M2 - Robotics

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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