ROS2 Self Driving Car with Deep Learning and Computer Vision

Rating 4.5 out of 5 (19 ratings in Udemy)

What you'll learn

Build your own Self Driving Car 🚘 in Simulation (ROS2)
Learn to develop 4 Essential 🤩 Self Drive features (Lane Assist, Cruise Control, Nav. T-Junc, Cross Intersections)
Master ComputerVision techniques 🤗 e.g. (Detection, Localization, Tracking)
Deep Dive with Custom-built 👌Neural Networks (CNN's)
( NEW!!! ) Develop a Satellite Navigation System (i.e GPS 😎 ) that helps the SDC navigate to any desired destination autonomously. 👍 …

Rating 4.5 out of 5 (19 ratings in Udemy)

What you'll learn

Build your own Self Driving Car 🚘 in Simulation (ROS2)
Learn to develop 4 Essential 🤩 Self Drive features (Lane Assist, Cruise Control, Nav. T-Junc, Cross Intersections)
Master ComputerVision techniques 🤗 e.g. (Detection, Localization, Tracking)
Deep Dive with Custom-built 👌Neural Networks (CNN's)
( NEW!!! ) Develop a Satellite Navigation System (i.e GPS 😎 ) that helps the SDC navigate to any desired destination autonomously. 👍
Learn 🕵️‍♂️ how to utilize functionality provided by other repos for your needs through a Practical example.

Description

This Course Contains ROS2 Based self-driving car through an RGB camera, created from scratch

SelfDrive Features:

- Lane Assist

- CruiseControl

- T-Junction Navigation

- CrossingIntersections

Ros Package

World Models Creation
Prius OSRF gazebo Model Editing
Nodes, Launch Files
SDF through Gazebo
Textures and Plugins in SDF

Software Part :

Perception Pipeline setup
Lane Detection with Computer Vision Techniques
Sign Classification using (custom-built) CNN
Traffic Light DetectionUsing Haar Cascades
Sign and Traffic Light Tracking using Optical Flow
Rule-Based Control Algorithms

Pre-Course Requirments

Software Based

Ubuntu 20.04 (LTS)
ROS2 - Foxy Fitzroy
Python 3.6
Opencv 4.2
Tensorflow 2.14

Skill Based

Basic ROS2 Nodes Communication
Launch Files
Gazebo Model Creation
Motivated mind :)

Course Flow (Self-Driving [Development Stage])

We will quickly get our car running on Raspberry Pi by utilizing 3D models ( provided in the repository) and car parts bought from links provided by instructors. After that, we will interface raspberry Pi with Motors and the camera to get started with Serious programming.

Then by understanding the concept of self-drive and how it will transform our near future in the field of transportation and the environment.Then we will perform a comparison between two SD Giants (Tesla & Waymo) ;). After that, we will put forward our proposal by directly talking you inside the simulation so that you can witness course outcomes yourself.

Primarily our Self Driving car will be composed of four key features.

1) Lane Assist 2) Cruise Control

3) Navigating T-Junction 4) Crossing Intersection

Each feature development will comprise of two parts

a) Detection: Gathering information required for that feature

b) Control: Proposing appropriate response for the information received

Software Requirements

Ubuntu 20.4 and ROS2 Foxy
Python 3.6
OpenCV 4.2
TensorFlow
Motivated mind for a huge programming Project

- Before buying take a look into this course Github repository or message
( if you do not want to buy get the code at least and learn from it :) )

Duration 11 Hours 58 Minutes

Paid

Self paced

All Levels

English (US)

413

Rating 4.5 out of 5 (19 ratings in Udemy)

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