The Robot Operating System (ROS) is an open-source framework for writing robot software. It provides a structured communications layer above the host operating systems of a heterogeneous compute cluster. Originally developed by Willow Garage in 2007, ROS has since become the de facto standard for robotics middleware, empowering developers with tools and libraries to build complex and scalable robot applications.
Despite its name, ROS is not a traditional operating system. Instead, it offers a flexible and distributed architecture composed of:
- Nodes: Independent processes that perform computation.
- Topics: A publish/subscribe messaging mechanism for nodes.
- Services: Synchronous communication between nodes.
- Actions: Asynchronous task management.
- Bags: File format for recording and playing back ROS message data.
Two major versions exist—ROS 1 and ROS 2. While ROS 1 focused on rapid prototyping and single-machine development, ROS 2 is designed for real-time performance, security, and multi-robot systems with DDS (Data Distribution Service) as its communication middleware.
How is ROS used in robotics?
ROS is widely used across research and industry to power autonomous systems, from mobile robots to aerial drones and industrial manipulators. Here’s how ROS supports robotic development:
- Sensor Integration: ROS supports a wide array of sensors such as cameras, GPS, imu, and lidar. Drivers and packages allow easy integration and real-time data acquisition.
- Control and Planning: With built-in support for kinematics, dynamics, and motion planning libraries like MoveIt, ROS enables the development of advanced robotic behaviors.
- Simulation: Tools like Gazebo and Ignition allow developers to simulate complex environments and test robotic systems before deployment.
- Mapping and Navigation: ROS provides robust SLAM (Simultaneous Localization and Mapping) and navigation stacks to enable autonomous movement and obstacle avoidance.
- Data Logging and Playback: ROS’s rosbag tool enables recording data during robot operation, which can later be played back for debugging and analysis.
Common ROS use cases in robotics.
| Use case |
ROS tools involved |
Description |
| Autonomous navigation |
nav2, tf2, costmap_2d |
Enables robots to plan paths and avoid obstacles in real-time. |
| Robot arm manipulation |
MoveIt, JointStatePublisher |
Used for inverse kinematics, planning, and executing motion commands. |
| Perception |
image_pipeline, PCL, OpenCV |
Processes sensor data to interpret and react to the environment. |
| Swarm robotics |
DDS, multi-master_fkie |
Coordinates multiple robots operating collaboratively. |
Use ROS with Foxglove.
Visualize ROS data in real time.
Foxglove is a powerful observability platform designed to work seamlessly with ROS-based systems. Whether you’re using ROS 1 or ROS 2, Foxglove provides intuitive interfaces for visualizing your robot’s real-time data.
- Topics viewer: Monitor the health and throughput of your ROS topics.
- Message inspector: Inspect the structure and contents of messages like sensor_msgs/Image or nav_msgs/Odometry.
- 3D view: Visualize tf trees, point clouds, and robot models in a unified, interactive 3D environment.
Load and analyze rosbag files.
Foxglove supports both live streaming and postmortem analysis using rosbag files. Developers can:
- Upload .bag files to replay telemetry data.
- Debug complex issues by scrubbing through time-stamped logs.
- Compare multiple data streams from the same session in synced views.
Debug robotics systems faster.
With Foxglove, engineers get:
- Schema-aware decoding of ROS messages.
- Custom panels tailored to robot-specific diagnostics.
- Time-synchronized playback of multiple sensor streams (camera, lidar, imu).
This drastically shortens the feedback loop when debugging distributed robotic systems.
Benefits of using Foxglove with ROS.
- Seamless ROS integration: Native compatibility with ROS 1 and ROS 2.
- No-code visualization: Out-of-the-box tools reduce the need for custom RViz plugins or dashboard UIs.
- Cross-platform support: Run in browser or desktop app.
- Remote collaboration: Share sessions and insights with distributed teams.
The Robot Operating System is a foundational technology in modern robotics. By combining ROS’s open ecosystem with Foxglove’s observability and debugging tools, robotics teams can accelerate development, reduce downtime, and build smarter, more reliable robots.
