In this lesson, we’re going to lay the foundation for the entire module by setting up a clean ROS2 workspace and integrating the xArm ROS2 stack, which will be the core robotic platform for all the applications we’ll develop later — from blind pick-and-place, to vision-based manipulation, to CNC-style toolpaths, all the way to full LLM-driven reasoning.

Before we jump into motion control, perception, and LLM planning, we need a reliable and well-organized development environment. This is exactly what today’s lesson is about.

What you will learn in this lesson

By the end of this lesson, you will be able to:

1. Create a new ROS2 workspace dedicated to LLM-powered robotics applications.
2. Clone the full xArm ROS2 ecosystem, including the robot description, MoveIt configuration, and control packages.
3. Build the workspace and verify that the robot can be launched successfully.

Why we start here

A solid foundation is critical when building advanced robotic applications.
Throughout this module, you will:

• Create custom packages
• Integrate MoveIt planners
• Add a simulated camera
• Build a perception pipeline
• Implement CNC trajectory generation
• And finally, connect everything to an LLM that generates motion commands and task plans in JSON

All of this depends on having a clean and stable robot environment from the beginning.
That’s why Lesson 1 focuses exclusively on preparing your workspace the right way.

What we are going to do step-by-step

1. Create a ROS2 workspace called xarm_ws.
2. Clone the main repositories:

• • xarm_ros2

1. Install dependencies using rosdep.
2. Build the workspace with colcon.
3. Source the environment.
4. Launch the robot and verify everything works.

Once these steps are complete, you’ll have a fully functional robotic base ready to be extended with custom applications.

The repository, located at https://github.com/LearnRoboticsWROS/my_xarm6_app, is a valuable resource for understanding the development and deployment of robotic applications. By following this lesson step by step, you will gain a deeper insight into the intricate process of developing software for robotics applications, specifically focusing on the xArm6 platform.

Lesson Summary

In this lesson, the focus is on setting up a clean and organized ROS2 workspace to prepare for developing applications using the xArm ROS2 stack. The following key points will be covered:

• Creation of a new ROS2 workspace dedicated to LLM-powered robotics applications.
• Cloning of the xArm ROS2 ecosystem, which includes robot description, MoveIt configuration, and control packages.
• Building the workspace and ensuring successful robot launch.

Starting with a solid foundation is crucial for constructing advanced robotic applications, as you will be working on tasks such as creating custom packages, integrating MoveIt planners, adding a simulated camera, building a perception pipeline, implementing CNC trajectory generation, and connecting everything to an LLM for motion commands and task plans in JSON format. A well-prepared environment is vital for these tasks, and that's why Lesson 1 focuses on workspace preparation.

The step-by-step process involves:

• Creating a ROS2 workspace named xarm_ws.
• Cloning main repositories such as xarm_ros2.
• Installing dependencies using rosdep.
• Building the workspace with colcon.
• Sourcing the environment.
• Launching the robot and verifying functionality.

Upon completing these steps, you will have a fully operational robotic base that can be further developed with custom applications. The repository provided at GitHub serves as a valuable resource for learning about robotic application development using the xArm6 platform. Following this lesson will offer a comprehensive understanding of software development for robotics applications.