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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)
FREE
This course includes
Hours of videos
777 years, 8 months
Units & Quizzes
28
Unlimited Lifetime access
Access on mobile app
Certificate of Completion
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 Currilcum
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- Lecture 1: Introduction to VNAV Unlimited
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- Lecture 2 and 3: 3D Geometric Basics Unlimited
- Lecture 4 and 5: Lie Groups and Distances Unlimited
- Lecture 6: Quadrotor Dynamics Unlimited
- Lecture 7: Quadrotor Control Unlimited
- Lecture 11: Image Formation Unlimited
- Lecture 12 and 13: Feature Detection and Tracking Unlimited
- Lecture 17: Intro to Nonlinear Least Squares Unlimited
- Lecture 18: LM and Optimization on Manifold Unlimited
- Lecture 19: Optimization on Manifold Unlimited
- Lecture 23: SLAM I — Formulations and Sparsity Unlimited
- Lecture 24: SLAM II — Factor Graphs and Marginalization Unlimited
- Lecture 28: Incremental SLAM Solvers Unlimited