Perception for Robotics

The purpose of this course is to study and implement perception systems for mobile, manipulative, and humanoid robots, among others. The course focuses on proprioceptive and exteroceptive perception systems, with a strong emphasis on vision systems. Lectures cover the general principles of perception and the operation of the most commonly used sensors (cameras, projectors, distance, motion, and position sensors, etc.). A series of lab sessions accompanies this course in the form of a long-term project divided into sub-goals that address different parts of the course.

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This course covers the perception systems commonly used in all types of robots (e.g., mobile robots, manipulators, humanoids). The course covers proprioceptive and exteroceptive sensors, with a focus on vision. We begin by introducing the general principles of perception, and then explain the modeling and operating principles of the main robot sensors: monocular cameras, stereo cameras, distance, position, and motion sensors, etc. The lab sessions consist of a robotics project with sub-goals that address the various steps of the course.

The purpose of this course is to familiarize students with the study and use of perception systems for robots. Its goal is to ensure that students who have taken this course are able to read and understand a scientific article in this field and to participate in the development of a robot’s perception system by actively contributing ideas during its design.

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The objective of this course is to familiarize students with perception systems for robots. How do you design a perception system? How do you model it? How do you use sensor data? The course aims 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:

            Lectures taught: 27 hours

            Laboratory Practicals: 15 hours

• Strong knowledge of signal and image processing,
• Concepts in robotics and automation,
• Strong knowledge of computer engineering.
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• good knowledge of signal and image processing,
• concepts of robotics and automation,
• Good knowledge of computer engineering.

Written exam based on scientific articles 60%

Lab 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

The Principle of Stereovision

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

Structured Light Vision

Omnidirectional vision and plenoptic vision

Operating Principles and Key Features of Distance, Motion, and Position Sensors

Concepts of Visual Servo Control

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Geometric modeling of image projection,

Camera Calibration

Basics of Stereo Vision

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

Structured Light Vision

Omnidirectional and Plenoptic Vision

Working Principle and Main Characteristics of Distance, Motion, and Position Sensors

Basics of Visual Servoing 

CM: 27 hours

Practical Training: 3:00 p.m.

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Lectures taught: 27 hours

Laboratory Practicals: 15 hours