanced calculus, numerical methods, mechatronics, programming etc.
How to apply:
Application is open from Feb 4 – Feb 18 at universityadmissions.se/antagning.se.Search for TRA455.
Alumni, PhD students and professionals apply by email to shivesh.kumar@chalmers.se
Details
Teacher: Shivesh Kumar
Course dates: Study period 4
Credits: 7.5
Level: A
Course code: TRA455
Application deadline: Open for applications Feb 4-18