Robotics -Learning

The module will cover the following:

• Link transfer function and differential equation
• Continuous state representation and feedback (eigenvalues, stability)
• Representation and Sampled State Feedback
• Status feedback control without and with full loopback, LQR control
• State Observers
• Non-linear control with examples

Practical work: implementation of knowledge on real examples (e.g. electric motors), programming in python (numpy and control libraries).

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

The first part (10:30 h lecture, 6 h hands-on) covers the sampling and quantization of continuous signals, and the relationship between digital signals and the original continuous signal. We define the discrete Fourier transform of digital signals, its estimation and its use on real deterministic signals.

The second part of the course (9h Lecture, 4h30 TD, 3h TP) 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 emphasize (filtering, increasing the signal-to-noise ratio, etc.) or to improve the transmission of information or identify complex linearized systems.

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

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This teaching unit, dedicated to the basics 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 progress of the associated courses.

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

The main notions of digital electronics will be deepened through lectures and practical work may complement the theoretical aspects to guide the progress of the project.

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

The last part presents actuator topologies for robotics and their implementation. The regulation of a DC motor and the self-pilot control of a synchronous motor will illustrate this last part.

Practical work will be carried out to observe the principle and implementation of regulated systems for electronics and actuators. This UE can be the support of the M1 project subjects.

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

This discipline has become fundamental in engineering sciences, whether in electronics, robotics, signal processing, measurement, etc. due to the important role that the computer has taken in all these areas.

This module aims to lead students to develop computer code in a volume corresponding to the scale of a complete software. The amount of code associated with it naturally creates a need to structure the code to keep it viable, and the concepts associated with structuring the code will therefore be addressed or reinforced.
Teaching is therefore mainly organised around practical work and projects. The context largely concerns deep themes of the EEA: signal processing (acquisition chain), instrument interfacing, and data transmission via the Internet on an embedded Linux platform. The topic of event-based programming through the development of graphical interfaces will also be addressed. The languages serving as support will be Labview and Python. Portions of C/C++ can be used at the initiative of the students in the projects.

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- Controller Summary.

- Robust synthesis and contingency management.

- Representation and synthesis of synchronous machines.

- Description/synthesis language.

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

- Behavioral and structural descriptions.

- Simulation (Testbench).

- Reprogrammable circuits (CPLD, FPGA).

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TD courses in English for Specialization and English for Communication and which aims at 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 end-of-study project must highlight the student's scientific skills, autonomy and adaptability:

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

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Description* :

1 - The aim is to allow students to understand the importance of a well-prepared application that is in line with an internship or job advertisement or in connection with the activities of a professional structure in the case of an unsolicited application; write CVs and cover letters; to know oneself better in terms of personality; use new technologies (social networks and job boards) and orient their research according to their professional project. Finally, to know how to prepare and behave during job interviews.

2 - It is a question of allowing students to write a scientific article following the completion of a project. To do this, they must know the objectives and characteristics, the plan to be applied, the different stages of implementation and the rules of presentation. Then, to present their project orally, students must know and be able to apply the general presentation structure; define appropriate and relevant visual aids; respect the rules of oral expression in order to express oneself correctly and in a professional manner (vocabulary, syntax, etc.); adopt behaviours that energize the discourse and allow you to hook your audience.

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Nowadays, image processing is omnipresent in information technologies: medicine, biology, agriculture, entertainment, culture, measurement, mechanics...

Image processing consists of 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. Although it has long been carried out using electronic circuits, image processing is nowadays carried out almost exclusively digitally, i.e. via algorithms generally programmed with an imperative language (C, C++, Java, Python, etc.).

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

The teaching unit is mainly composed of 11 didactic courses covering the basics in the main areas of image processing and 3 practical work sessions whose subjects are to be chosen from 6 proposals. Students can choose to carry out the work on images they bring corresponding to their field of training.

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The module will cover the following:

• Introduction to the Git version control system
• Introduction to ROS Middleware for Robotics Applications
• Modularization of a robotic application

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

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The module will cover the following:

• Introduction to robotics: history, type of robots, series and parallel mechanisms, applications
• Components (sensors and actuators)
• Trajectory generation (in the articular and operational spaces)
• Direct/Inverse Geometric Models, Direct/Inverse Kinematics Model
• Kinematic control and singularities
• Issues and applications in mobile robotics
• Non-holonomic models: unicycle, bicycle, car
• Sensors and odometry
• Distance finder and data fusion location (Kalman filter)
• Mapping (homogeneous transformations and KPIs)
• Navigation (installation regulation, path tracking)

Practical work: implementation of the skills on a real robot (either manipulator arm or wheeled robot), ROS programming with git and python.

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Advanced programming

• object-oriented programming (C++)
• classes
• attributes/methods
• heritage
• 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

• Setting up a logic simulator for microelectronics
• Implementation (in C++) then 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 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

• Architectures de Harvard & de Von Neumann
• Knowledge and implementation of the main features of a microcontroller
• Choice and sizing of an embedded programming solution in relation to a given need
• C programming of a Raspberry Pi board
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• Optimization

  • Linear optimization
  • Non-linear optimization (gradient descent, Lagrange multipliers)
  • Applying optimisation 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 microcontroler
  • Choice and implementation of an embedded programming solution adapted to given design specifications
  • C Programming on a Raspberry Pi

   

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

Micro-robotics: Microrobotics concerns the design, modeling and control of miniaturized robotic systems to perform manipulation tasks on objects of size between 1μm and 1mm. The fields of application include all areas that require high precision (assembly of mechanical, electronic or optical microsystems, micro-surgery, etc.). At these dimensional scales, robots cannot be made by simple homothetic miniaturization of conventional robots. New robot concepts and actuation principles are to be used. This course is an introduction to microrobotics and introduces the essential concepts of scale, microworld physics, deformable and flexible robotics and micro-actuators.

Surgical Robotics: The objective of this course is to give students an introduction to the field of surgical robotics. The aim is to be able to understand the needs expressed by clinicians and to show through a few examples the approach that has made it possible to design and build robots used for surgical procedures. Some design elements as well as some control architectures will be mentioned, insisting on the need to guarantee the safety of the patient and the medical team.

Underwater and flying robots: Mobile robotics dedicated to aerial and underwater environments is based on specificities that will be introduced in this course. Current solutions and problems that are still open will be presented. Issues related to modeling and nonlinear controls applied to under/iso/over-actuated systems will be addressed.

Humanoid robotics: This will present the advanced geometric modeling and kinematic methods for tree robotic structures such as humanoid robots. Basic notions will also be presented on the center of mass, the center of pressure, the ZMP, static stability, dynamic stability. 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 course will focus on the kinematic control of highly redundant structures (underdetermined system of type Ax=b) by the use of methods based on optimization techniques (LP, QP) under constraints as well as on hierarchical control based on techniques of projection in zero space or task hierarchy based on hierarchies of QP or LP.

Parallel Cable Robots: This course introduces the principle of Parallel Cable Robots (CPRs) followed by a state-of-the-art including application examples, CPR demonstrators and commercial PCRs. Geometric, kinematic and dynamic models of the RPCs are then developed. Based on these templates, the different types of RPCs, several definitions of their workspace, the main concepts useful for their design as well as simple methods of ordering will finally be presented.

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

Reliability and operational safety: This course focuses on the reliability of a robotic system, particularly in the operational phase. When a robot operates in a complex and partially unfamiliar environment, unforeseen events can occur that the system will have to react to if it wants to ensure its own safety and that of its environment. This course will introduce the basic notions of dependability, and present examples of reliability mechanisms applied to mobile robotics.

Teleoperation: This part covers a brief introduction to the history of teleoperation development, modeling of teleoperation components, and their schematics. The criteria for evaluating performance in teleoperation are defined. Performance analysis and control design methods are also introduced. The course provides the applications of teleoperation in the field of surgical robotics as well as the open questions and remaining challenges to be solved.

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This teaching unit covers a set of specialities in robotics, ranging from micro to macro scales, including micro manipulation, surgical, sub-marine, flying, humanoid and cable-driven robots passing through teleoperation, virtual and augmented reality as well as operational safety. The content of each sub-unit is detailed hereafter. Projects on the mentioned topics will be carried out to deepen the thought basics using both simulation softwares and real robots.

Micro-robotics: Micro-robotics concerns the design, modelling and control of miniaturized robotic systems able to perform 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 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.

Sub-marine 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 modelling 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 modelling methods for humanoid robots. Basics on the centre of mass (COM), the centre of pressure, the zero-moment point (ZMP), static stability and dynamic stability are addressed. A study on biped 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 is focused on the differential kinematic control of very redundant structures (underdetermined system of type Ax = b) by the use of methods based on optimization techniques (LP, QP) under constraints as well as on the hierarchical control based on the projection in the null space or tasks hierarchy 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 in 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 a graphical one, 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 when creating an AR/VR system. We will address the current 3D technologies (OpenGL, Vulkan), the devices available, the basics of physical engines, and the localisation and vision techniques used to track the user movements in real time and compute his 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 of the development history, the typical structures of teleoperation schemes and the modelling of teleoperation components. Based on the system modelling, 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 field of robotic surgery as well as the open issues and challenges existing in practical implementation.

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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.

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This teaching unit covers the techniques and tools required for kinematic and dynamic modeling and control for handling robotics. Teaching is structured around the following four axes:

1) Robot manipulator modeling: homogeneous transformations, direct and inverse geometric models, kinematic modeling, singularity studies

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

3) Joint and operational control in free space

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

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

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

1) Modelling of robot manipulators: homogeneous transformations, direct and inverse kinematic models, differential kinematic modelling, 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 treated in supervised works and practices 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 scientific skills, autonomy and adaptability of the student.

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Internship of 5 to 6 months to be carried out in a research laboratory or within a company, highlighting the scientific skills, autonomy and adaptability of the student.

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Preparation for professional integration.

Teaching provided by a senior HR consultant, former HR manager of large groups, who uses her rich experience in recruitment to serve her teaching.

Pedagogical approach promoting the sharing of experience and the response to students' situations and questions.

General contributions on recruitment from A to Z, how to be more efficient in your search, vision on the approaches of final recruiters, recruitment agencies, service companies.

Simulations of recruitment interviews in small groups with personalized debriefing orchestrated by the teacher.

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TD courses in English for Specialization and English for Communication and which aims at professional autonomy in the English language.

Strengthen and consolidate the achievements of Master 1.

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