Self Driving and ROS 2 – Learn by Doing! Map & Localization

Self Driving and ROS 2 – Learn by Doing! Map & Localization, available at $54.99, has an average rating of 4.77, with 153 lectures, 2 quizzes, based on 47 reviews, and has 1505 subscribers.

You will learn about Create a Real Self-Driving Robot Master ROS2, the last version of the Robot Operating System Implement Mapping algorithms Implement Localization algorithms Implement SLAM algorithms Simulate a Self-Driving robot in Gazebo Programming Arduino for Robotics Applications Master Nav2 Probability Theory Use Laser Sensors for real world applications Master the slam_toolbox library This course is ideal for individuals who are Self-Driving enthusiast or Makers and Hobbists keen on robotics or Software developers taht wants to learn ROS 2 and Robotics or Students or Engineers that wants to learn how to buid a robot from scratch or Developers that already knows ROS 2 and that want to use it in a real world application or ROS Developers that want to learn and migrate to ROS 2 or Robotics Engineers that wants to develop skills in Autonomous Navigation or Beginner Python developers curious about Self-Driving or Beginner C++ developers curious about Self-Driving It is particularly useful for Self-Driving enthusiast or Makers and Hobbists keen on robotics or Software developers taht wants to learn ROS 2 and Robotics or Students or Engineers that wants to learn how to buid a robot from scratch or Developers that already knows ROS 2 and that want to use it in a real world application or ROS Developers that want to learn and migrate to ROS 2 or Robotics Engineers that wants to develop skills in Autonomous Navigation or Beginner Python developers curious about Self-Driving or Beginner C++ developers curious about Self-Driving.

Enroll now: Self Driving and ROS 2 – Learn by Doing! Map & Localization

Summary

Title: Self Driving and ROS 2 – Learn by Doing! Map & Localization

Price: $54.99

Average Rating: 4.77

Number of Lectures: 153

Number of Quizzes: 2

Number of Published Lectures: 150

Number of Published Quizzes: 2

Number of Curriculum Items: 155

Number of Published Curriculum Objects: 152

Original Price: $119.99

Quality Status: approved

Status: Live

What You Will Learn

Create a Real Self-Driving Robot
Master ROS2, the last version of the Robot Operating System
Implement Mapping algorithms
Implement Localization algorithms
Implement SLAM algorithms
Simulate a Self-Driving robot in Gazebo
Programming Arduino for Robotics Applications
Master Nav2
Probability Theory
Use Laser Sensors for real world applications
Master the slam_toolbox library

Who Should Attend

Self-Driving enthusiast
Makers and Hobbists keen on robotics
Software developers taht wants to learn ROS 2 and Robotics
Students or Engineers that wants to learn how to buid a robot from scratch
Developers that already knows ROS 2 and that want to use it in a real world application
ROS Developers that want to learn and migrate to ROS 2
Robotics Engineers that wants to develop skills in Autonomous Navigation
Beginner Python developers curious about Self-Driving
Beginner C++ developers curious about Self-Driving

Target Audiences

Self-Driving enthusiast
Makers and Hobbists keen on robotics
Software developers taht wants to learn ROS 2 and Robotics
Students or Engineers that wants to learn how to buid a robot from scratch
Developers that already knows ROS 2 and that want to use it in a real world application
ROS Developers that want to learn and migrate to ROS 2
Robotics Engineers that wants to develop skills in Autonomous Navigation
Beginner Python developers curious about Self-Driving
Beginner C++ developers curious about Self-Driving

Would you like to build a real Self-Driving Robotusing ROS2, the second and last version of Robot Operating System by building a real robot?

Would you like to get started with Autonomous Navigation of Robot and dive into the theoretical and practical aspects of Localization, Mapping and SLAM from industry experts?

The philosophy of this course is the Learn by Doing and quoting the American writer and teacher Dale Carnegie

Learning is an Active Process. We learn by doing, only knowledge that is used sticks in your mind.

In order for you to master the concepts covered in this course and use them in your projects and also in your future job, I will guide you through the learning of all the functionalities of ROS both from the theoretical and practical point of view.

Each section is composed of three parts:

Theoreticalexplanation of the concept and functionality
Usage of the concept in a simple Practicalexample
Application of the functionality in a real Robot

There is more!

All the programming lessons are developed both using Python and C++ . This means that you can choose the language you are most familiar with or become an expert Robotics Software Developer in both programming languages!

By taking this course, you will gain a deeper understanding of self-driving robots and ROS 2, which will open up opportunities for you in the exciting field of robotics.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Motivation

Lecture 2: The Self-Driving Program

Lecture 3: Course Presentation

Lecture 4: Meet your Teacher

Lecture 5: Get the Most out of the Course

Lecture 6: Course Material

Chapter 2: Setup

Lecture 1: Install Ubuntu on Virtual Machine

Lecture 2: Install Ubuntu on Dual Boot

Lecture 3: <LAB>Install ROS 2</LAB>

Lecture 4: <LAB>Configure the Development Environment</LAB>

Lecture 5: <HWLAB>Configure the Development Environment</HWLAB>

Lecture 6: <HWLAB>Install ROS 2 on Raspberry Pi</HWLAB>

Lecture 7: <LAB>Getting Started with the Simulated Robot</LAB>

Chapter 3: Introduction to ROS 2

Lecture 1: Why a Robot Operating System?

Lecture 2: What is ROS 2

Lecture 3: Why a NEW Robot Operating System

Lecture 4: ROS 2 Architecture

Lecture 5: Hardware Abstraction

Lecture 6: Low-Level Device Control

Lecture 7: Messaging Between Process

Lecture 8: Package Management

Lecture 9: Architecture of a ROS 2 Application

Lecture 10: <LAB>Create and Activate a Worksapce</LAB>

Lecture 11: <PY>Simple Publisher</PY>

Lecture 12: <C++>Simple Publisher</C++>

Lecture 13: <PY>Simple Subscriber</PY>

Lecture 14: <C++>Simple Subscriber</C++>

Chapter 4: Probability for Robotics

Lecture 1: Motivation

Lecture 2: Random Variables

Lecture 3: Conditional Probability

Lecture 4: Probability Distributions

Lecture 5: Gaussian Distributions

Lecture 6: Total Probability Theorem

Lecture 7: Bayes Rule

Lecture 8: Sensor Noise

Chapter 5: Global Localization

Lecture 1: Where am I ?

Lecture 2: Robot Localization

Lecture 3: Robotics Convention for Localization

Lecture 4: Why a Robotics Convention for Localization?

Lecture 5: Gazebo Worlds and Models

Lecture 6: <LAB>Give an house to the Robot</LAB>

Lecture 7: Local and Global Localization

Lecture 8: Local Localization

Lecture 9: Global Localization

Lecture 10: Wheel Odometry Errors

Lecture 11: Laser Odometry Errors

Lecture 12: The Real Purpose of Global Localization

Lecture 13: Error Propagation

Lecture 14: Odometry Motion Model

Lecture 15: <PY>Odometry Motion Model</PY>

Lecture 16: <PY>Odometry Motion Model with Noise</PY>

Lecture 17: <C++>Odometry Motion Model</C++>

Lecture 18: <C++>Odometry Motion Model with Noise</C++>

Lecture 19: <LAB>Odometry Motion Model</LAB>

Chapter 6: Sensors for Localization and Mapping

Lecture 1: What is a Map

Lecture 2: How Robots Perceive the World

Lecture 3: Sensors for Self-Driving Robots

Lecture 4: 1D Sensors – Sonar

Lecture 5: 2D Sensors – LiDAR

Lecture 6: <LAB>Add a 2D LiDAR to the Robot</LAB>

Lecture 7: <LAB>Simulate a 2D LiDAR</LAB>

Lecture 8: 3D Sensors – RGBD Cameras and 3D LiDAR

Lecture 9: Speed and Separation Monitoring

Lecture 10: twist_mux

Lecture 11: <LAB>Preparation for twist_mux</LAB>

Lecture 12: <LAB>Configure twist_mux</LAB>

Lecture 13: <LAB>Use twist_mux</LAB>

Lecture 14: <PY>Safety Stop</PY>

Lecture 15: <C++>Safety Stop</C++>

Lecture 16: <LAB>Safety Stop</LAB>

Lecture 17: ROS 2 Actions

Lecture 18: <PY>Create an Action Server</PY>

Lecture 19: <C++>Create an Action Server</C++>

Lecture 20: <LAB>Create an Action Server</LAB>

Lecture 21: <PY>Create an Action Client</PY>

Lecture 22: <C++>Create an Action Client</C++>

Lecture 23: <LAB>Create an Action Client</LAB>

Lecture 24: <PY>Speed and Separation Monitoring</PY>

Lecture 25: <C++>Speed and Separation Monitoring</C++>

Lecture 26: <LAB>Speed and Separation Monitoring</LAB>

Lecture 27: <PY>Display Markers in RViz</PY>

Lecture 28: <C++>Display Markers in RViz</C++>

Lecture 29: <LAB>Display Markers in RViz</LAB>

Chapter 7: Map Representations

Lecture 1: Map Representation

Lecture 2: Topological Maps

Lecture 3: OccupancyGrid

Lecture 4: Octomap and Voxel Grids

Lecture 5: Introduction to Nav2

Lecture 6: ROS 2 Lifecycle Nodes

Lecture 7: <PY>Create a Lifecycle Node</PY>

Lecture 8: <C++>Create a Lifecycle Node</C++>

Instructors

Antonio Brandi
Robot Autonomous Navigation Engineer

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2 stars: 0 votes
3 stars: 2 votes
4 stars: 9 votes
5 stars: 36 votes

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