Robotics -Learning

The module will cover the following:

• Link between transfer function and differential equation
• Representation and continuous state 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 the acquired knowledge on real examples (e.g. electric motors), programming in python (numpy and control libraries).

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This course completes a basic training in signal processing with a thorough 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 a first part (10h30 lecture, 6h lab), the course deals with the sampling and quantization aspects of continuous signals and the relation between digital signals and original continuous signals. We define the discrete Fourier transform of digital signals, its estimation and its use on real deterministic signals.

The second part of the course (9 hours lecture, 4.5 hours lab, 3 hours lab) is dedicated to random signals and how the properties of some random signals can be used either to reduce the random part of a signal whose deterministic part is to be privileged (filtering, increase of the signal-to-noise ratio, ...) or to improve the transmission of information or to identify complex linearized systems.

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

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This teaching unit, devoted to the basics of digital electronics, is structured in an original way around a technical project, carried out individually or in pairs, whose progress will follow the progression 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 can complete 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 power electronics structures required to supply an electronic system. The second part will deal with the current or voltage regulation of these structures. A third part will deal with the conversion functions necessary for the control of MCC and DC Brushless actuators.

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

Practical work will allow to observe the principle and the implementation of regulated systems for electronics and actuators. This UE could 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 hardware and software.

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

This module aims at bringing students to develop computer code in a volume corresponding to the scale of a complete software. The quantity of code associated naturally gives rise to a need to structure the code so that it remains viable, and the concepts associated with code structuring will therefore be addressed or reinforced.
The teaching is therefore organized for the most part around practical work and projects. The context concerns for a large part deep themes of EEA: signal processing (acquisition chain), instrument interfacing, and data transmission by internet on embedded Linux platform. The theme of event-based programming through the development of graphical interfaces will also be addressed. The supporting languages 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 synthesis.

- Robust synthesis and hazard 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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Specialized English and English for Communication courses aimed at professional autonomy in the English language.

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Project in partnership with a research laboratory and/or a company, emphasizing the scientific skills, autonomy and adaptabilitý of the student.

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The internship or end-of-study project should emphasize the student's scientific skills, autonomy, and adaptabilitý :

• Internship of 2 to 3 months (maximum 5 months) to be carried out in a research laboratory or in a company;
• or 3-month end-of-study 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 in line with an internship or job advertisement or in relation to the activities of a professional structure in the case of an unsolicited application; to write CVs and cover letters; to get to know themselves better in terms of personality; to use new technologies (social networks and job boards) and to orient their research in line with their professional project Finally, to know how to prepare 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 so, they must know the objectives and characteristics of the project, the plan to be applied, the different stages of realization as well as the rules of presentation. Then, to present their project orally, students must know and be able to apply the general structure of the presentation; define appropriate and relevant visual aids; respect the rules of oral expression in order to express themselves correctly and professionally (vocabulary, syntax, etc.); adopt behaviors that energize the speech and enable the audience to be hooked.

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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 to extract information from them. More generally, image processing aims to manipulate the underlying information contained in an image. If it has long been achieved through electronic circuits, image processing is nowadays almost exclusively done digitally, ie via algorithms programmed generally with an imperative language (C, C++, Java, Python, ...).

This course aims to provide a solid foundation in image processing. It covers image formation and acquisition, color transformations, morphological operations, geometric transformations, compression, frequency transformations, recognition and matching techniques, ... and an introduction to deep learning methods. The courses are complemented by support videos.

The teaching unit is mainly composed of 11 didactic courses dealing with the basics in the main fields of image processing and 3 practical work sessions whose subjects are to be chosen among 6 proposals. The students can choose to carry out the work on images that 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, types of robots, serial and parallel mechanisms, applications
• Components (sensors and actuators)
• Generation of trajectories (in the articular and operational spaces)
• Geometric models direct/inverse, Kinematic model direct/inverse
• Kinematic control and singularities
• Problems and applications in mobile robotics
• Non-autonomous models: unicycle, bicycle, car
• Sensors and odometry
• Localization by rangefinder and data fusion (Kalman filter)
• Mapping (homogeneous transformations and ICP)
• Navigation (pose control, path following)

Practical work: implementation of the acquired knowledge on a real robot (either a manipulator arm or a robot with wheels), 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, problems, 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++) 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
• Non-linear optimization (gradient method, optimal step gradient, Lagrange multipliers)
• Optimization applied to robotics (optimal control based on quadratic programming under linear constraints)

On-board system

• Harvard & Von Neumann architectures
• Knowledge and implementation of the main features of a microcontroller
• Choice and sizing of 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 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 topics, from micro to macro scale, including micro manipulators, cabled robots, surgical robots, underwater robots, flying robots, humanoid robots, teleoperation, virtual and augmented reality, and operational safety. The content of each theme is detailed below. Mini-projects on the above-mentioned topics will be conducted to deepen the basics taught using both simulation software and real robots.

Micro-robotics: Micro-robotics concerns the design, modeling and control of miniaturized robotic systems that can perform manipulation tasks on objects of sizes between 1µm and 1mm. The fields of application include all areas that require high precision (assembly of mechanical, electronic or optical microsystems, microsurgery, etc.). At these dimensional scales, robots cannot be realized by simple homothetic miniaturization of conventional robots. New concepts of robots and new principles of actuation must be used. This course is an introduction to microrobotics and presents the essential concepts of scaling, microworld physics, 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 be able to understand the needs expressed by the clinicians and to show through some examples the approach which allowed the design and the realization of robots used for surgical acts. Some design elements as well as some control architectures will be evoked by insisting on the necessity to guarantee the safety of the patient and the medical team.

Underwater and flying robots: Mobile robotics dedicated to air and underwater environments rely on specificities that will be introduced in this course. Current solutions and open problems will be presented. Issues related to modeling and non-linear control applied to under/iso/overactuated systems will be addressed.

Humanoid Robotics: This course will present advanced geometric and kinematic modeling methods for tree-like robotic structures such as humanoid robots. Basic notions will also be presented on the center of mass, the center of pressure, the ZMP, the static stability, the dynamic stability. A study on bipedal gait control will be performed including gait models, trajectory generation and ZMP/COM control as well as dynamic robot stabilization. The second part of the course will focus on the kinematic control of highly redundant structures (system under Ax=b) by using methods based on optimization techniques (LP, QP) under constraints as well as on hierarchical control based on techniques of projection in null space or task hierarchy based on hierarchies of QP or LP

Parallel Cable Robots: This course presents the principle of Parallel Cable Robots (PCR) followed by a state of the art including application examples, PCR demonstrators and commercial PCRs. Geometric, kinematic and dynamic models of RPCs are then developed. Based on these models, the different types of RPCs, several definitions of their working space, the main concepts useful for their design as well as simple control methods 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 visual in nature, but 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 cover the main 3D synthesis libraries (OpenGL, Vulkan), the peripherals available on the market, the basics of physics engines as well as the techniques used to localize the user and estimate in real time his point of view.

Reliability and operational safety: this course focuses on the reliability of a robotic system, especially in the operational phase. When a robot evolves in a complex and partially unknown environment, unexpected events may occur to which the system will have to react if it wants to guarantee 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 section covers a brief introduction to the history of teleoperation development, modeling of teleoperation components and their schematics. Teleoperation performance evaluation criteria are defined. Performance analysis and control design methods are also introduced. The course provides 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 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 software 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 center of mass (COM), the center 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 domain of robotic surgery as well as the open issues and challenges existing in practical implementation.

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This teaching unit aims to study and implement perception systems for mobile robots, manipulators, humanoids, ... The teaching is based on proprioceptive and exteroceptive perception systems with an important focus on vision systems. In the lectures, the general principles of perception are presented as well as the functioning of the most commonly used sensors (cameras, projectors, distance, motion and position sensors, ...). A series of practical works accompany this teaching, taking 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 necessary for kinematic and dynamic modeling and control for robotic manipulation. The teachings are structured around the following four axes:

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

2) Introduction to the dynamics of robotic manipulators: Euler-Lagrange formalism, Newton-Euler formalism, algorithmic for the calculation of 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 treated in tutorials and practical work 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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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, emphasizing the scientific skills, autonomy and adaptability of the student.

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5 to 6 month internship in a research laboratory or in a company, emphasizing the scientific skills, autonomy and adaptability of the student.

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Preparation for professional integration.

The course is taught by a senior HR consultant and former HRM of large groups, who brings to the teaching her rich experience in recruitment.

A pedagogical approach that favors the sharing of experience and the response to students' situations and questions.

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

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

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Specialized English and English for Communication courses aimed at professional autonomy in the English language.

Reinforce and consolidate the knowledge acquired in Master 1.

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