5 posts tagged with "robotics"

Robotics applications generate and process a wide variety of data, such as sensor readings, video streams, logs, and AI model outputs. Managing this data efficiently is crucial because it affects the performance, scalability, and reliability of the entire system.

In this article, we'll compare ReductStore and MongoDB, two databases designed to handle different aspects of data management. ReductStore is a time-series blob storage solution optimized for managing large amounts of data coming from continuous streams. MongoDB, on the other hand, is a popular NoSQL database known for its flexibility, scalability, and support for unstructured and semi-structured data.

By understanding the strengths and limitations of each, you can make an informed decision to meet your project's specific data needs.

The Robot Operating System (ROS) stands as a versatile framework for developing sophisticated robotic applications with various sensors, including cameras. These cameras are relatively inexpensive and widely used as they can provide a wealth of information about the robot's environment.

Processing camera output with computer vision requires efficient solutions to handle massive amounts of data in real time. ROS 2 is designed with this in mind, but it is a communication middleware and does not provide a built-in solution for storing and managing large volumes of image data.

Addressing this challenge, this blog post will guide you through setting up ROS 2 with ReductStore—a time-series database for unstructured data optimized for edge computing, ensuring your robotic applications can process and store camera outputs effectively.

This blog post 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.