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Movement generation by Humans and Robots: a dynamical systems perspective

If you haven't contacted me about your individual oral exam, please do so now. gregor.schoener@rub.de

Humans are the dexterous species. We excel at movement generation, in particular, at handling objects and generating the complex sequences of actions that achieve goals. This course looks at the fundamental processes of movement generation in humans and other animals and characterizes the special properties of human movement that emerge from the neural foundation. Object-oriented movement generation entails not only the timing and control of movement, but also object perception, scene representation, and the organization and planning of sequences. Movement generation thus cuts across a wide range of neural processes.

We review experimental results in movement science, discuss mathematical models of movement generation, and use robotic instantiations of such models to illustrate their function. The mathematical language that pervades the theoretical work reviewed in the course comes from the theory of dynamical systems. The course includes tutorials on basic concepts in dynamical systems theory. The exercises provide opportunities to use those concepts in a variety of contexts.

Another goal of the course is to expose students to interdisciplinary science. The exercises include readings of review papers in different relevant fields. An essay exercise practices reading and writing at the level of academic research papers.



Course type
6 CP
Summer Term 2016


Takes place every week on Thursday from 14:15 to 16:00 in room NB 3/57.
First appointment is on 14.04.2016
Takes place every week on Thursday from 16:15 to 17:00 in room NB 3/57.
First appointment is on 21.04.2016


Usually, we upload an exercise sheet after each lecture. This sheet has to be handed in before the lecture of the following week (alternatively, you can hand it in via email to Oliver Lomp), which gives you a week to work on the solutions.

After collecting your solutions, we take a week to correct them and then discuss them in the exercise session following the lecture.

Exercises are corrected, and exercise sessions lead by Oliver Lomp.

Further reading

There is a book, which I partially follow. See here


Lecture slides Slides of lecture on motor control/muscle models
Exercises Exercise 2
Lecture slides Slides of the lecture on movement preparation
Lecture slides Slides of the lecture on elementary behaviors
Exercises Exercise 7 about timing
Exercises Reading for Exercise 7
Exercises Exercise 1
Lecture slides Slides for first DFT lecture
Lecture slides Slides for second DFT lecture
Exercises Exercise 5
Lecture slides Reading for exercise 5
Exercises Exercise 6
Lecture slides Slides on manupulator movement
Lecture slides Slides about the organization of the course
Lecture slides Slides of lecture on attractor dynamics for heading direction
Lecture slides Slides of the timing and coordination lecture
Lecture slides Rules for obtaining credit and for grading
Lecture slides Reading that complements the Introductory Lecture
Exercises Exercise 4
Lecture slides Slides of the introductory lecture
Exercises Reading for Exercise 2
Lecture slides Reading for the essay
Exercises Exercise sheet for the essay
Lecture slides Slides of the behavioral organization lecture
Lecture slides Slides of lecture on the degrees of freedom problem
Exercises Exercise 8 about the degrees of freedom problem

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210