Intelligent Vehicles are robotic systems that perceive the driving environment to assist the driver in safe vehicle operation by providing pertinent information or by controlling directly the vehicle.
For autonomous navigation, localization is still an open problem. Global Navigation Satellite Systems (GNSS) provide global localization and need to be assisted by exteroceptive and proprioceptive sensors and map information to increase the performance particularly in terms of accuracy and integrity. I study methods and algorithms able to merge these sources of information and able to provide reliable confidence indicators.
Perception systems that use camera, lidars and radars need also deep improvements to enable drivable space characterization and scene understanding. I consider frameworks and methodologies able to handle uncertainties and partial knowledge in highly dynamic open conditions.
I am also interested in the definition and elaboration of enhanced digital maps able to support these different processes, being convinced that they will play a key role in these technologies.

• Mobile Robotics, Intelligent Vehicles
• Advanced Driver Assistance System,
• Perception, Obstacle Detection, Drivable Space
• Localization

1. GNSS (GPS, Galileo)
2. GIS and Navigable Maps
3. Map-matching
4. Integrity monitoring, Fault Detection, Identification, Adaptation

• Multisensor Fusion and State Observers

1. Bayesian (EKF, UKF, PF, IMM, etc.)
2. Set-membership (Set Inversion, Interval Analysis, CSP, BPF)
3. Belief Theory and Evidential Grids