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To optimize your chances of success in the Robotics Software Engineer Nanodegree program, we’ve created a list of prerequisites and recommendations to prepare you for the program curriculum.See detailed requirements.
Learn the essential elements of robotics, meet your instructors, and get familiar with the tools that will help you succeed in this program.
Learn how to simulate your first robotic environment with Gazebo, the most common simulation engine used by Roboticists around the world.Build My World
Discover how ROS provides a flexible and unified software environment for developing robots in a modular and reusable manner. Learn how to manage existing ROS packages within a project, and how to write ROS Nodes of your own in C++.Go Chase It!
Learn how Gaussian filters can be used to estimate noisy sensor readings, and how to estimate a robot’s position relative to a known map of the environment with Monte Carlo Localization (MCL).Where Am I?
Learn how to create a Simultaneous Localization and Mapping (SLAM) implementation with ROS packages and C++. You’ll achieve this by combining mapping algorithms with what you learned in the localization lessons.Map My World
Learn different Path Planning and Navigation algorithms. Then, combine SLAM and Navigation into a home service robot that can autonomously transport objects in your home!Home Service Robot
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As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.
David Silver leads the School of Autonomous Systems at Udacity. 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.
Karim started his early career as a Mechanical Engineer. He earned his M.S. in Mechatronics and Robotics Engineering from NYU. His specialties include Kinematics, Control, and Electronics.
Julia is an experienced educator and robotics specialist. Her previous work experiences include teaching Mechatronics Engineering at the University of Waterloo and designing electric vehicles for underground mines.
Numbers don't lie. See what difference it makes in career searches.*
Career-seeking and job-ready graduates found a new, better job within six months of graduation.
Average salary increase for graduates who found a new, better job within six months of graduation.
Demand for software engineers with advanced robotics skills far exceeds the current supply of qualified talent. This makes this an ideal time to pursue career advancement in this field, and this program represents a great opportunity to develop and practice core robotics skills such as C++, ROS, and probabilistic robotics algorithms such as Localization, Mapping, SLAM, Path Planning and Navigation.
You will graduate from this Nanodegree program having completed five hands-on robotics projects in the Gazebo simulator; these will serve as portfolio pieces demonstrating your acquired skills to hiring managers and recruiters. These skills will help you pursue and advance a career in the robotics field.
As a Robotics Software Engineer, you'll be equipped to bring value to a wide array of industries and be eligible for many roles.
Your opportunities might include:
The Robotics Software Engineer Nanodegree program is designed for those looking to pursue or advance a career in the robotics field. In this program, you will learn and practice the core robotics skills that employers have told us serve as the foundation for the work robotics engineers do: C++, ROS, Gazebo, and robotics algorithms such as Localization, Mapping, SLAM, Path Planning, and Navigation amongst others.
If you want to work in a field where you get to see your solutions come to life, and solve some of the world’s most difficult and exciting problems, the Robotics Software Engineer Nanodegree program is right for you.
The Robotics Software Engineer Nanodegree program focuses on teaching the core robotics skills needed for a successful robotics software engineering career. The program focuses on Localization, Mapping, SLAM, Path Planning, and Navigation. These are taught using C++ and the Robot Operating System (ROS) framework.
The Self-Driving Car Engineer Nanodegree program focuses entirely on a specialized application of robotics—it uses robotics concepts and applies them to a self-driving car. If your primary interest is in the application of robotics, machine learning, and artificial intelligence to autonomous vehicles, then this is the program for you. However, if you want to learn and practice core robotics skills in C++ and ROS, with an emphasis on robotics algorithms, then the Robotics Software Engineer Nanodegree program is your best option.
There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.
To succeed in this Nanodegree program, you should have experience with the following:
We created the Intro to Self-Driving Cars Nanodegree program to help prepare prospective students for more advanced programs. That introductory program will teach you the skills you need to be successful in the Robotics Software Engineer Nanodegree program, including C++, linear algebra, calculus, and statistics.
The Robotics Software Engineer Nanodegree program is comprised of content and curriculum to support five (5) 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.
Please see the Udacity Nanodegree program FAQs for policies on enrollment in our programs.
The core of this Nanodegree program focuses on robotics applications in software. You will learn and practice robotics skills using the Gazebo simulator.
For this Nanodegree program, you will use the Robot Operating System (ROS) and Gazebo. You will code primarily with C++. These platforms and languages are freely available.
We will provide you with a GPU-enabled Linux Workspace that runs in your browser, and an internet connection is required. Optionally, you can install the Linux image on a Virtual Machine.