M2 - Robotics

Advanced Programming

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

Artificial Intelligence

• Machine Learning: State of the Art, Challenges, 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

• Development of a Logic Simulator for Microelectronics
• Implementation (in C++) and integration (in ROS) of robotics algorithms
• Introduction to AI-Based Classification Tools
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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 of 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 and Von Neumann Architectures
• Understanding and implementing the main features of a microcontroller
• Selecting and sizing an embedded programming solution based on a specific need
• Programming a Raspberry Pi Board in C
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• Optimization

  • Linear Optimization
  • Nonlinear optimization (gradient descent, Lagrange multipliers)
  • Applying Optimization in Robotics (Optimal Control Based on Quadratic Programming Under Linear Constraints)

  Embedded Systems

  • Harvard & Von Neumann Architectures
  • Understanding and Implementation of the Main Functions of a Microcontroller
  • Selection and Implementation of an Embedded Programming Solution Tailored to Specific Design Specifications
  • C Programming on a Raspberry Pi

   

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This course covers a range of topics in robotics, from the micro to the macro scale, including micro-manipulators, cable-driven robots, surgical robots, underwater robots, flying robots, and 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 aforementioned topics will be conducted to reinforce the fundamentals taught, using both simulation software and real robots.

Microrobotics: Microrobotics involves the design, modeling, and control of miniaturized robotic systems capable of performing manipulation tasks on objects ranging in size from 1 µm to 1 mm. Application areas include all fields that require high precision (assembly of mechanical, electronic, or optical microsystems; microsurgery; etc.). At these scales, robots cannot be created simply by homothetic miniaturization of conventional robots. New robot concepts and new actuation principles must be employed. This course is an introduction to microrobotics and presents the essential concepts, including: the scale effect, the physics of the microworld, deformable and soft robotics, and microactuators.

Surgical Robotics: The objective of this course is to provide students with an introduction to the field of surgical robotics. The goal is to enable students to understand the needs expressed by clinicians and to illustrate, through several examples, the process that led to the design and development of robots used in surgical procedures. Several design elements and control architectures will be discussed, with an emphasis on the need to ensure the safety of both the patient and the medical team.

Underwater and Flying Robots: Mobile robotics designed for aerial and underwater environments relies on specific characteristics that will be introduced in this course. Current solutions and outstanding challenges will be discussed. Topics related to modeling and nonlinear control applied to under-, iso-, and over-actuated systems will be covered.

Humanoid Robotics: This course will cover advanced geometric and kinematic modeling methods for tree-like robotic structures, such as humanoid robots. Basic concepts will also be covered, including the center of mass, the center of pressure, the ZMP, static stability, and dynamic stability. A study on bipedal walking control will be conducted, covering 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 (underdetermined systems of the Ax=b type) using methods based on constrained optimization techniques (LP, QP) as well as hierarchical control based on projection into null space or task hierarchies based on QP or LP hierarchies.

Parallel Cable Robots: This course introduces the principles of Parallel Cable Robots (PCR), followed by a review of the state of the art, including application examples, PCR demonstrators, and commercial PCRs. The geometric, kinematic, and dynamic models of PRCs are then developed. Based on these models, the various types of PRCs, 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) technologies involve the interactive simulation of a 3D environment in which the user is immersed. This simulation is generally primarily visual in nature, though it may also include other perceptual information through various sensory modalities: spatialized sound, haptic or force feedback, somatosensory input, etc. This course is an introduction to the various techniques used in VR/AR systems: we will cover the main 3D rendering libraries (OpenGL, Vulkan), devices currently available on the market, the basics of physics engines, and the techniques used to track the user’s position 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, the modeling of teleoperation components, and their 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 course covers a range of specialties in robotics, spanning from the micro to the macro scale, including micro-manipulation, surgical, underwater, 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 reinforce the fundamental concepts 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 1 µm to 1 mm. Application areas include all fields requiring high precision (assembly of mechanical, electronic, or optical microsystems; microsurgery; etc.). At these scales, robots cannot be fabricated simply by homothetic miniaturization of conventional robots. New robot concepts and new actuation principles must be employed. This course serves as an introduction to micro-robotics and covers the essential concepts of scale effects, the physics of the micro-world, deformable and flexible robotics, and micro-actuators.

Surgical Robotics: The objective of this subunit is to provide students with an introduction to the field of surgical robotics. It focuses on helping students understand the needs expressed by clinicians and, through a few examples, illustrate the process that led to the development of robots used in surgical procedures. Certain design elements and control architectures will be discussed, with an emphasis on ensuring the safety of the patient and the medical team.

Underwater and flying robots: The specific characteristics of underwater and aerial robotics will be presented. Current solutions and outstanding issues will be discussed. The basic elements required for control design for this type of vehicle—from modeling to nonlinear control techniques—will be addressed, depending on whether the systems are under-, iso-, or over-actuated.

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

Cable-driven parallel robots: This section presents the basic principle of cable-driven parallel robots (CDPRs), followed by a review of the current state of the art, including application examples, CDPR demonstrators, and commercial CDPRs. Geometric, kinematic, and dynamic models of CDPRs are then developed. Based on these models, the different types of CDPRs, various definitions of their workspace, the main concepts relevant to their design, and simple control strategies will be presented.

Virtual and Augmented Reality: AR and VR involve providing the user with an interactive simulation of a 3D world, where physics can be simulated and enhanced with additional data visualization. This simulation is typically graphical in nature, but it can also incorporate other perceptual information across multiple sensory modalities: spatialized sound, haptics, somatosensory feedback, etc. This course serves as an introduction to the various techniques involved in creating an AR/VR system. We will cover current 3D technologies (OpenGL, Vulkan), available devices, the basics of physics engines, and the localization and vision techniques used to track the user’s movements in real time and compute their point of view.

Operational Safety of Robots: This section focuses on the reliability of robotic systems, primarily during the operational phase. When a robot moves in a complex and partially unknown environment, unforeseen events can occur. The system must respond to these events to ensure its own safety and that of its environment. This course will introduce the basic concepts of dependability and present examples of safety mechanisms applied to mobile robotics.

Teleoperation: This section provides a brief introduction to the history of development, the typical structures of teleoperation systems, and the modeling of teleoperation components. Based on system modeling, the criteria for evaluating teleoperation performance are defined, and methods for performance analysis and control design are introduced accordingly. The course also covers the applications of teleoperation in the field of robotic surgery, as well as the outstanding issues and challenges involved in practical implementation.

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

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

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This course covers the techniques and tools required for kinematic and dynamic modeling and control in manipulation robotics. The course content is structured around the following four areas:

1) Modeling of robotic manipulators: 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, algorithms for calculating dynamics

3) Articular and operational control in free space

4) Motion control in confined 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 hands-on exercises using MATLAB and V-REP on various manipulation robots (6- and 7-axis robots) as well as on a real humanoid robot named “Poppy.” 

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This course covers the techniques and tools necessary for kinematic and dynamic modeling and the control of robot manipulators. The lectures are organized around the following four topics:

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 computing 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, movement generation, application examples.

Several examples of all these techniques will be covered in supervised lab sessions and practical exercises using MATLAB and V-REP tools on various manipulation robots (6- and 7-axis robots) as well as on a real humanoid robot named "Poppy."

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A project conducted in partnership with a research laboratory and/or a company, highlighting the student's scientific skills, independence, and adaptability.

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

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Preparation for entering the workforce.

The course is taught by a senior HR consultant, a former HR manager at major corporations, who draws on her extensive recruitment experience in her teaching.

A teaching approach that encourages the sharing of experiences and addresses students' situations and questions.

General insights on recruitment from A to Z, how to conduct a more effective job search, and perspectives on the approaches taken by end-hiring companies, recruitment firms, and staffing agencies.

Small-group mock job interviews with personalized debriefing led by the instructor.

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A tutorial course in specialized English and communicative English designed to foster professional autonomy in the English language.

To reinforce and consolidate the knowledge gained in the first year of the master's program.

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