9 posts tagged with "ros"

Mobile robots produce a lot of data (camera images, IMU readings, logs, etc). Storing this data reliably on each robot and syncing it to the cloud can be hard. ReductStore makes this easier: it's a lightweight, time-indexed object store built for robotics and industrial IoT. It stores binary blobs (images, logs, CSV sensor data, MCAP, JSON) with timestamps and labels so you can quickly find and query them later.

This introduction guide explains a simple setup where each robot stores data locally and automatically syncs it to a cloud ReductStore instance backed by Amazon S3.

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!

ROS2 is widely used for building robotic systems with sensors like cameras, LiDAR, and IMUs. While it's great for communication (e.g., publishing and subscribing to topics), it lacks a built-in solution for storing large amounts of unstructured data, such as images.

Bag files are commonly used to store data in ROS2, but they aren't a good fit for long-term storage or real-time streaming. They're mainly meant for recording and replaying mission data or episodes, not for managing large volumes of unstructured data.

Addressing this challenge, this blog post will guide you through setting up ROS2 with ReductStore a high-performance storage and streaming solution optimized for unstructured, time-series data.

We will focus specifically on image data, but if you are interested in a more general overview you can read How to Store and Manage Robotic Data which covers the challenges and strategies for storing and managing robotic data in general.

For the full code example, we will be using the reduct-ros-example repository, which provides a complete implementation of the concepts discussed in this article.