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How to Analyze ROS Bag Files and Build a Dataset for Machine Learning

· 8 min read
Ekaterina Marova
Data Scientist - ML, Python

Linear and Angular Velocities over Time

Working with real-world robot data depends on how ROS (Robot Operating System) messages are stored. In the article 3 Ways to Store ROS Topics, we explored several approaches — including storing compressed Rosbag files in time-series storage and storing topics as separate records.

In this tutorial, we'll focus on the most common format: .bag files recorded with Rosbag. These files contain valuable data on how a robot interacts with the world — such as odometry, camera frames, LiDAR, or IMU readings — and provide the foundation for analyzing the robot's behavior.

You’ll learn how to:

  • Extract motion data from .bag files
  • Create basic velocity features
  • Train a classification model to recognize different types of robot movements

We'll use the bagpy library to process .bag files and apply basic machine learning techniques for classification.

Although the examples in this tutorial use data from a Boston Dynamics Spot robot (performing movements like moving forward, sideways, and rotating), you can adapt the code for your recordings.

Data Acquisition System for Manufacturing: Shop Floor to Cloud

· 7 min read
Alexey Timin
Software Engineer - Database, Rust, C++

ReductStore on DAQ edge device

As modern manufacturing becomes increasingly data-driven, the need for efficient data acquisition systems is more critical than ever. In my previous article, Building a Data Acquisition System for Manufacturing, we discussed the challenges of data acquisition in manufacturing and how ReductStore can help solve them. Here we will learn how to use ReductStore at the edge of the shop floor and stream data to the cloud.

ReductStore vs. MinIO: Beyond Benchmarks

· 7 min read
Anthony Cavin
Data Scientist - ML/AI, Python, TypeScript

MinIO vs ReductStore

As data-driven applications evolve, the need for efficient storage solutions continues to grow. ReductStore and MinIO are two powerful solutions designed to handle massive amounts of unstructured data, but they serve different purposes.

While ReductStore is optimized for time-series object storage with a focus on unstructured data such as sensor logs, images, and machine-generated data for robotics and IIoT, MinIO is a high-performance object storage system built for scalable, cloud-native applications with a focus on S3 compatibility and enterprise-wide storage needs.

In this article, we'll explore the differences between ReductStore and MinIO, examine where each excels, and discuss how they can be used together to build a more comprehensive data storage solution.