Self Driving and ROS 2 - Learn by Doing! Odometry & Control

Name: Self Driving and ROS 2 - Learn by Doing! Odometry & Control
Rating: 4.5 (1009 reviews)

Create a ROS2 Self-Driving robot with Python and C++. Master Odometry, Control and Sensor Fusion using Kalman Filters

Bestseller

Created byAntonio Brandi

Last updated 1/2026

English

What you'll learn

Create a Real Self-Driving Robot
Mastering ROS2, the latest version of the Robot Operating System
Implement Sensor Fusion algorithms
Simulate a Self-Driving robot in Gazebo
Programming Arduino for Robotics Applications
Use the ros2_control library
Develop a Controller
Odometry and Localization
Kalman Filters and Extended Kalman Filter
Probability Theory
Differential Kinematics
Create a Digital Twin of a Self-Driving Robot
Master the TF2 library

Course content

13 sections • 174 lectures • 28h 46m total length

Course Motivation2:53
The Self-Driving Program3:16
Course Presentation6:16
Meet your Teacher2:27
[EXTRA]: Boost your Robotics Software Developer Career1:53
Get the Most out of the Course3:40
Course Material1:05

Why a Robot Operating System?4:18
What is ROS 23:13
Why a NEW Robot Operating System?4:58
ROS 2 Architecture3:12
Hardware Abstraction2:53
Low-Level Device Control1:22
Messaging Between Process7:00
Package Management1:41
Architecture of a ROS 2 Application2:59
Introduction to ROS 2
<LAB>Create and Activate a Workspace</LAB>11:18
<PY>Simple Publisher</PY>18:16
<C++>Simple Publisher</C++>23:14
<PY>Simple Subscriber</PY>13:15
<C++>Simple Subscriber</C++>15:44
Workspaces, Publishers, Subscribers

Robot Locomotions5:54
Mobile Robots4:15
Friction Effects9:54
Robot Description3:33
URDF4:41
<LAB>Create the URDF Model</LAB>31:24
Rviz 25:32
Parameters1:55
<PY>Parameters</PY>13:33
<C++>Parameters</C++>17:04
<LAB>ROS 2 Parameter CLI</LAB>6:36
URDF and Parameters
<LAB>Visualize the Robot</LAB>9:07
Launch Files5:58
<LAB>Visualize the Robot with Launch Files</LAB>20:23
Add a Can on top of your Robot
Gazebo4:48
<LAB>Simulate the Robot</LAB>14:59
<LAB>Launch the Simulation</LAB>16:27

The TF2 Library5:23
Operations with Transformations5:31
Static and Dynamic Transformations3:00
<PY>Simple TF2 Static Broadcaster</PY>14:09
<C++>Simple TF2 Static Broadcaster</C++>19:14
<PY>Simple TF2 Broadcaster</PY>13:09
<C++>Simple TF2 Broadcaster</C++>13:21
ROS 2 Services5:43
<PY>Service Server</PY>19:10
<C++>Service Server</C++>21:05
<PY>Service Client</PY>18:36
<C++>Service Client</C++>23:31
<PY>Simple TF2 Listener</PY>20:06
<C++>Simple TF2 Listener</C++>23:12
Angle Rapresentations1:41
Euler Angles3:04
Quaternion3:54
<PY>Euler to Quaternion</PY>11:47
<C++>Euler to Quaternion</C++>12:39
<LAB>TF2 Tools</LAB>7:31

Where is the Robot?3:01
The Local Localization Challenge5:22
Wheel Odometry7:49
Differential Inverse Kinematics5:33
<PY>Differential Inverse Kinematic</PY>18:55
<C++>Differential Inverse Kinematic</C++>20:35
Wheel Odometry - Position3:17
Wheel Odometry - Orientation3:38
<PY>Wheel Odometry</PY>10:35
<C++>Wheel Odometry</C++>10:48
<PY>Publish Odometry Message</PY>14:48
<C++>Publish Odometry Message</C++>16:16
Draw the Robot's Trajectory
<PY>Broadcast Odometry Transform</PY>11:44
<C++>Broadcast Odometry Transform</C++>13:14

Requirements

Basic knowledge of Python or C++
Basic knowledge of Linux
No prior knowledge of ROS or ROS 2 required
No prior knowledge of Robotics theory required
No hardware required. All the course can be followed also using only the PC

Description

Would you like to build a real Self-Driving Robot using 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 Odometry and Control 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 a theoretical and practical point of view.

Each section is composed of three parts:

Theoretical explanation of the concept and functionality
Usage of the concept in a simple Practical example
Application of the functionality in a real Robot

There is more!

All the programming lessons are developed using both 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.

Who this course is for:

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

Self Driving and ROS 2 - Learn by Doing! Odometry & Control

What you'll learn

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Course content

Introduction7 lectures • 22min

Setup8 lectures • 49min

Introduction to ROS 214 lectures • 1hr 53min

Locomotion17 lectures • 2hr 56min

Control7 lectures • 1hr

Kinematics10 lectures • 1hr 38min

Differential Kinematics12 lectures • 2hr 14min

TF2 Library20 lectures • 4hr 6min

Odometry14 lectures • 2hr 26min

Probability for Robotics12 lectures • 1hr 34min

Requirements

Description

Who this course is for: