30h Th, 4h Pr, 80h Proj.
Number of credits
Language(s) of instruction
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
- Basics: SE(3) geometry, sensors, actuators, controllers, kinematics.
- Mobile robots: locomotion, localization, navigation, SLAM.
- Arms and grippers: reaching, grasping, grasp learning.
- Computer vision: feature extraction (Edge, Harris), curve fitting (Ransac, Hough), tracking (Kalman, Nonparametric), object recognition (PCA, probabilistic model).
Learning outcomes of the learning unit
- 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.
Prerequisite knowledge and skills
- Programming skills
- Basic math
- Elements of probabilities, statistics, and algorithmics
Planned learning activities and teaching methods
- Oral courses
- Group project
Mode of delivery (face to face, distance learning, hybrid learning)
Organisational adjustments related to the current health context
Recommended or required readings
The course notes et the slides will be available on the course's webpage at the beginning of the semester: http://www.montefiore.ulg.ac.be/~sacre/INFO0948/.
Assessment methods and criteria
Group project (evaluating the assimilation of practical notions).
Lecturer: Pierre Sacré (firstname.lastname@example.org).