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Estimated Time
4 Months
At 10 hours/week
Enroll by
September 29, 2021
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Prerequisites
Intermediate C++, Calculus, and Probability
Built in Collaboration With
Why take this Nanodegree program
The Sensor Fusion Engineer Nanodegree program will teach you the skills that most engineers learn on-the-job or in a graduate program - how to fuse data from multiple sensors to track non-linear motion and objects in the environment. Apply the skills you learn in this program to a career in robotics, self-driving cars, and much more.
Top Sensor Fusion Engineers in the US make an average of $149k!
What You Will Learn
Syllabus
Sensor Fusion Engineer
Related NanodegreesPrerequisite Knowledge
You should have intermediate C++ knowledge, and be familiar with calculus, probability, and linear algebra.
Lidar
Process raw lidar data with filtering, segmentation, and clustering to detect other vehicles on the road.
Radar
Analyze radar signatures to detect and track objects. Calculate velocity and orientation by correcting for radial velocity distortions, noise, and occlusions.
Cameras
Fuse camera images together with lidar point cloud data. You'll extract object features, classify objects, and project the camera image into three dimensions to fuse with lidar data.
Kalman Filters
Fuse data from multiple sources using Kalman filters, and build extended and unscented Kalman filters for tracking nonlinear movement.
Program OfferingsFull list of offerings included:
Enrollment Includes:
Class Content
Content Co-created with Mercedes-Benz
Real-world projects
Project reviews
Project feedback from experienced reviewers
Student Services
Technical mentor support
New
Student community
Improved
Career services
Resume support
Github review
Linkedin profile optimization
Succeed with Personalized Services
We provide services customized for your needs at every step of your learning journey to ensure your success!
Get timely feedback on your projects
Reviews By the numbers
1,400+ project reviewers
2.7M projects reviewed
88/100 reviewer rating
1.1 hours avg project review turnaround time
Reviewer Services
- Personalized feedback
- Unlimited submissions and feedback loops
- Practical tips and industry best practices
- Additional suggested resources to improve
Mentors available to answer your questions
Mentors by the numbers
1,400+ technical mentors
0.85 hours median response time
Mentorship Services
- Support for all your technical questions
- Questions answered quickly by our team of technical mentors
Learn With The Best
David Silver
Head of Curriculum
David Silver leads the Udacity Curriculum Team. Before Udacity, David was a research engineer on the autonomous vehicle team at Ford. He has an MBA from Stanford, and a BSE in Computer Science from Princeton.
Stephen Welch
Instructor
Stephen is a Content Developer at Udacity and has worked on the C++ and Self-Driving Car Engineer Nanodegree programs. He started teaching and coding while completing a Ph.D. in mathematics, and has been passionate about engineering education ever since.
Andreas Haja
Instructor
Andreas Haja is an engineer, educator and autonomous vehicle enthusiast with a PhD in computer science. Andreas now works as a professor, where he focuses on project-based learning in engineering. During his career with Volkswagen and Bosch he developed camera technology and autonomous vehicle prototypes.
Abdullah Zaidi
Instructor
Abdullah holds his M.S from the University of Maryland and is an expert in the field of Radio Frequency Design and Digital Signal processing. After spending several years at Qualcomm, Abdullah joined Metawave, where he now leads Radar development for autonomous driving.
Aaron Brown
Instructor
Aaron Brown has a background in electrical engineering, robotics and deep learning. Aaron has worked as a Content Developer and Simulation Engineer at Udacity focusing on developing projects for self-driving cars.
Become a Sensor Fusion Engineer
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Best Value
Learn
Combine and filter lidar, radar, and camera data to detect and track vehicles and pedestrians.
Average Time
On average, successful students take 4 months to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
- Career services
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Program Details
Program Overview - Why should I take this program?
Why should I enroll?
Sensor fusion engineering is one of the most important and exciting areas of robotics.
Sensors like cameras, radar, and lidar help self-driving cars, drones, and all types of robots perceive their environment. Analyzing and fusing this data is fundamental to building an autonomous system.
In this Nanodegree program, you will work with camera images, radar signatures, and lidar point clouds to detect and track vehicles and pedestrians. By graduation, you will have an impressive portfolio of projects to demonstrate your skills to employers.What jobs will this program prepare me for?
As a Sensor Fusion Engineer, you'll be equipped to bring value to a wide array of industries and be eligible for many roles.
Your opportunities might include roles such as an:- Imaging Engineer
- Sensor Fusion Engineer
- Perception Engineer
- Automated Vehicle Engineer
- Research Engineer
- Self-Driving Car Engineer
- Object Tracking Engineer
- Sensor Engineer
- System Integration Engineer
- Depth Engineer
How do I know this program is right for me?
If you’re interested in learning about lidar, radar, and camera data and how to fuse it together, this program is right for you.
Sensors and sensor data are used in a wide array of applications -- from cell phones to robots and self-driving cars -- giving you a wide array of fields you could enter or advance a career in after this program.
Enrollment and Admission
Do I need to apply? What are the admission criteria?
There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.What are the prerequisites for enrollment?
To optimize your chances of success in the Sensor Fusion Engineer Nanodegree program, we’ve created a list of prerequisites and recommendations to help prepare you for the program curriculum. You should have the following knowledge:- Advanced knowledge in any object-oriented - programming language, preferably C++
- Intermediate Probability
- Intermediate Calculus
- Intermediate Linear Algebra
- Basic Linux Command Lines
If I don't meet the requirements to enroll, what should I do?
For aspiring sensor fusion engineers who currently have a limited background in programming or math, we've created the Intro to Self-Driving Cars Nanodegree program to help you prepare. This program teaches C++, linear algebra, calculus, and statistics.
If you have a limited background in programming, we’ve created the C++ Nanodegree program to help you prepare for the coding in this program.
Tuition and Terms of Program
How is this program structured?
The Sensor Fusion Engineer Nanodegree program is comprised of content and curriculum to support four (4) projects. We estimate that students can complete the program in four (4) months, working 10 hours per week.
Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.How long is this Nanodegree program?
Access to this Nanodegree program runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.Can I switch my start date? Can I get a refund?
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.
Hardware and Software
What software and versions will I need for this program?
We have few requirements since you will be coding on our virtual environments (“Workspaces”) in the browser. This means you can complete all coursework within our platform, and do not need to install anything on your own machine.
If you choose to complete projects on your local machine, you should install:- C++ Version 11
- Point Cloud Library 1.7
Hardware Requirements:- None