Introduction to Intelligent Robotics

Introduction to Intelligent Robotics INFO0948 is a Master's course that I created and taught at ULiege in 2013–2018. The course explains the basic concepts that allow robots to build a world representation from sensory data, and to plan and perform complex tasks such as navigating a building, or manipulating tools.

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Introduction to Intelligent Robotics INFO0948 is a Master's course that I created and taught at ULiege in 2013–2018. The course explains the basic concepts that allow robots to build a world representation from sensory data, and to plan and perform complex tasks such as navigating a building, or manipulating tools.

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I no longer teach this course. This page is obsolete. The course is now taught by Pierre Sacré, see the course page on Pierre’s website, or the ULiege INFO0948 syllabus.

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Course Material

Group Project

Setup instructions and project details are on the TRS website: http://teaching-robotics.renaud-detry.net/trs.

Objectives

At the end of this course, student will be able to solve the following problems:

  1. Extract information from video streams (object/people identity/position, body postures, 3D room and object structures)
  2. Infer a useful behavior from sensory data (navigation, grasping; via optimization, machine learning, or control)
  3. Generate a set of robot commands that implement the desired behavior.

A group project allows students to gain practical experience. In this project, students will program a robotic agent that processes images, plans a task based on the image data, and executes a set of motor commands that complete the task. The robot will be simulated in the V-REP simulator.

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The V-REP simulator.

We are currently discussing with Kuka the possibility of borrowing a youBot for a month, to allow groups (some, maybe not all) to implement their work on a real robot.

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The Kuka youBot mobile robot, in simulation (left), and in the real world (right).

Required Readings

rvc

The course is largely based on the book Robotics, Vision and Control: Fundamental Algorithms in MATLAB, written by Peter Corke, published by Springer in 2011.

Going Further

The books listed below are good complements to P. Corke’s Robotics, Vision and Control.

  • ELEN0062 Apprentissage inductif appliqué - Pierre Geurts, Louis Wehenkel
  • ELEN0016 Traitement numérique d’images - Marc Van Droogenbroeck
  • SYST0003 Linear control systems - Raphaël Fonteneau
  • PROT0430 Robotique biomédicale et prothèses actives - Olivier Bruls
  • MECA0031 Cinématique et dynamique des mécanismes - Olivier Bruls

Students are encouraged to concurrently follow the course Applied Inductive Learning. (Applied Inductive Learning is however not a prerequisite.)