Descriptif
This course provides a comprehensive introduction to the fundamental concepts and practical applications of mobile robotics. Students will gain a solid understanding of robot kinematics, locomotion, perception, and navigation, with a strong emphasis on hands-on experience using the Robot Operating System 2 (ROS2). The curriculum is designed to equip students with the necessary skills to design, program, and integrate mobile robotic systems in various environments.
effectifs minimal / maximal:
10/50Diplôme(s) concerné(s)
Format des notes
Numérique sur 20Littérale/grade européenPour les étudiants du diplôme IA : Intelligence Artificielle multimodale et autonome
Vos modalités d'acquisition :
La note finale de cette unité d'enseignement rentre dans le calcul de la moyenne du bloc d'enseignement de rattachement
Conformément au règlement scolaire (art. 4.4.2, p. 8) : "Si l'étudiant obtient une note de BE inférieure à 10, il peut passer un examen de rattrapage pour toute IE de ce BE pour laquelle il a obtenu une note inférieure à 10".
- le rattrapage peut être demandé par l'étudiant si :
- Note initiale < 10
- Crédits ECTS acquis : 4 ECTS
Programme détaillé
- Lecture 1: Introduction (1h30, overview of mobile robotics, history, applications, and challenges)
- Practical work 1: ROS2 Installation (1h30, setting up the ROS2 environment on student machines)
- Lecture 2: Software for Robotics (1h30, robot software architectures and communication protocols)
- Practical work 2: ROS2 Beginner Level (1h30, hands-on with basic ROS2 commands and the turtlesim simulator)
- Lecture 3: System Integration (1h30, interfacing hardware and software, building and managing development workspaces)
- Practical work 3: ROS2 Intermediate Level (1h30, working with multiple nodes, custom messages, and launch files)
- Lecture 4: Locomotion (1h30, types of mobile robot locomotion including wheeled and legged)
- Practical work 4: Play with Gazebo (1h30, simulating a robot in Gazebo and commanding its movement)
- Lecture 5: Kinematics (1h30, forward kinematics of wheeled and legged robots)
- Practical work 5: tf2 & URDF (1h30, implementing tf2 for coordinate transformations and creating URDF models)
- Lecture 6: Perception (1h30, introduction to robot sensors such as lidar, camera, IMU and encoders)
- Practical work 6: Maze Solving (1h30, using sensor data to navigate and solve a simple maze)
- Lecture 7: SLAM (1h30, fundamentals of Simultaneous Localization and Mapping)
- Practical work 7: slam_toolbox (1h30, implementing and evaluating SLAM using slam_toolbox)
- Lecture 8: Exploration (1h30, strategies for autonomous robot exploration)
- Practical work 8: Frontier-based Exploration (1h30, developing and testing a frontier-based exploration system)
- Lecture 9: Planning (1h30, task and path planning algorithms)
- Practical work 9: Nav2 (1h30, configuring and using Nav2 planners and designing basic behavior trees)
- Lecture 10: Navigation (1h30, global and local navigation strategies, obstacle avoidance, and dynamic environments)
- Practical work 10: Nav2 (1h30, full navigation stack implementation with Nav2)
- Lecture 11: Multi-robot Systems (1h30, coordination, communication, and task allocation in multi-robot teams)
- Practical work 11: ROS2 Namespaces and DDS (1h30, implementing multi-robot communication and basic (formation) patrol)
- Lecture 12: Exam
- Lecture 13 - 18: Project
