Study Programmes 2017-2018
WARNING : 2016-2017 version of the course specifications
Introduction to intelligent robotics
Duration :
30h Th, 4h Pr, 80h Proj.
Number of credits :
Master in data science (120 ECTS)5
Master in electrical engineering (120 ECTS)5
Master of science in computer science and engineering (120 ECTS)5
Master in data science and engineering (120 ECTS)5
Master in computer science (120 ECTS)5
Master in mechanical engineering (120 ECTS)5
Lecturer :
Renaud Detry
Coordinator :
Louis Wehenkel
Language(s) of instruction :
English language
Organisation and examination :
Teaching in the second semester
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Learning unit contents :
1: Basics: SE(3) geometry, sensors, actuators, controllers, kinematics. 2: Mobile robots: Locomotion, localization, navigation, SLAM. 3: Arms and grippers: Reaching, grasping, grasp learning. 4: Computer Vision: Feature extraction (Edge, Harris), Fitting (Ransac, Hough), Tracking (Kalman, Nonparametric), Object recognition (PCA, probabilistic model). See
Learning outcomes of the learning unit :
At the end of the course, students will be able to:
  • Extract information from video streams (identity/position of objects/persons, body pose, 3D structure).
  • Plan actions from sensory data (navigation, grasping, via optimization, learning or control).
  • Translate these actions into a sequence of motor commands that can be executed on the robot.
A group project will allow students to practice the concepts studied in class. Students will program a robotic agent capable of processing images, plan actions, and execute these actions on a robot. The agent will be evaluated in a robot simulator (V-REP).
Prerequisite knowledge and skills :
  • Programming skills
  • Basic math
  • Elements of probabilities and statistics
Planned learning activities and teaching methods :
  • Oral Courses
  • Seminars
  • Group project
Mode of delivery (face-to-face ; distance-learning) :
Face-to-face delivery.
Recommended or required readings :
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. See the course page for download and purchase information.
Assessment methods and criteria :
Group project (evaluating the assimilation of practical notions).
Work placement(s) :
Organizational remarks :
Course webpage:
Contacts :
Renaud Detry: