ROS2 Ultimate Mobile Robotics Course for Beginners OpenCV




ROS2 Ultimate Mobile Robotics Course for Beginners OpenCV

This Course is on ROS2 Foxy Fritzoy on Linux .If you are interested in learning the fast growing technology then this course is for you !.


Outcomes After this Course : You can create

  • Custom Workspace

  • Custom Python Packages

  • Custom Python Nodes

  • Message Publishing Bandwidth and Frequency

  • Creation of Robot through URDF in XML

  • Launch files

  • RVIZ2 and Gazebo Simulation Fundamentals

  • Adding Virtual Sensors to your Robot

    • Camera

    • Lidar

    • Driving Differential Drive Control

Projects :

  • Obstacle Avoiding Custom Robots

  • Wall Following Robot

  • Line Following Prius Car with Computer Vision


Process of Explanation

  1. Theory for Concepts building with interactive Writing and Comments

  2. Writing Code for the nodes and concepts discussed

  3. Analyzing the output and noting the resources utilized


Course Flow

I will be first teaching you some basics of ROS2 with the help of in-built ROS2 package "TurtleSim" . Then will start to move toward very useful concepts which are nodes , package, topic, messages etc.

This will lead us towards creation of our new package "Dolly" which is a car that we will be creating from scratch using URDF xml syntax . Next we will create its Gazebo and RVIZ2 3D simulator

With these simulators endless possibilities of projects will open by adding the virtual sensors to your Robot.



Disclaimer

This course is just the beginning of ROS2 and you Will not become a developer right away . But still it will put you on the track how to get into ROS and work for your projects to learn .

Contact me if you are confused to take the Course :)

Start your ROS Developer Journey by Building Custom Robot ,Nodes , Workspaces and Packages

Url: View Details

What you will learn
  • Learn ROS2 Basics
  • Learn to add Lidar and Camera sensors
  • Emulate your Sensors in Gazebo

Rating: 3.3

Level: Intermediate Level

Duration: 3 hours

Instructor: Muhammad Luqman


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