In this class, we are going to see how to reproduce the results of the famous paper "Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World" with Fetch robot, using ROS and Gazebo simulation.
You will learn:
▸ What is domain randomization
▸ How to implement it in Gazebo using a world plugin
▸ How the whole pipeline works: from training the vision system to making the robot grasp the spam object
▸ How to create the dataset to train the visual system using simulation images.
- The whole code will be provided for free to all the attendants to the class as a ROSject, containing simulation, notebook with instructions and code.
➡️ ROSject link: [ Ссылка ]
📚 Related course: Deep Learning with Domain Randomization: [ Ссылка ]
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Every Tuesday at 18:00 CET / CEST. This is a LIVE Class on how to develop with ROS. In Live Classes, you will practice with me at the same time that I explain, with the provided free ROS material. IMPORTANT: Remember to be on time for the class because at the beginning of the class we will share the code with the attendants for free. IMPORTANT 2: in order to start practicing quickly, we are using the ROS Development Studio for doing the practice. You will need a free account to attend the class. Go to [ Ссылка ] and create an account prior to the class. // RELATED LINKS ▸ ROS Development Studio: [ Ссылка ] ▸ Robot Ignite Academy: [ Ссылка ]= youtube & ▸ What is a ROSject ?: http:
