( Will be updated. Last update: 8- 5 2020 )




Period: February 4th - May 19th 2020

Time:   Tuesday 14.15 16.00

Place:  LIACS, Room 407-409 (Workshops Room 302-304)





Dr Erwin M. Bakker ( )

Room 126a and LIACS Media Lab (LML)


Teaching assistant:

Laduona Dai


NB E-mail your name and student number to


During the last decade we have seen an explosion of all kinds of robots designed for tasks that previously were deemed too challenging. Robots have evolved from robotic arms and karts that could execute repetitive or simple tasks such as painting, welding and vacuum cleaning to autonomous cars, drones and humanoid helpers that execute their tasks in much less controlled and even natural settings. For this modern robots require sophisticated adaptive capabilities.
During this course we will have a thorough look at all important aspects of the robot-architecture used in modern and state of the art robots. The use of various actuators and sensors will be studied. Algorithms for low level tasks such as movement, dead reckoning, obstacle-detection, and balancing will be presented. Intermediate level tasks such as mapping, obstacle recognition and avoidance, and more advanced modes of reckoning, navigation and object manipulation will be studied. Finally, high level tasks such as human-robot-interaction and adaptive behavior in natural environments will be studied and proto-typed using state of the art sensor analysis, computer vision and audio recognition techniques.

Course objectives
After successfully finishing the Robotics course the student:

Requirements: C, C++

Grading (6 ECTS): Presentations and Robotics Project (60% of grade). Class discussions, attendance, workshops and assignments (40% of grade). It is necessary to be at every class and to complete every workshop. If you can not be there, you must contact Dr. E.M. Bakker before class!



Lecture slides and further materials will be made available on this site.


List of recommended books:


To be added




Schedule (tentative, visit regularly):
 Introduction and Overview
 No Class (canceled)
 Locomotion and Inverse Kinematics (will be updated) + Yetiborg Introduction
 Robotics Sensors and Image Processing 
 Yetiborgs Handout 13.15 - 14.45 in Room 126a
 Getting started + qualification challenge
 Project Proposals (presentation by students)
 SLAM Workshop + ( instructions for Windows 10 (64-bit) , instructions for Mac ), Yetiborg Qualification Challenge
 No Class (Project Team Meetings ,see e-mail of 14-3) 
 Robotics Vision ( AlexNet link will be removed ) 
 Online question hour.(a link with a WebEx invitation will be sent at 14.00) 
7-4 and 8-4
 Project Progress Meetings with each team.
 Robotics Reinforcement Learning
 Robotics Reinforcement Learning Workshop II (Instructions W10 will be made available soon, for now W10-users could consider using VirtualBox:
 Online project questions hour.(a link with a WebEx invitation will be sent at 14.00) 
 Online Project Demos
 Online Yetiborg Race (Postponed)

Assignments (workshops):

  1. Homework I:  Cool robots & DOF Assignments. See last slides of 18-2 Lecture Notes. Due 24-2 2020 at 14.00.
  2. Yetiborg Racing Teams See last slides of 18-2 lecture notes. Due 24-2 at 14.00.
  3. Project Titles+Abstract (Due 17-3 2020)
  4. SLAM Workshop I (Due: 6-4 2020) Instructions for Windows 10 (64-bit), instructions for Mac .
  5. Reinforcement Learning Workshop II (Due 12-5 2020)
  6. Yetiborg Race Code.
  7. Final Project Deliverables: (Due 2-6 2020)
    •  A link to a short movie of a demo of your project, starting with the title and list of team members ( max 60 seconds )
    • A technical report describing your project (Typically consists of: title, authors, abstract, intro, novelty, related work (if any), design, implementation, etc., results, conclusions, references.) (max 4 pages).
    • A link to a zip file containing all the project related code, designs, etc. and a ReadMe-file with clear instructions on how to use/employ it.)

Project Links
  • To be added