A Self Driving (New) Year #2

My 2018 Path to Learning.

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This is Part 2 of the series.

Term 1 Cohort of my Self Driving Car Nanodegree classroom starts on the 19th, meanwhile I have started working on things in my Garage that I want to share:

2 Weeks in:

As Promised, I would add posts to the series regularly

Here is some news:I have decided to make a Mini Self Driving Car to apply what I will learn in my Self Driving Car Nanodegree Program:

• The Setup: The Model 1 (Name TBD-Please help me pick a name in the comments below!) will be Raspberry Pi 3 based + RC Car setup.
• Reason: Raspberry Pi 3 although has less horsepower (pun intended) to run all the Image Processing and detection tasks is a good place to test my skills as a primer and certainly later, I will apply the same to a Nvidia Jetson TX-2 (Or 1). The secondary reason being, I don’t own a Jetson and I will apply for Student aid options later.

Model 1 Chasis: The Chasis is 10 years old!

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  Progress: 1. I’ve found a RC Toy Car (from my childhood), that will function as the main chassis.2. Setup RPI3 board: I’ve installed Ubuntu Mate on the Raspberry Pi Board, configured ROS and OpenCV on it. 3. Setup the PiBoard for Remote Logins and running scripts on boot: which is essential, since in the field my Model 1 car should be able to boot up and drive right away!

Ubuntu Mate Setup I have also taken the courage to set 5 bold targets before my Term 1 starts (Roughly a week from now):

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  Complete 2 Projects before the Term’s opening:I will attempt to make a crude solution to the Lane Detection & Sign Classification Projects, before the Nanodegree opens! (The Project Repositories are hosted on GitHub and I will attempt to solve it using knowledge and hints provided via them). Later, I’ll share a proper review once the Projects ‘Meet specifications’-which is Udacity’s codeword for saying Project Complete!

• Deploy Lane Detection on Model 1 Mini SDC (Guys, please help me pick a name, this doesn’t sound cool at all). Since the Lane Detection pipeline is OpenCV based, I’ll test on the RPI board using the Pi Camera.

Pi Cam 2

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  Create a Simulation of a Self Driving Car using ROS:I will not Udacity’s Simulator, I will take a shot at Gazebo and use Open Source Models of Cars to make a simulation. The goal is to make a model where I can play around with algorithms (not to make a fully functioning prototype inside a simulation)

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  Learn Keras basics: and in my , PyTorch in the . Next up is Keras which will be used in my Term 1.By no means am I a master of these Libraries, but I’m keen on learning and implementing Models using them.

• Complete Lex Fridman’s ’s 2018 version.

Long Term functionality Goals for My Mini Self Driving Car:

• Path (lane) following
• Crash Avoidance
• Object Detection
• Symbol Detection
• Bonus points: A drift mode!

Please note that these aren’t the Pre-requistes, rather are my own personal ventures to my Self Driving Year. I will share detailed posts of the targets that I have completed. Stay Tuned for updates! I will keep sharing my story, if I make it to the finish line with my Goals or hit the dust!

These series will also be a public accountability of how I have been working on my Journey and hence the title for the series ‘A Self Driving Year’

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