Perception systems, Sensor Fusion, Lane keeping, Trajectory optimization and planning, Modelling and control of wheeled vehicles, Lateral dynamics control, Traction control, AI and ML for driving, Dynamic path planning, Vehicle-to-Everything (V2X) / to-Vehicle (V2V) communication, Safety-Critical Control
Navigate autonomously and using communication networks in smart cities or uncertain industrial environments involve high skills in control, perception, and reasoning at different levels.
The research on wheeled vehicles includes the use of Artificial Intelligence to support and improve autonomy solutions, develop architecture and algorithms, and embedded advanced control on microcontroller, vehicle systems modelling, simulation, and control from two/three/four-wheeled wheeled vehicles, furthermore, develop embedded solutions in real-time with high reliability and minimum hardware resources; face complex tasks as: lane keeping, navigating intersections, reacting to traffic lights, navigation based on localization data, SLAM, reacting to other traffic cars or pedestrians and so on.
