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Uedu Open / Visual Navigation for Autonomous Vehicles (VNAV)
16.485

Visual Navigation for Autonomous Vehicles (VNAV)

Prof. Luca Carlone, Kasra Khosoussi, Markus Ryll, Golnaz Habibi, Vasileios Tzuomas, Rajat Talak | Fall 2020
Data Science, Analytics & Computer Technology AI Machine Learning Visualization Computer Science Engineering Aerospace Engineering Artificial Intelligence
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CC BY-NC-SA 4.0
課程簡介
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.
Course Information
SourceMIT 開放式課程
科系Aeronautics and Astronautics
LanguageEnglish
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