Perception for Robotics

This teaching unit focuses on the study and implementation of perception systems for mobile robots, manipulation robots, humanoid robots, etc. The course centers on proprioceptive and exteroceptive perception systems, with a strong emphasis on vision systems. Lectures cover the general principles of perception and the functioning of the most commonly used sensors (cameras, projectors, motion and position sensors, etc.). This teaching is accompanied by a series of practical assignments in the form of a long project with sub-goals covering 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 students who have taken the course are able to read and understand scientific articles in this field and participate in the development of a robot's perception system by contributing ideas to its design.

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The objective of this course is to familiarize students 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 students 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,
• Concepts of robotics and automation,
• Good knowledge of computer engineering.
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• good knowledge of signal and image processing,
• concepts of robotics and automation,
• good knowledge in computer engineering.

Written exam with documents based on scientific articles 60%

Practical work 40%

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Written exam based on scientific journal or conference papers 60%

Practical project 40%

Geometric modeling of image formation,

Camera calibration

Principle of stereovision

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

Structured light vision

Omnidirectional vision and plenoptic vision

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

Concepts of visual enslavement

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Geometric modeling of image projection,

Camera calibration

Fundamentals 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

Fundamentals of visual servoing 

CM: 27 hours

Practical work: 3 p.m.

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Taught lectures: 27 hours

Laboratory Practicals: 15 hours