Visual Navigation for Autonomous Vehicles (VNAV)

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. It culminates in a critical review of recent advances in the field and a team project aimed at advancing the state of the art.

Duration: Not defined

Cost: Free

Language: English

Type: Self-Paced