Perception for Robotics

The purpose of this teaching unit is the study and implementation of perception systems for mobile robots, manipulative robots, humanoids, etc. The teaching is based on the proprioceptive and exteroceptive perception systems with a strong focus on vision systems. In the lectures, the general principles of perception and the functioning of the most widely used sensors (cameras, projectors, distance and position sensors, etc.) are presented. A series of practical work accompanies this teaching in the form of a long project punctuated by sub-goals addressing different parts of the course.

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This course presents the perception systems commonly used on all types of robots (e.g., mobile robots, manipulators, humanoids). The course presents proprioceptive and exteroceptive sensors with a focus on vision. We start by introducing the general principles of perception, and then explain the modeling and working principle of the main robot sensors: monocular cameras, stereo cameras, distance position and movement sensors, etc. The lab practicals consist of a robotic project with sub-goals addressing the various steps of the course.

The aim of this course is to familiarize students with the study and use of perception systems for robots. Its ambition is to ensure that a student who has taken it is able to read and understand a scientific article in this field, and to participate in the development of a robot's perception system by being a driving force in its design.

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The objective of this course is to make the student familiar with perception systems for robots. How to design a perception system? How to model it? How to use the sensor information? Its ambition is to enable the student to read and understand a scientific article in this field and to participate in the development of a robot's perception system.

Contact Hours:

            Taught lectures: 27 hours

            Laboratory Practicals: 15 hours

• Good knowledge of signal and image processing,
• Notions of robotics and automation,
• Good knowledge of computer engineering.
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• good knowledge in signal and image processing,
• notions of robotics and automation,
• good knowledge in computer engineering.

Written exam with documents based on scientific articles 60%.

40% hands-on

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Written exam based on scientific journal or conference papers 60%.

Practical project 40%

Geometric modeling of image formation,

Camera calibration

Stereovision principle

Motion vision (optical flow, target tracking, etc.)

Vision in structured light

Omnidirectional and plenoptic vision

Operating principle and main features of distance, motion and position sensors

Notions of visual servoing

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Geometric modeling of image projection,

Camera calibration

Basics of stereo-vision

Vision with movement (optical flow, target tracking, etc.)

Structured light vision

Omnidirectional and plenoptic vision

Working principle and main characteristics of distance, movement and position sensors

Basics of visual servoing 

CM: 27h

Practical work: 15h

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Taught lectures: 27 hours

Laboratory Practicals: 15 hours