ROS2 Path Planning and Maze Solving with Computer Vision

Published 04/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 77 lectures (9h 19m) | Size: 8.5 GB

Mobile Robot Localization , Navigation and Motion Planning with Robot Operating System 2

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)

Python basic Programming and Modules

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


Motivated mind for a huge programming Project

Who this course is for
Engineers wanting to embark in the fields of Computer Vision, Artificial Intelligence and Robotics






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