MICRO-452: Basics of mobile roboticsThe course teaches the basics of autonomous mobile robots. Both hardware (energy, locomotion, sensors) and software (signal processing, control, localization, trajectory planning, high-level control)
MICRO-451: Applied and industrial roboticsThis course is a real contact with industrial robotic applications. Components and mechanisms are reminded. The fields of microtechnical assembly and packaging are treated. CTOs from established compa
MICRO-450: Basics of robotics for manipulationThis course introduces the basics of robotics for manipulation. The aspects concerning robot architectures (Serial , Parallel and Cartesian), sensors, kinematics and dynamic modelling and control are
MICRO-453: Robotics practicalsThe goal of this lab series is to practice the various theoretical frameworks acquired in the courses on a variety of robots, ranging from industrial robots to autonomous mobile robots, to robotic dev
CIVIL-459: Deep learning for autonomous vehiclesDeep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects,
MICRO-315: Embedded Systems and RoboticsCe cours aborde la programmation de systèmes embarqués: la cross-compilation, l'utilisation d'une FPU dans des microcontrôleurs, l'utilisation d'instructions DSP et les mécanismes à disposition dans l
CS-432: Computational motor controlThe course gives (1) a review of different types of numerical models of control of locomotion and movement in animals, from fish to humans, (2) a presentation of different techniques for designing mod
ENV-548: Sensor orientationDetermination of spatial orientation (i.e. position, velocity, attitude) via integration of inertial sensors with satellite positioning. Prerequisite for many applications related to remote sensing, e
EE-559: Deep learningThis course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.
COM-304: Communications projectThe course teaches the development of systems that solve real-world challenges in communications, signal processing, AI, and robotics. Students will work in teams, construct their ideas, and either pr
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approac
ENV-530: Sustainability roboticsThe goal of this course is to provide methods and tools of robotics in promoting sustainable development. The course is a balance between theoretical basics in robotics, associated case studies and pr
ENG-466: Distributed intelligent systemsThe goal of this course is to provide methods and tools for modeling distributed intelligent systems as well as designing and optimizing coordination strategies. The course is a well-balanced mixture
HUM-414: Law and technology IICe cours présente le cadre légal applicable à certaines problématiques dans des domaines à caractère technique, tels que le droit de la construction, le droit de l'informatique, la biotechnologie, la
