Self-Driving Fundamentals: Featuring Apollo

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Identify key parts of self-driving cars, utilize Apollo HD Map, localization, perception, prediction, planning and control, and start the learning path of building a self-driving car.

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Reddit Posts and Comments

0 posts • 3 mentions • top 3 shown below

r/SelfDrivingCars • comment
1 points • LovelyJiqiren

I love these sorts of questions and would love to see more of them on this sub. Thank you, /u/deeplearninglex

If you haven't already, I'd recommend checking out Udacity's free Apollo course, and Oliver Cameron's discussion of Prediction as the next frontier in SDCs.

r/learnmachinelearning • post
2 points • dittospin
What do you think of Udacity's ML, DL, and self-driving Nanodegrees?

Udacity is offering 1month free for all their Nanodegree programs, and I thought of taking one of their AI courses. For reference I have calc 1 and 2 and I'm a fairly decent programmer.

Thoughts? The self-driving car excites the most.

If these aren't worth the time, should I take Fast AI's DL or ML course first?

r/SelfDrivingCars • comment
1 points • selfdrivingcars360

Hi,

there seems to be a lot of sistemised information on this subject

check out Amazon https://www.amazon.com/s?k=Autonomous+Cars&i=stripbooks-intl-ship&ref=nb_sb_noss

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1)

On technical aspects I would recommend this book written by Baidu engineers

https://www.amazon.com/Creating-Autonomous-Vehicle-Systems-Shaoshan-ebook/dp/B079NTN992/ref=sr_1_7?keywords=Autonomous+Cars&qid=1553069612&s=books&sr=1-7

It covers three major subsystems of the car: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training.

In short -

Chapter 1 provides an overview of autonomous vehicle systems;

Chapter 2 focuses on localization technologies;

Chapter 3 discusses traditional techniques used for perception;

Chapter 4 discusses deep learning based techniques for perception;

Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies;

Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem;

Chapter 7 introduces reinforcement learning-based planning and control;

Chapter 8 delves into the details of client systems design; and

Chapter 9 provides the details of cloud platforms for autonomous driving.

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2) Take a FREE, but very usefull intro course from Udacity here -

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Self-Driving Fundamentals: Featuring Apollo

https://www.udacity.com/course/self-driving-car-fundamentals-featuring-apollo--ud0419

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3)

And if you like to dive deeper -

https://www.udacity.com/course/intro-to-self-driving-cars--nd113

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Good luck! )

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