Robotics - Learning

The module will cover the following points:

• Transfer function link and differential equation
• Representation and continuous status feedback (eigenvalues, stability)
• Representation and sampled status feedback
• Feedback control without and with full-loop feedback, LQR control
• State observers
• Nonlinear control with examples

Practical work: applying knowledge to real-world examples (e.g., electric motors), programming in Python (numpy and control libraries).

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This teaching unit complements basic training in signal processing with in-depth knowledge of deterministic or random digital signals. This knowledge is essential in all engineering sciences, as digital signal processing is currently used in the majority of applications.

In the first part (10.5 hours of lectures, 6 hours of practical work), the course covers the sampling and quantification of continuous signals and the relationship between digital signals and the original continuous signal. It defines the discrete Fourier transform of digital signals, its estimation, and its use on real deterministic signals.

The second part of the course (9 hours of lectures, 4.5 hours of tutorials, 3 hours of practical work) is dedicated to random signals and how the properties of certain random signals can be used either to reduce the random part of a signal whose deterministic part we wish to favor (filtering, increasing the signal-to-noise ratio, etc.) or to improve information transmission or even identify complex linearized systems.

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• This teaching unit complements basic training in analog electronics with in-depth knowledge of signal filtering, amplification, and modulation. This knowledge is essential for understanding and implementing analog electronic systems in all fields of engineering science.
• Teaching is organized in the form of lectures, tutorials, and practical work, opening up the possibility for mini-projects.

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This teaching unit, devoted to the fundamentals of digital electronics, is structured in an original way around a technical project, carried out individually or in pairs, the progress of which will follow the progression of the associated courses.

Each project topic will be assigned at the beginning of the teaching unit.

The main concepts of digital electronics will be explored in depth through lectures, and practical work may supplement the theoretical aspects to guide the progress of the project.

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This teaching unit consists of several parts, the first of which deals with the power electronics structures required to power an electronic system. The second part will focus on the current or voltage regulation of these structures. A third part will deal with the conversion functions required to control MCC and DC Brushless actuators.

The last section presents actuator topologies for robotics and their implementation. DC motor control and autopilot control of a synchronous motor will illustrate this last section.

Practical work will enable students to observe the principle and implementation of regulated systems for electronics and actuators. This course unit may serve as a basis for M1 project topics.

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Computer engineering is the discipline that deals with the design, development, and manufacture of computer systems, both hardware and software.

This discipline has become fundamental in engineering sciences, whether in electronics, robotics, signal processing, measurement, etc., due to the important role that computers now play in all these fields.

This module aims to encourage students to develop computer code on a scale corresponding to that of a complete software program. The quantity of code involved naturally creates a need to structure the code so that it remains viable, and the concepts associated with code structuring will therefore be addressed or reinforced.
Teaching is therefore organized mainly around practical work and projects. The context largely concerns the core themes of the EEA: signal processing (acquisition chain), instrument interfacing, and data retrieval via the internet on an embedded Linux platform. The topic of event-driven programming through the development of graphical interfaces will also be covered. The languages used will be Labview and Python. Portions of C/C++ may be used in projects at the students' initiative.

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- Controller summary.

- Robust synthesis and risk management.

- Representation and synthesis of synchronous machines.

- Description/synthesis language.

- The basics of the VHDL language (entity, architecture, etc.).

- Behavioral and structural descriptions.

- Simulation (Testbench).

- Reprogrammable circuits (CPLD, FPGA).

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Tutorial courses in specialized English and English for communication, aimed at developing professional autonomy in the English language.

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Project in partnership with a research laboratory and/or a company, highlighting the student's scientific skills, autonomy, and adaptability.

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The internship or final project should highlight the student's scientific skills, independence, and adaptability:

• Internship lasting 2 to 3 months (maximum 5 months) to be carried out in a research laboratory or within a company;
• or a 3-month final project in a research laboratory or teaching project room.

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Description:

1 - The aim is to enable students to understand the importance of a well-prepared application that is tailored to a specific internship or job advertisement, or linked to the activities of a professional organization in the case of a speculative application; to write resumes and cover letters; to gain a better understanding of their personality; to use new technologies (social networks and job boards) and to tailor their search to their career plans. Finally, to know how to prepare for and behave during job interviews.

2 - The aim is to enable students to write a scientific article following the completion of a project. To do this, they must be familiar with the objectives and characteristics of the article, the plan to be followed, the different stages of completion, and the rules of presentation. Next, in order to present their project orally, students must know and be able to apply the general presentation structure; define appropriate and relevant visual aids; follow the rules of oral expression in order to express themselves correctly and professionally (vocabulary, syntax, etc.); and adopt behaviors that energize their speech and engage their audience.

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Nowadays, image processing is ubiquitous in information technology: medicine, biology, agriculture, entertainment, culture, measurement, mechanics, etc.

Image processing involves applying mathematical transformations to images in order to modify their appearance or extract information from them. More generally, image processing aims to manipulate the underlying information contained in an image. While it has long been performed using electronic circuits, image processing is now carried out almost exclusively digitally, i.e., using algorithms generally programmed with an imperative language (C, C++, Java, Python, etc.).

This teaching unit aims to provide a solid foundation in image processing. It covers, among other things, image formation and acquisition, colorimetric transformations, morphological operations, geometric transformations, compression, frequency transformations, recognition and matching techniques, and an introduction to deep learning methods. The courses are supplemented by supporting videos.

The teaching unit consists mainly of 11 lectures covering the basics of the main areas of image processing and three practical sessions, with topics to be chosen from six proposals. Students can choose to carry out the work on images they bring in that are relevant to their field of study.

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The module will cover the following points:

• Introduction to the Git version control system
• Introduction to ROS middleware for building robotic applications
• Modularization of a robotic application

Practical work: Implementation of a ROS application, testing on a simulator, and verification on a real robot

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The module will cover the following points:

• Introduction to robotics: history, types of robots, serial and parallel mechanisms, applications
• Components (sensors and actuators)
• Trajectory generation (in joint and operational spaces)
• Direct/inverse geometric models, direct/inverse kinematic model
• Kinematics control and singularities
• Issues and applications in mobile robotics
• Non-holonomic models: unicycle, bicycle, car
• Sensors and odometry
• Location by rangefinder and data fusion (Kalman filter)
• Mapping (homogeneous transformations and ICP)
• Navigation (positioning control, path tracking)

Practical work: applying acquired knowledge to a real robot (either a manipulator arm or a wheeled robot), ROS programming with Git and Python.

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Advanced Programming

• object-oriented programming (C++)
• classes
• attributes/methods
• inheritance
• pointers
• templates
• C++11 standards

Artificial Intelligence

• learning: State of the art, issues, applications
• PCA (Principal Component Analysis)
• SVM (Support Vector Machines)
• Generations 1, 2, and 3 of neural networks (spike technologies, etc.)
• neural network learning
• convolutional neural networks
• reinforcement learning
• genetic algorithms

Practical Work

• Implementation of a logic simulator for microelectronics
• Implementation (in C++) and integration (in ROS) of robotics algorithms
• Introduction to classification tools based on artificial intelligence
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• Advanced Programming

  • object-oriented programming (C++)
  • classes
  • attributes/methods
  • heritage
  • pointers
  • templates
  • C++11 standards

  Artificial Intelligence

  • Machine Learning: State of the art, problems, applications
  • PCA (Principal Component Analysis)
  • SVM (Support Vector Machines)
  • Neural networks generations 1, 2, and 3 (spike technologies, etc.)
  • Convolutional neural networks
  • Reinforcement learning
  • Genetic Algorithms

  Laboratory Practicals

  • Implementation of a logical simulator for microelectronics
  • Implementation (in C++) and integration (in ROS) of robotic algorithms
  • Introduction to classification tools based on artificial intelligence

   

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Optimization

• Linear optimization
• Nonlinear optimization (gradient method, optimal step gradient, Lagrange multipliers)
• Optimization applied to robotics (optimal control based on quadratic programming under linear constraints)

Embedded systems

• Harvard & Von Neumann architectures
• Knowledge and implementation of the main features of a microcontroller
• Choosing and sizing an embedded programming solution for a given need
• Programming a Raspberry Pi board in C
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• Optimization

  • Linear optimization
  • Non-linear optimization (gradient descent, Lagrange multipliers)
  • Applying optimization in robotics (optimal control based on quadratic programming under linear constraints)

  Embedded Systems

  • Harvard & Von Neumann Architectures
  • Knowledge and implementation of the main functions of a microcontroller
  • Selection and implementation of an embedded programming solution adapted to specific design specifications
  • C Programming on a Raspberry Pi

   

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This teaching unit covers a range of topics in robotics, from micro to macro scale, including micro manipulators, cable robots, surgical robots, underwater robots, flying robots, humanoid robots, as well as teleoperation, virtual and augmented reality, and operational safety. The content of each topic is detailed below. Mini-projects on the above topics will be carried out to further explore the basics taught, using both simulation software and real robots.

Micro-robotics: Micro-robotics involves the design, modeling, and control of miniaturized robotic systems capable of performing manipulation tasks on objects ranging in size from 1µm to 1mm. Applications include all fields requiring high precision (assembly of mechanical, electronic, or optical microsystems, microsurgery, etc.).At these scales, robots cannot be created by simply miniaturizing conventional robots. New robot concepts and new actuation principles must be used. This course is an introduction to microrobotics and presents the essential concepts of scale effects, the physics of the microworld, deformable and flexible robotics, and microactuators.

Surgical robotics: The objective of this course is to give students an introduction to the field of surgical robotics. The aim is to enable them to understand the needs expressed by clinicians and to use a few examples to illustrate the process that led to the design and production of robots used for surgical procedures. Some design elements and control architectures will be discussed, with an emphasis on the need to ensure the safety of patients and medical staff.

Underwater and flying robots: Mobile robotics dedicated to aerial and underwater environments relies on specific features that will be introduced in this course. Current solutions and outstanding issues will be presented. Questions relating to modeling and nonlinear controls applied to under/iso/over-actuated systems will be addressed.

Humanoid robotics: This will involve presenting advanced geometric and kinematic modeling methods for tree-like robotic structures such as humanoid robots. Basic concepts will also be presented on the center of mass, center of pressure, ZMP, static stability, and dynamic stability. A study on bipedal walking control will be carried out, including walking models, trajectory generation, and ZMP/COM control, as well as dynamic stabilization of the robot. The second part of the course will focus on the kinematic control of highly redundant structures (Ax=b underdetermined systems) using methods based on constrained optimization techniques (LP, QP) and hierarchical control based on zero-space projection techniques or task hierarchies based on QP or LP hierarchies.

Parallel cable robots: this course presents the principle of parallel cable robots (PCRs), followed by a state-of-the-art review including application examples, PCR demonstrators, and commercial PCRs. The geometric, kinematic, and dynamic models of CPCs are then developed. Based on these models, the different types of CPCs, several definitions of their workspace, the main concepts useful for their design, and simple control methods will finally be presented.

Virtual and augmented reality: Augmented reality (AR) and virtual reality (VR) techniques consist of interactive simulation of a 3D universe in which the user is immersed. This simulation is generally visual in nature, but it can also include other perceptual information through several sensory modalities: spatialized sound, haptic or force feedback, somatosensory approach, etc. This course is an introduction to the different techniques used in VR/AR systems: we will cover the main 3D synthesis libraries (OpenGL, Vulkan), the peripherals available on the market, the basics of physics engines, and the techniques used to locate the user and estimate their point of view in real time.

Reliability and operational safety: this course focuses on the reliability of a robotic system, particularly during the operational phase. When a robot operates in a complex and partially unknown environment, unforeseen events may occur to which the system must respond in order to ensure its own safety and that of its environment. This course will introduce the basic concepts of operational safety and present examples of reliability mechanisms applied to mobile robotics.

Teleoperation: This section provides a brief introduction to the history of teleoperation development, teleoperation component modeling, and schematics. Performance evaluation criteria for teleoperation are defined. Methods for performance analysis and control design are also introduced. The course covers applications of teleoperation in the field of surgical robotics, as well as open questions and remaining challenges.

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This teaching unit covers a set of specialties in robotics, ranging from micro to macro scales, including micro manipulation, surgical, submarine, flying, humanoid, and cable-driven robots, as well as teleoperation, virtual and augmented reality, and operational safety. The content of each sub-unit is detailed below. Projects on the topics mentioned will be carried out to deepen the theoretical foundations using both simulation software and real robots.

Micro-robotics: Micro-robotics concerns the design, modeling, and control of miniaturized robotic systems capable of performing handling tasks on objects between 1µm and 1mm in size. Application fields include all areas requiring high precision (assembly of mechanical, electronic, or optical microsystems, microsurgery, etc.). At these scales, robots cannot be fabricated by simple homothetic miniaturization of conventional robots. New robot concepts and new actuating principles must be used. This course is an introduction to micro-robotics and presents the essential concepts of scale effect, physics of the micro-world, deformable and flexible robotics, and micro-actuators.

Surgical robotics: The objective of this sub-unit is to give students an introduction to the field of surgical robotics. It is about being able to understand the needs expressed by clinicians and to show, through a few examples, the process that allowed the development of robots used for surgical procedures. Some design elements as well as some control architectures will be discussed, emphasizing the need to ensure the safety of the patient and the medical team.

Submarine and flying robots: The specificities of underwater and aerial robotics will be presented. Current solutions and open issues will be exposed. The basic elements required by the control design for this type of vehicles, from modeling to nonlinear control techniques, will be addressed, according to the under/iso/over actuation property of the systems.

Humanoid robotics: This sub-unit concerns advanced kinematic and differential kinematics modeling methods for humanoid robots. Basics on the center of mass (COM), the center of pressure, the zero-moment point (ZMP), static stability, and dynamic stability are addressed. A study on bipedal gait control will be carried out, including gait models, trajectory generation, and ZMP/COM control, as well as dynamic stabilization of the robot. The second part of the sub-unit focuses on the differential kinematic control of highly redundant structures (under-determined system of type Ax = b) using methods based on optimization techniques (LP, QP) under constraints, as well as hierarchical control based on projection into null space or task hierarchies based on QP or LP hierarchies.

Cable-driven parallel robots: This sub-unit presents the basic principle of Cable-Driven Parallel Robots (CDPRs) followed by a state of the art including application examples, CDPR demonstrators, and commercial CPPRs. Geometric, kinematic, and dynamic models of CDPRs are then developed. Based on these models, the different types of CDPRs, several definitions of their workspace, the main concepts useful for their design, as well as simple control strategies will finally be presented.

Virtual and Augmented Reality: AR and VR consist of providing the user with an interactive simulation of a 3D world, where one can simulate physics, but also enhance it with additional data visualization. This simulation is usually mostly graphical, but it can also include other perceptual information across multiple sensory modalities: spatialized sound, haptics, somatosensory, etc. This course is an introduction to the different techniques involved in creating an AR/VR system. We will address current 3D technologies (OpenGL, Vulkan), available devices, the basics of physical engines, and the localization and vision techniques used to track user movements in real time and compute their point of view.

Operational safety of robots: This part concerns the reliability of robotic systems, mainly in the operational phase. When a robot moves in a complex and partially unknown environment, unforeseen events can occur. The system must react to these events to ensure its own safety and that of its environment. This course will introduce the basic notions of dependability, and will present examples of safety mechanisms applied to mobile robotics.

Teleoperation: This part covers a brief introduction to the development history, the typical structures of teleoperation schemes, and the modeling of teleoperation components. Based on the system modeling, the teleoperation performance evaluation criteria are defined and, accordingly, the performance analysis and control design methods are introduced. The course also provides the applications of teleoperation in the domain of robotic surgery as well as the open issues and challenges existing in practical implementation.

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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.

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This teaching unit covers the techniques and tools required for kinematic and dynamic modeling and control for manipulation robotics. The courses are structured around the following four areas:

1) Modeling of manipulator robots: homogeneous transformations, direct and inverse geometric models, kinematic modeling, study of singularities

2) Introduction to the dynamics of manipulator robots: Euler-Lagrange formalism, Newton-Euler formalism, algorithms for calculating dynamics

3) Articulation and operational commands in free space

4) Motion control in constrained spaces: interaction and compliance models, position/force control, impedance and admittance control, motion generation, application examples.

Several examples of all these techniques will be covered in tutorials and practical sessions using MATLAB/V-REP tools on various manipulation robots (6- and 7-axis robots) and also on a real humanoid robot called "Poppy." 

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This teaching unit covers the techniques and tools necessary for kinematic and dynamic modeling and the control of robot manipulators. The lectures provided are structured around the following four axes:

1) Modeling of robot manipulators: homogeneous transformations, direct and inverse kinematic models, differential kinematic modeling, study of singularities

2) Introduction to the dynamics of robot manipulators: Euler-Lagrange formalism, Newton-Euler formalism, algorithms for the computation of dynamics

3) Joint space and operational space controls in free space

4) Control of movements in constrained space: interaction and compliance models, hybrid position/force control, impedance and admittance control, generation of movement, application examples.

Several examples of all of these techniques will be addressed in supervised work and practice using MATLAB/V-REP tools on different manipulation robots (6- and 7-axis robots) and also on a real humanoid robot, "Poppy."

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Project in partnership with a research laboratory and/or a company, highlighting the student's scientific skills, autonomy, and adaptability.

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5- to 6-month internship to be completed in a research laboratory or within a company, highlighting the student's scientific skills, independence, and adaptability.

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Preparation for professional integration.

Teaching provided by a senior HR consultant, former HR manager for large corporations, who draws on her extensive recruitment experience in her teaching.

Teaching approach that encourages sharing experiences and responding to students' situations and questions.

General information on recruitment from A to Z, how to be more effective in your search, insight into the approaches of final recruiters, recruitment agencies, and service companies.

Simulated job interviews in small groups with personalized debriefing led by the instructor.

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Tutorial courses in specialized English and English for communication, aimed at developing professional autonomy in the English language.

Reinforce and consolidate the knowledge acquired in Master 1.

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