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Object Tracking and Localization

Course

Learn how to locate an object and track it over time. These techniques are used in a variety of moving systems, such as self-driving car navigation and drone flight.

Learn how to locate an object and track it over time. These techniques are used in a variety of moving systems, such as self-driving car navigation and drone flight.

Advanced

4 weeks

Real-world Projects

Completion Certificate

Last Updated January 3, 2024

Skills you'll learn:
Object tracking • Slam • Object localization • Feature matching
Prerequisites:
Basic probability • Object-oriented Python • Basic arithmetic

Course Lessons

Lesson 1

Introduction to Motion

This lesson introduces a way to represent motion mathematically, outlines what you'll learn in this section, and introduces optical flow.

Lesson 2

Robot Localization

Learn to implement a Bayesian filter to locate a robot in space and represent uncertainty in robot motion.

Lesson 3

Mini-project: 2D Histogram Filter

Write sense and move functions (and debug) a 2D histogram filter!

Lesson 4

Introduction to Kalman Filters

Learn the intuition behind the Kalman Filter, a vehicle tracking algorithm, and implement a one-dimensional tracker of your own.

Lesson 5

Representing State and Motion

Learn about representing the state of a car in a vector that can be modified using linear algebra.

Lesson 6

Matrices and Transformation of State

Linear Algebra is a rich branch of math and a useful tool. In this lesson you'll learn about the matrix operations that underly multidimensional Kalman Filters.

Lesson 7

Simultaneous Localization and Mapping

Learn how to implement SLAM: simultaneously localize an autonomous vehicle and create a map of landmarks in an environment.

Lesson 8

Optional: Vehicle Motion and Calculus

Review the basics of calculus and see how to derive the x and y components of a self-driving car's motion from sensor measurements and other data.

Lesson 9 • Project

Project: Landmark Detection & Tracking

Implement SLAM, a robust method for tracking an object over time and mapping out its surrounding environment, using elements of probability, motion models, and linear algebra.

Taught By The Best

Photo of Sebastian Thrun

Sebastian Thrun

Founder and Executive Chairman, Udacity

As the Founder and Chairman of Udacity, Sebastian's mission is to democratize education by providing lifelong learning to millions of students worldwide. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.

Photo of Andy Brown

Andy Brown

Curriculum Lead

Andy has a bachelor's degree in physics from MIT, and taught himself to program after college (mostly with Udacity courses). He has been helping Udacity make incredible educational experiences since the early days of the company.

Photo of Cezanne Camacho

Cezanne Camacho

Curriculum Lead

Cezanne is an expert in computer vision with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she's applied computer vision and deep learning to medical diagnostic applications.

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Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

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Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.

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