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Become a Sensor Fusion Engineer

Nanodegree Program

Learn to fuse lidar point clouds, radar signatures, and camera images using Kalman Filters to perceive the environment and detect and track vehicles and pedestrians over time.

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00Days08Hrs47Min36Sec

  • Estimated time
    4 Months

    At 10 hours/week

  • Enroll by
    February 8, 2023

    Get access to classroom immediately on enrollment

  • Prerequisites
    Intermediate C++, Calculus, and Probability
Built in collaboration with
  • Mercedes-Benz

What you will learn

  1. Sensor Fusion Engineer

    Estimated 4 Months

    Learn to detect obstacles in lidar point clouds through clustering and segmentation, apply thresholds and filters to radar data in order to accurately track objects, and augment your perception by projecting camera images into three dimensions and fusing these projections with other sensor data. Combine this sensor data with Kalman filters to perceive the world around a vehicle and track objects over time.

    Prerequisite knowledge

    You should have intermediate C++ knowledge, and be familiar with calculus, probability, and linear algebra.

    1. Lidar

      Process raw lidar data with filtering, segmentation, and clustering to detect other vehicles on the road.

    2. 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.

    3. Radar

      Analyze radar signatures to detect and track objects. Calculate velocity and orientation by correcting for radial velocity distortions, noise, and occlusions.

    4. Kalman Filters

      Fuse data from multiple sources using Kalman filters, and build extended and unscented Kalman filters for tracking nonlinear movement.

All our programs include:

  • Real-world projects from industry experts

    With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

  • Technical mentor support

    Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

  • Career services

    You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

  • Flexible learning program

    Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Program offerings

  • Class Content

    • Content Co-created with Mercedes-Benz
    • Real-world projects
    • Project reviews
    • Project feedback from experienced reviewers
  • Student services

    • Technical mentor support
    • Student community
  • Career services

    • 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.

  • Personalized feedback
  • Unlimited submissions and feedback loops
  • Practical tips and industry best practices
  • Additional suggested resources to improve
  • 1,400+

    project reviewers

  • 2.7M

    projects reviewed

  • 88/100

    reviewer rating

  • 1.1 hours

    avg project review turnaround time

Learn with the best.

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.

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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

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 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 FAQs for policies on enrollment in our programs.

Software and hardware: What do I need for this program?
  • 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

Get Started

Start your path towards a Sensor Fusion career today

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