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Autonomous Robotics: Action, Perception, and Cognition

This course will take place in remote teaching form. All interaction takes place through this webpage (rather than through Moodle). 

The course is open to all students. Please register by  follow the link to "e-learing", creating an account (if you don't have one yet). When you create an account, please enter your degree program specifically (e.g. Master in Angewandte Informatik). Just listing "Master" doesn't help us. We really like to know what disciplinar you come from so we can make sure we have the right offering given your background.

Registering in this way enables you to see all material, access the links to the ZOOM lectures, and upload your solutions to exercises. Some of the material is visible also to unregistered visitors. 

At the scheduled lecture times, we will have live life video-streamed lectures. Registered participants will be able to see the ZOOM link under "live sessions" in the e-learning portion of this web page. This works best if you use the ZOOM app, but a web based ZOOM interface works too. You can use audio to ask questions and are welcome to activate your video camera as well, especially during discussion. 

Live sessions will start on Thursday, 15th of April 2021 at 14:15. 

The lectures will be recorded and will be available for asynchronous viewing. Participating in the live session and asking questions is highly encouraged, however. The discussion portion of the lecture is not put online. 

We will have live sessions for the exercises at the listed times. Th exercise sessions will not be recorded.  

All course material will be on this webpage, including links to all the video material, to the lecture slides, exercises, and readings.

After registering, you will be able to upload your solutions to the exercises and will also be able to see your results once your submission has been corrected. You will be also be able to use discussion forums to ask questions synchronously and interact with your peers. 

Autonomous robotics is an interdisciplinary research field in which embodied systems equipped with their own sensors and with actuators generate behavior that is not completely pre-programmed. Autonomous robotics thus entails perception, movement generation, as well as core elements of cognition such as making decisions, planning, and integrating multiple constraints.

This course touches on various approaches to this interdisciplinary problem. In the first half of the course, the main emphais will be on dynamical systems methods for generating movement in vehicles.  The main focus of the course is, however, on solutions to autonomous movement generation that are inspired by analogies with how nervous systems generate movement. The second half of the course will review core problems in human movement  science, including the degree of freedom problem, coordination, motor control, and the relex control of muscles. 

Lecturers

Details

Course type
Lectures
Credits
6 CP
Term
Summer Term 2021
E-Learning
e-learning course available

Dates

Lecture
Takes place every week on Thursday from 14:15 to 16:00.
First appointment is on 15.04.2021
Last appointment is on 22.07.2021
Exercise
Takes place every week on Thursday from 16:15 to 17:00.
First appointment is on 22.04.2021
Last appointment is on 22.07.2021

Requirements

The emphasis of the course is on learning concepts, practicing interdisciplinary scholarship including reading and writing at a scientific and technical level. Mathematical concepts are used throughout, so understanding these concepts is important. Mathematical skills are not critical to mastering the material, but helpful. The mathematics is mostly from the qualitative theory of dynamical systems, attractors and their instabilities. Short tutorials on some of these concepts will be provided. 


Exercises

The course is accompanied by exercises, which will be posted weekly. Participants will upload their solutions, which will be corrected and marked (for bonus points). The exercises and their solutions will be discussed by Rachid Ramadan in the weekly exercise live session.

Further reading

Readings will be posted on this web page. Also have a look at the web page of the Dynamic  Field Theory community that is interested in related problems and solutions. There you find more exercises, reading material, slides and lecture videos that have some overlap with the lecture.

Teaching Units

Introduction

Organizing the lecture course: how to participate, how to do exercises, what to expect. 

Introduction to the topic of the lecture course. 

Lecture slides Organizational issues
Document Rules for credit
Lecture slides Introduction
Video Introduction
Dynamical Systems Tutorial
Lecture slides Dynamical Systems Tutorial
Video Dynamical Systems Tutorial
Exercises Exercise 1: Dynamical Systems Tutorial
Vehicle motion planning
Lecture slides Attractor dynamics approach to vehicle motion planning Part 1

This is lecture is about what we will l later call the "symbolic" variant of the attractor dynamics approach to vehicle motion planning. The lecture also covvers a variant of that method that accounts for the movement paths in human pedestrian motion. 

Video Attractor dynamics approach to path planning Part 1
Document Background reading for the attractor dynamics approach to vehicle motion planning
Exercises Exercise 2 on the attractor dynamics approach to path planning
Lecture slides Attractor dynamics approach to path planning Part 2: sub-symbolic
Video Attractor dynamics approach to path planning: Part 2 sub-symbolic
Exercises Exercise 3 on the sub-symbolic attractor dynamics for vehicle motion planning
Document Reading for exercise 3

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