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Getting Started with ROS 2 for Physical AI Applications

#ros2 #robotics #ai #opensource

Getting Started with ROS 2 for Physical AI Applications

Introduction

ROS 2 is a robotics software framework that provides communication, tools, libraries, and conventions for building robot applications.

It is commonly used to connect:

  • Sensors
  • Controllers
  • Perception systems
  • Navigation
  • Manipulation
  • AI workloads
  • Visualization tools

ROS 2 Nodes

A ROS 2 application is typically divided into nodes.

For example:

Camera Node
     |
     v
Object Detection Node
     |
     v
Planning Node
     |
     v
Controller Node
     |
     v
Motor Node
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Each node can perform a focused task.

Installing ROS 2

ROS 2 distributions are tied to supported operating systems. Before installation, check the official ROS 2 documentation for the current distribution and platform.

After installation, source the ROS 2 environment:

source /opt/ros/<distribution>/setup.bash
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You can then test the installation:

ros2 --help
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Creating a Workspace

A common ROS 2 workspace layout is:

ros2_ws/
└── src/
    └── robot_package/
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Create it with:

mkdir -p ~/ros2_ws/src
cd ~/ros2_ws
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Build the workspace using the ROS 2 build system:

colcon build
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Then source the workspace:

source install/setup.bash
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ROS 2 Topics

Topics allow nodes to exchange messages using a publish-subscribe model.

For example:

Camera Node
    |
    | publishes images
    v
/camera/image
    |
    v
AI Detection Node
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A sensor node can publish data without knowing which nodes consume it.

ROS 2 Services

Services provide request-response communication.

For example:

Robot Controller
       |
       | request
       v
Reset Service
       |
       | response
       v
Controller
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Services are useful for operations that have a clear request and response.

ROS 2 Actions

Actions are designed for longer-running tasks.

Examples:

  • Navigate to a location
  • Move a robot arm
  • Execute a trajectory

An action can provide feedback and can be cancelled.

ROS 2 and Physical AI

A Physical AI architecture might look like:

Sensors
   |
   v
ROS 2 Drivers
   |
   +---------> Perception / AI
   |                 |
   v                 v
State Estimation -> Planning
                      |
                      v
                 Control
                      |
                      v
                  Actuators
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ROS 2 provides the communication infrastructure, while specialized libraries and real-time components can handle time-critical workloads.

Useful ROS 2 Commands

List nodes:

ros2 node list
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List topics:

ros2 topic list
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Inspect a topic:

ros2 topic info /topic_name
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Echo messages:

ros2 topic echo /topic_name
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List services:

ros2 service list
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Best Practices

  • Keep nodes focused on specific responsibilities.
  • Define clear message interfaces.
  • Use appropriate QoS settings.
  • Separate high-level AI processing from low-level control.
  • Monitor message latency.
  • Test communication under realistic network conditions.
  • Use simulation before deploying to expensive hardware.

Conclusion

ROS 2 provides a flexible foundation for building modular Physical AI applications. Its node, topic, service, and action abstractions allow complex robot systems to be divided into manageable components.

Useful Links

Website: www.v-modal.com

SDK Flutter: https://github.com/v-modal/vmodal_sdk_flutter

SDK Android: https://github.com/v-modal/vmodal_sdk_android

Discord: https://discord.gg/K72z28KU

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