When you enroll through our links, we may earn a small commission—at no extra cost to you. This helps keep our platform free and inspires us to add more value.

Self Driving and ROS 2 - Learn by Doing! Map & Localization
Create a ROS2 Self-Driving robot with Python and C++. Master Robot Localization, Mapping and SLAM

This Course Includes
udemy
4.7 (347 reviews )
25h 9m
english
Online - Self Paced
professional certificate
Udemy
About Self Driving and ROS 2 - Learn by Doing! Map & Localization
Would you like to build a real
Self-Driving Robot
using
ROS2
, the second and last version of the Robot Operating System, by building a
real robot
? Would you like to get started with
Autonomous Navigation
of robots 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 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.
What You Will Learn?
- Create a Real Self-Driving Robot .
- Master ROS2, the latest 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 Show moreShow less.