The activity of the thesis, after identifying a particular application domain, will consist of the study, design, development, and test/validation of perception and sensor fusion algorithms useful for a contextual understanding of the environment, providing output information to be used as inputs for path planning algorithms and control of autonomous vehicles.
Internship main topic:
The architectures proposed for driver assistance systems (ADAS) and/or autonomous driving include a perception module dedicated to the estimation of contextual conditions such as the state of other agents (pedestrians and vehicles), horizontal and vertical road markings and road surface conditions. This information is usually deduced through the use of machine learning algorithms (e.g. computer vision) and sensor fusion using onboard sensors (cameras, lidar, radar) as input.
Candidate requirements/Course of study:
Computer Engineering, Electronics or Automation.