11 posts tagged with "robotics"

Robotics teams today wrestle with data that grows faster than their infrastructure. Every robot generates streams of images, sensor readings, logs, and events in different formats. These data piles are fragmented, expensive to move, and slow to analyze. Teams often rely on generic cloud tools that are not built for robotics. They charge way too much per gigabyte (when it should cost little per terabyte), hide the raw data behind proprietary APIs, and make it hard for robots (and developers) to access or use their own data.

ReductStore introduces a new category: a database purpose built for robotics data pipelines. It is open, efficient, and developer friendly. It lets teams store, query, and manage any time series of unstructured data directly from robots to the cloud.

In robotics development, effective visualization and analysis tools are essential for monitoring, debugging, and interpreting complex sensor data. Platforms like RViz, Foxglove, and Rerun play a key role at the visualization layer of the observability stack. They help developers interact with both live and recorded data. These tools rely on timely, well-structured access to the underlying data streams. That's where ReductStore comes in. It handles the data logging, storage, and processing, with a focus on capturing high-volume time-series data efficiently. ReductStore aims to integrate with tools like RViz, Foxglove, and Rerun, supporting a complete observability pipeline: from raw data ingestion to actionable insights.

At ReductStore, we specialize in the high-performance storage and streaming of robotics data from edge devices to the cloud. In this tutorial, we will demonstrate how to develop a robust ROS 2 data logging pipeline for practical robotics applications.

First, we will set up a Raspberry Pi with a USB camera running a lightweight YOLOv5n object detection model via ONNX Runtime. Then, a recorder node will capture selected ROS 2 topics, including images, detection results, and logs. Next, these topics will be saved as segmented MCAP files locally with ReductStore. Finally, we will configure automatic replication to stream data to another ReductStore instance.

This minimal setup shows how to efficiently capture, store, and replicate ROS 2 data from a robot to a central server or cloud instance. These techniques can be applied to any ROS 2 system, whether it's a single robot or a fleet of autonomous systems.

Let's get started!