RViz (ROS Visualization) is an open-source 3D visualization tool within the Robot Operating System (ROS), for visualizing a robot’s sensor data, state, and environment. It helps developers by displaying data from cameras, lidar, radar, and other sensors while visualizing robot models and joint states within the ROS ecosystem. Integrated with ROS topics, it streams real-time data, enabling interactive debugging and testing. RViz can be resource-intensive for large datasets and requires familiarity with ROS concepts. Nonetheless, it remains a good starting point for hobbyists and first-timers becoming familiar with ROS.
Foxglove empowers over 10,000 robotics and embodied AI developers and supports hundreds of robotics companies in accelerating and scaling their development. From data collection and ingestion to visualizing, debugging, and managing robotic data, Foxglove streamlines every step of the development process, enabling teams to innovate faster and more effectively.
“Things that were impossible before are now possible.”
Robert Sun, Founding Engineer, Dexterity
The deep ROS integration makes Foxglove a powerful tool for visualizing and debugging ROS-based systems. Its user-friendly interface and feature set streamline workflows, enabling robotic developers to work efficiently with ROS data streams in real-time or offline. Here’s how Foxglove supports ROS and simplifies getting started:
Foxglove supports both ROS 1 and ROS 2, ensuring compatibility regardless of the ROS version your project uses. It connects to ROS environments seamlessly, enabling real-time visualization of data from ROS topics, services, and parameters without additional setup or middleware.
Easily connect to your ROS data with the native Foxglove_bridge, a high-performance C++ node that seamlessly links ROS stacks to Foxglove via WebSocket. With minimal overhead, it supports both ROS 1 and ROS 2 for smooth integration.
Foxglove also offers multiple options for live ROS data integration, including the WebSocket protocol for simplicity, Rosbridge for efficient single-port communication, and native TCP connections, providing flexible and reliable real-time data access tailored to your robotics workflows.
Foxglove makes it easy to load and visualize data from ROS bag files, which are used to record and replay ROS data. Developers can replay bag files in Foxglove to analyze historical data, debug issues, or validate system performance. This capability is invaluable for diagnosing problems that occur in the field.
Get started instantly. Load files effortlessly by dragging and dropping a bag file, double-clicking, or selecting “Open local file.”
Foxglove supports ROS data visualization directly in the browser. This capability eliminates the need for complex installations or dependencies, allowing teams to access and share insights from any device.
1. Download and install Foxglove for your platform (Windows, macOS, or Linux) or use it directly in your browser.
2. Drag and drop your ROS bag files into Foxglove to start replaying and analyzing data immediately.
Foxglove simplifies the complexity of working with ROS data by integrating real-time visualization, debugging, and analysis into one powerful tool. Its compatibility with both ROS 1 and ROS 2, combined with its intuitive interface and seamless setup, ensures robotics developers can start visualizing and debugging ROS data quickly and efficiently. Whether you’re working on a small research project or scaling a complex robotics system, Foxglove’s comprehensive ROS support accelerates development and enhances insight.
“It fills a longstanding gap in the ROS ecosystem.”
Mirza A. Shah, CTO and Co-founder, Simbe
