Teaching

Intelligent Robotics (MSc in EIC @ FEUP)

This course focused on introducing fundamental concepts in robotics, with a strong emphasis on mobile robotics and intelligent autonomous systems. It covered key topics such as robotic architectures, sensors and actuators, localization and mapping, motion planning and navigation, learning methods applied to robotics, and human–robot interaction. Moreover, the practical component of the course consisted of two group projects. The first project was common to all groups and aimed to introduce students to robotics software frameworks and algorithmic reasoning through the exploration of the ROS framework and the Webots simulator, used to control a reactive two-wheel mobile robot based on sensor data. The second project was proposed by each group and focused on the exploration of a specific component of an intelligent robotic system, such as mapping, localization, path planning, or path control, using either heuristic approaches or learning-based methods (e.g., reinforcement learning). In this project, students were also allowed to justify the use of alternative simulators (e.g., Webots, Gazebo, Isaac Sim) and communication mechanisms (e.g., ROS, ZMQ). In the final project, students also had the opportunity to work with real robots, using one of the following platforms: Waveshare UGV Rover, Duckiebot, or TurtleBot 3 Waffle.

My participation in this course was mainly focused on project supervision during practical classes, supporting students in the design, implementation, and validation of their robotic systems. Additionally, I developed a digital twin of the Waveshare UGV Rover in the Webots simulator and prepared supporting tutorials using ROS 2 and Webots, including practical examples of robotic algorithms such as Adaptive Monte Carlo Localization (AMCL).

Topics in Intelligent Robotics (MSc in IA @ FEUP)

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Introduction to Intelligent Robotics (BSc in IACD @ FCUP)

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