My 2018 Path to Learning. , connect with me on You can find me on Twitter @bhutanisanyam1 Linkedin here This is Part 2 of the series. Here is the Part 1, go check it out to know what has been going on in my Garage! 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 Model 1 (Name TBD-Please help me pick a name in the comments below!) will be Raspberry Pi 3 based + RC Car setup. The Setup: 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. Reason: Model 1 Chasis: The Chasis is 10 years old! 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! Progress: Ubuntu Mate Setup I have also taken the courage to set 5 bold targets before my Term 1 starts (Roughly a week from now): Complete 2 Projects before the Term’s opening:I will attempt to make a crude solution to the Lane Detection & Sign Classification Projects, 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! before 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 Create a Simulation of a Self Driving Car using ROS:I will 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) not 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 and implementing Models using them. I have worked on Tensorflow Projects in my Deep Learning Nanodegree Internship Projects FastAI International Fellowship learning Complete Lex Fridman’s ’s 2018 version. Self Driving Course at MIT 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’ if you want a weekly-ish curated list of Deep Learning and Computer Vision articles. Subscribe to My Newsletter , connect with me on You can find me on Twitter @bhutanisanyam1 Linkedin here

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A Self Driving (New) Year #2

A Self Driving (New) Year #2

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