Foxglove is a purpose-built platform for robotics teams to collect, analyze, and learn from the vast quantities of multimodal data required to build, train, deploy, and operate reliable robots. In this notebook, we'll demonstrate how to retrieve messages from Data Platform and process them for insights. We'll be using self-driving car data from the nuScenes dataset, and writing Python code to visualize its route, IMU acceleration, and perceived objects.
Foxglove's mission is to increase the GDP of robotics. We build commercial and open source software to help robotics developers get to market faster and scale to millions of units. 🔎 Foxglove is our flagship visualization and observability platform for multimodal data.
🧢 MCAP is an open source file format for multimodal data. Foxglove, a startup building a data and observability platform for robotics companies, raised $40 million in Series B funding. Managing data through Foxglove's connections and platform creates seamless development loops: while your robot operates and records data, you identify issues, make improvements, redeploy, and repeat.
Foxglove Documentation Foxglove is a platform to record, upload, organize, and visualize multimodal log data such as time series, text logs, video, 3D, maps, and more. It is most often used in hardware, robotics, and physical AI. Workflows Foxglove supports all aspects of multimodal observability: Record Record logs in a variety of supported formats (MCAP, ROS Bag, ULog, etc) Ingest Import.
Foxglove is visualization and management for temporal and multimodal data. It's used by robotics companies to build reliable robots and accelerate development. Foxglove raised $40 million in Series B funding led by Bessemer Venture Partners to expand its data and observability platform for Physical AI, addressing a critical infrastructure bottleneck as robotics companies scale autonomous systems from prototypes to production deployments.
The funding reflects growing recognition that Physical AI. 🐍🦊 Python library for Foxglove Data Platform. Contribute to foxglove/foxglove.
Foxglove's primary use cases include multimodal data visualization and management. Visualizing all your robotic data on a single screen enables you to troubleshoot and debug issues more quickly. Managing data through Foxglove's connections and platform creates seamless development loops: while your robot operates and records data, you identify issues, make improvements, redeploy, and repeat.