The following courses are taught by members of the Intelligent Robotics group.

ELEC-E8126 – Robotic manipulation

The course provides an overview of mathematical models and algorithms behind state-of-the-art robotic manipulation. The covered viewpoints include grasping. motion planning, motion control, control in contact and redundancy, and learning manipulation skills. 
After completing the course, a student can: (i) explain main concepts related to robotic manipulation; (ii) read scientific literature in robotics to choose approaches for a particular problem; (iii) implement state-of-the-art algorithms.

ELEC-C1240 – State-space models and discrete-time control

The course provides a modern introduction to digital control theory, where students get familiar with concepts such as discretizing linear and nonlinear systems, analysing global stability of nonlinear systems with Lyapunov analysis, accounting for different types of noise sources in the design of control systems, and performing system identification using neural networks.

The course also teaches how to utilize modern software tools in the implementation of digital control systems, such as Python, NumPy, SymPy, SciPy and PyTorch.

The course is a third-year bachelor’s course taught in Finnish.

Past courses

ELEC-E8125 – Reinforcement learning D

The course provides an overview of mathematical models and algorithms behind optimal decision making in time-series systems. The course focus is in optimal decision making and control, reinforcement learning, and decision making under uncertainty.

Have a look at some of the agents that went through our final competitive phase of our course Wimblepong tournament!

The course is current taught by Joni Pajarinen. More information is available here.