MPŠ MP&Scaron MP&Scaron MP&Scaron Avtorji

Jožef Stefan
Postgraduate School

Jamova 39
SI-1000 Ljubljana

Phone: +386 1 477 31 00
Fax: +386 1 477 31 10


Course Description

Robot Vision


Information and Communication Technologies, third-level study programme


prof. dr. Aleš Ude


The goal of this course is to acquire basic knowledge of computer vision, especially robot vision. The students will become familiar with image processing methods and their application for the control of robotic systems. Students who will successfully complete this class will be able to independently select suitable image processing techniques for a given task and apply the acquired information for the control of robotic systems.


Robot vision is essentially a computational process whose goal is to interpret the observed scenes and events. Especially important for robot vision is the real-time processing of incoming images, which enables closed-loop control and timely decision making. This class will introduce the students to the following areas and methodologies:
• fundamental techniques of computer vision (edge detection, segmentation, motion analysis, object recognition, localization and tracking);
• visual servoing (position-based visual servo control, image-based visual servo control);
• active vision and vision-based manipulation;
• biological and humanoid vision (oculomotor behaviors, visual attention, humanoid heads).

Course literature:

Selected chapters from the following books:
• Corke, P. Robotics, Vision and Control: Fundamental Algorithms in MATLAB, Springer-Verlag, Berlin, Heidelberg, 2013, ISBN: 978-3642201431.
• Szeliski, R. Computer Vision Algorithms and Applications, Springer, London, Dordrecht, Heidelberg, New York, 2011, ISBN: 978-1-84882-934-3.
• R. B. Fisher (Ed.),, CVonline: The Evolving, Distributed, Non-Proprietary, On-Line Compendium of Computer Vision.
• Siciliano, B. and Khatib, O. (Eds.), Springer Handbook of Robotics, Springer-Verlag, Berlin Heidelberg, 2008, ISBN: 978-3-540-23957-4.

Significant publications and references:

• R Bevec, A Ude. Building object models through interactive perception and foveated vision. Advanced Robotics 29, 2015
• B Ridge, A Leonardis, A Ude, M Deniša and D Skočaj. Self-supervised online learning of basic object push affordances. International Journal of Advanced Robotic Systems 12:24, 2015.
• A Gams, B Nemec, A J Ijspeert, A. Ude. Coupling movement primitives: Interaction with the environment and bimanual tasks, IEEE Transactions on Robotics, 30(4), 816-830, 2014.
• D Schiebener, J Morimoto, T Asfour, A Ude. Integrating visual perception and manipulation for autonomous learning of object representations, Adaptive Behavior, 21(5), 328-345, 2013.
• D Omrčen, A Ude. Redundancy control of a humanoid head for foveation and three-dimensional object tracking: A virtual mechanism approach. Advanced Robotics 24(15), 2171-2197, 2010.


Seminar work (50%)
Oral defense of seminar work (50%)

Students obligations:

Seminar work and oral defense of seminar work.