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Last updated:

September 22, 2022

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

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 Curriculum

    • Lecture 1: Introduction to VNAV Unlimited
    • 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 8: Trajectory Optimization 1 Unlimited
    • Trajectory Optimization 2 Unlimited
    • Lecture 10: Trajectory Optimization 3 Unlimited
    • Lecture 11: Image Formation Unlimited
    • Lecture 12 and 13: Feature Detection and Tracking Unlimited
    • Lecture 14: 2-view Geometry Unlimited
    • Lecture 15: RANSAC and 3D-3D Correspondences Unlimited
    • Lecture 16: ML and MAP Estimation Unlimited
    • Lecture 17: Intro to Nonlinear Least Squares Unlimited
    • Lecture 18: LM and Optimization on Manifold Unlimited
    • Lecture 19: Optimization on Manifold Unlimited
    • Lecture 20: Visual and Visual-Inertial Odometry Unlimited
    • Lecture 21: Place Recognition Unlimited
    • Lecture 22: Bag of Words and Object Detection Unlimited
    • Lecture 23: SLAM I — Formulations and Sparsity Unlimited
    • Lecture 24: SLAM II — Factor Graphs and Marginalization Unlimited
    • Lecture 25: Dense 3D Reconstruction Unlimited
    • Lecture 26: Beyond Cameras Unlimited
    • Lecture 27: Open Problems Unlimited
    • Lecture 28: Incremental SLAM Solvers Unlimited
    • Lecture 30: Outlier-Robust Perception 1 Unlimited
    • Lecture 31: Outlier-Robust Perception 2 Unlimited
    • Lecture 32: Outlier-Robust Perception 3 Unlimited

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Massachusetts Institute of Technology
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