This course covers the mathematical foundations and state-of-the-art implementations of algorithms for vision-based navigation of autonomous vehicles (e.g., mobile robots, self-driving cars, drones). It provides students with a rigorous but pragmatic overview of differential geometry and optimization on manifolds and knowledge of the fundamentals of 2-view and multi-view geometric vision for real-time motion estimation, calibration, localization, and mapping. The theoretical foundations are complemented with hands-on labs based on state-of-the-art mini racecar and drone platforms. It culminates in a critical review of recent advances in the field and a team project aimed at advancing the state of the art.
Visual Navigation for Autonomous Vehicles (VNAV)
Miscellaneous
Electronic Resource
English
British Library Online Contents | 2001
|Visual Navigation System for Autonomous Land Vehicles
NTIS | 1985
|European Patent Office | 2020
|European Patent Office | 2019
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