Flying Car and Autonomous Flight Engineer

BY
Udacity

Embrace a career in drone robotics and flying cars by immersing in an exciting Nanodegree program by Udacity to explore flight software engineering skills.

Lavel

Expert

Mode

Online

Duration

86 Hours

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video Based

Course overview

A major technological revolution is brewing and the niche associated is that of autonomously propelled vehicles. The next 5 years will see the emergence of flying car engineers at the forefront of this industry. In this program, the students collaborate with the brightest minds of this arena with industry-leading tools and solve groundbreaking problems.

Typically, keeping 15 hours per week of commitment to this program will see you clear it in 4 months time. However, for candidates who would like to build on their fundamentals, there is a preparatory course to bring you up to speed. It is in the form of a Nanodegree program and goes by the name: Introduction to Self-Driving Cars. This program will enable beginners to get accustomed to the technical side of the subjects.

The Flying Car and Autonomous Flight Engineer Nanodegree program prepare the students with essential skills including Planning, Controlling, and Estimating. This is closely followed by writing code for aircraft readiness and can be applied to drones. Thus, if you have a keen interest in unravelling the exciting prospects of drones, flying cars, and smart transportation, this program will be a good fit for you.

The highlights

  • 4 months program
  • Commit just 15 hours per week
  • Technical Mentor Support
  • Real-life projects
  • Nanodegree program

Program offerings

  • Github review
  • Career services
  • Unlimited feedback loops
  • Flexible curriculum
  • Peer to peer learning
  • Interview preparation
  • Seasoned project reviewers
  • Dedicated technical support
  • Job search assistance
  • Job offers negotiation.

Course and certificate fees

The tuition fee for the Flying Car and Autonomous Flight Engineer Nanodegree program is summarized as follows:

Fees componentsAmount
All Access monthly
Rs. 20,500 /month
All Access bundle
Rs. 17,425 /month
Flying Car and Autonomous Flight Engineer
Rs. 78,131 /one-time payment


certificate availability

Yes

certificate providing authority

Udacity

Who it is for

This Nanodegree program is designed for new career entries as well as for those seeking to come abreast with the latest technological innovations in this space. This program will be most suitable for students with the following skills:

  • Significant programming experience in any language
  • Intermediary familiarity with Python and C++ coupled with a zeal to excel in them
  • Know-how of classes, memory allocation, and references in connection with both the above-mentioned programming languages
  • Introductory knowledge of linear algebra and calculus, including integrals and derivatives
  • Comfortable with Probability and other statistical measures such as Variance, Mean, and Standard Deviations
  • A clear understanding of elementary Physics, including knowledge of dynamics, torque, and kinematics
  • Decent spoken and written English

Eligibility criteria

Work experience

There is no work experience required for this program. This program is open for all.

Education

For optimum learning, it is recommended that the participants be well versed with any Object-Oriented programming language such as C++, and have a decent understanding of calculus, probabilities, and linear algebra.

Certification qualifying details

This Robotics Software Engineer program comprises 5 projects, all of which need to be cleared by the students. In order to graduate, the project submission will be evaluated closely by the expert panel and a decision will be made if it was cleared or not. If it isn’t cleared, thorough feedback is provided and the candidate will have to retake the project until he/she clears it.

What you will learn

Knowledge of engineering

Among its various advantages, this Nanodegree program will build on the following concepts:

  • The founding principles of flight history, challenges, and vehicles
  • Be adept with having a drone take-off and fly around with the requisite controls in place
  • The basics of aerial path planning in order to deal with complex environments including obstacles, erratic sensor outputs, and wind, to name a few
  • Master 2D problem statements, followed by experiential optimizations and subsequently grow it to work in three dimensions as well
  • Immerse in a project involving autonomous navigation of a drone through a dense urban environment
  • Deep dive into building a cascaded controller to enable low-level motor controls. This assists in a practical solution to traversing through a 3D path
  • Become confident of designing an Extended Kalman Filter, a.k.a. EKF, to predict the relative position of a drone
  • A clear understanding of sensor fusion and filtering
  • Lead the flight of a fixed-wing aircraft in simulation, on the background of the concepts learned so far

The syllabus

Course 1: Welcome to the Nanodegree Program

An Introduction to Your Nanodegree Program
  • Welcome! We're so glad you're here. Join us in learning a bit more about what to expect and ways to succeed.
Getting Help
  • You are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.

Course 2: Introduction to Autonomous Flight

Welcome!
  • In this lesson you'll meet your instructors and go over some of the logistical details of this Nanodegree program.
Autonomous Flight
  • In this lesson you'll get a high level overview of the concepts underlying autonomous flight and the physical components from which flying vehicles are made.
Drone Integration
  • Walkthrough the steps you need to take to get your code running on an actual drone! We'll show you the steps for the "Intel Aero", but a lot of what you'll learn applies to other drones as well.

Course 3: Planning

Planning as Search
  • Solving the planning problem really comes down performing search through a state space to find a path from a start state to a goal state and here you'll get a chance to do just that!
Flying Car Representation
  • Your vehicle has a physical size and orientation in the world and here you'll learn how to think about position and orientation as part of your planning solution.
From Grids to Graphs
  • Graphs are really just a way of describing how your search space is connected. Here you'll learn about the tradeoffs between grids and graphs and each can be used in your planning representation.
Moving into 3D
  • Here you'll make the leap from two dimensions to three dimensions and discover how you can use different representations of your search space to optimize your planning solution.
Real World Planning
  • In this lesson, you'll dive deep into some advanced concepts that are crucial to motion planning in the real world, where a consideration for physics and preparedness for the unexpected are crucial.

Course 4: Controls

Vehicle Dynamics
  • Learn how flying vehicles move in one and two dimensions by understanding how propellers create forces and moments which cause accelerations and rotations.
Introduction to Vehicle Control
  • Learn how to control a drone moving in one dimension using Proportional Integral Derivative (PID) Control.
Control Architecture
  • The controls problem becomes more difficult in two dimensions. Learn how to use a cascaded PID control architecture to control a flying vehicle that moves in two dimensions.
Full 3D Control
  • In this lesson you'll take everything you've learned so far about vehicle dynamics and control and put it together to control a quadrotor that moves in three dimensions.
Drone Integration
  • Walkthrough the steps you need to take to get a version of your controls project on a crazyflie!

Course 5: Estimation

Introduction to Estimation
  • Review basic probability and learn three approaches to state estimation for a stationary vehicle.
Introduction to Sensors
  • In this lesson you'll learn about the sensors a drone uses to localize itself in the world. You'll implement sensor models, analyze sources of error, and perform calibration of various sensors.
Extended Kalman Filters
  • In this lesson you'll learn how to estimate the state of a drone that's actually moving! You'll implement a Kalman Filter for a 1D drone and an Extended Kalman Filter for a non-linear 2D drone.
The 3D EKF and UKF
  • Take what you learned in the previous lesson and generalize to three dimensions. After learning about the 3D EKF you'll also learn another estimation algorithm called the Unscented Kalman Filter.
GPS Denied Navigation
  • How do you estimate vehicle state when you don't have GPS? In this lesson you'll learn about optical flow and particle filters as two approaches to solving this problem.

Course 6: Congratulations!

Congratulations!
  • Congratulations! You've completed all the requirements for this Nanodegree Program. Pat yourself on the back and share your accomplishment with the world!

Course 7: [Optional] Fixed Wing

Introduction to Fixed-Wing Flight
  • This lesson provides a brief introduction to Fixed Wing Vehicles, flying cars, and the components of typical fixed-wing aircraft.
Lift and Drag
  • Build mathematical models for lift and drag, the aerodynamic forces that make fixed wing flight possible (and difficult).
Longitudinal Model
  • Analyze both non-linear and linear models of a fixed-wing aircraft's motion in the x-z plane and use linear algebra to identify two oscillatory "modes" of motion.
Lateral-Directional Model
  • Understand the lateral-directional dynamics of fixed wing vehicles by looking at aircraft from above and behind.
Fixed-Wing Autopilot
  • Apply the concepts of PID control by implementing an autopilot for fixed wing flight.
Optional Project: Fixed-Wing Control
  • In this optional project you will control a simulated fixed-wing aircraft by implementing and tuning your own autopilot in Python.

Course 8: Autonomous Systems Interview Optional

Admission details

The enrolment steps for this program are outlined in the following section:

  • Enrolment
    The free trial can be availed from the home page of the course once you are ready to join. You will be prompted to sign in with Google or Facebook. If you are a new user, please sign-up instead by providing your First name, Last name, Email address, and set up a password.
  • Payment
    The 4-month access will be displayed to be available for purchase for a price of 1356USD.This will be charged to your card only after 7 days of the free trial is over. If you were to not graduate in the 4−month window, the fee for every month post the 4−month period is 399 USD, which will be automatically charged to your card unless cancelled or the course finished.
  • Learning
    The LMS access is granted within 5 minutes of the receipt of the payment.

Filling the form

The application form is fairly straightforward. The steps mentioned in the previous section will suffice.

Evaluation process

There are assignments built-in at the end of each module. These need to be cleared by the students in order to proceed to the next section.

How it helps

Industrial projects form a very close segment of this program. The modules presented have dedicated case studies that enable the students to apply the theory learnt to practice. Moreover, they have been designed and implemented by industry veterans, thereby creating immense value.

A successful program is one that has a robust feedback loop with the latest innovations in the market. The subjects of this Flying Car Nanodegree program have been designed with close partnerships with the leading companies in this space. Thus, the skills are perfectly in-line with what leading recruiters desire.

Instructors

Mr Nicholas Roy
Instructor
MIT University, Shil...

Ms Angela Schoellig
Assistant Professor
Freelancer

Mr Sebastian Thrun
President
Udacity

Mr Raffaello D Andrea

Mr Raffaello D Andrea
Instructor
Amazon.com Inc.

Mr Andy Brown
Lead
Udacity

Other Bachelors

Mr Sergei Lupashin

Mr Sergei Lupashin
Instructor
Freelancer

Mr Jake Lussier
Lead
Stanford

Ph.D

FAQs

What is the selection criteria?

This course is open for all irrespective of a specific background and thus does not have selection criteria. Please refer to the program deliverables to decide if it is suitable for you.

What is the start date of this program?

The course access is granted as soon as you pay for it by accessing the option on the program web-page.

What are the support functions for the Robotics Software Engineer program?

Our team of technical mentors will guide you for all your technical queries. They have a quick turnaround time.

What employment related support be provided?

There will be personalized feedback through 1 on 1 call. Moreover, your professional network will be boosted. Lastly, there will be sessions on fruitful negotiation of job offers.

What are some job profiles that are suitable after this course?

Positions pertain to autonomous mobility and aerial robotics. One may work as a Software and Controls Engineer, a GNC Engineer, and an Unmanned Aircraft Software Engineer.

Is there a preview available?

Yes, the preview is available on the program web-page.

What software do I need?

Typically, a laptop or a desktop with a reliable connection to the internet, such as that created by a hotspot or a dedicated broadband connection will be apt. The following are recommended: Quad-core i-5 processor, 4 GB RAM, 50 GB available Hard disk space,  stable internet connection.

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