ROS2 Self Driving Car with Deep Learning and Computer Vision

ROS2 Self Driving Car with Deep Learning and Computer Vision

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

Self Drive Features:

- Lane Assist

- Cruise Control

- T-Junction Navigation

- Crossing Intersections

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 Detection Using 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 :) )

Autonomous Car using TensorFlow and Neural Networks for Beginners

Url: View Details

What you will 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)

Rating: 4.85

Level: All Levels

Duration: 11 hours

Instructor: Muhammad Luqman