In accompanying exercises and hands on tutorials the students will experiment with state of the art machine learning methods and robotic simulation tools. In particular, Mathworks’ MATLAB, the robot middleware ROS and the simulation tool V-Rep will be used. The exercises and tutorials will also take place in the seminar room 2.132 on selected Fridays (see the course materials and dates below).
- Humanoid Robotics (RO5300)
- Robotics (CS2500)
Follow this link to register for the course: https://moodle.uni-luebeck.de/course/view.php?id=3793.
Location & Time: Room: Seminarraum Informatik 5 (Von Neumann) 2.132 12.15 – 14.00
Course materials and dates (tentative slides, last update Sep. 27, 2018)
- Probabilistic Learning for Robotics Intro (L1: October, 18th)
- Introductions to Topics I-III: Bayesian Inference, Gaussian Processes & Kalman/P. Filters (L2: October, 25th)
- Introductions to Topics IV-VI: Bayesian Optimization, Spiking Networks for Planning, Probabilistic Movement Primitives (L3: November, 1st)