Connected and Autonomous Vehicles: Sensors and Sensor Fusion
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The first part of the course covers the operational principles of the state-of-the-art sensors used in CAVs, presenting useful case studies and real-world applications. The second part of the course deals with estimation and tracking, presenting the main types of sensor fusion architectures and the principal algorithms used for sensor fusion, such as the Kalman Filter, the Extended Kalman Filter and the Unscented Kalman Filter.
A generical tech savvy audience should be able to follow the first 6 units easily. The last 2 units require more advanced statistical knowledge.
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Level | Technical |
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Partner Details | The Transport Systems Catapult (Connected Places Catapult ) is the UK’s technology and innovation centre for Intelligent Mobility. It is a neutral, not-for-profit, Technology and Innovation company which aims to make the UK a world leader in Transport Innovation.. Dr. Luca Zanotti Fragonara: Lecturer at Cranfield University, member of the Centre for Autonomous and Cyber-Physical Systems and of the Aerospace Integration Research Centre. Dr. Luca is involved in several projects linked to: artificial intelligence for autonomous systems (HumanDrive), connectivity of autonomous systems (CORAM), autonomous inspections for non-destructive evaluation of aircraft composite materials (H2020 CompInnova), analytical and experimental studies of vibration in vacuum for structural health monitoring, system identification, experimental modal analysis of helicopter blades and wings (BLADESENSE). He is the author of more than 30 peer-reviewed journal articles and 30 international conference proceedings.. |
Type | Course |
• Understand and classify the types of sensors used in autonomous cars
• Understand the main types of sensor fusion architectures
• Understand real problems and be able to apply filter algorithms for linear and non-linear systems