Humanoid Robotics – RO5300

Lehrinhalte / TOC

During the summer semester Prof. Dr. Elmar Rueckert is teaching the course Humanoid Robotics (RO5300). In this course he will discuss the key components of one of the most complex autonomous systems.

These topics are





  1. Kinematics, Dynamics & Locomotion
  2. Representations of Skills & Imitation Learning
  3. Feedback Control, Priorities & Torque Control
  4. Reinforcement Learning & Policy Search
  5. Sensor Integration & Fusion
  6. Cognitive Reasoning & Planning

This course provides a unique overview over central topics in robotics. A particular focus is put in the dependencies and interaction among the components in the control loop. These interactions are discussed through in the context of state of the art methods including dynamical systems movement primitivesgradient based policy search methods or probabilisitic inference for planning algorithms

Qualifikationsziele / Objectives

The students will also experiment with state of the art machine learning methods and robotic simulation tools in accompanying exercises. Hands on tutorials on programming with Matlab, the robot middleware and interface ROS and the simulation tool V-Rep complement the course content.