Visual Navigation for Autonomous Vehicles (VNAV)
16.485 · Aeronautics and Astronautics · Graduate · Fall 2020
Prof. Luca Carlone, Kasra Khosoussi, Markus Ryll, Golnaz Habibi, Vasileios Tzuomas, Rajat Talak
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 com…
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Attribution
Prof. Luca Carlone, Kasra Khosoussi, Markus Ryll, Golnaz Habibi, Vasileios Tzuomas, Rajat Talak. 16.485 Visual Navigation for Autonomous Vehicles (VNAV). Fall 2020. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
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