14 posts tagged with "robotics"

The CRA Deadline Every German Robot Operator Must Face

The EU Cyber Resilience Act (Regulation (EU) 2024/2847) is the “GDPR for connected products.” It entered into force on 10 December 2024, with critical milestones approaching fast:

• 11 September 2026: Mandatory reporting of actively exploited vulnerabilities and severe incidents (24-hour early warning, 72-hour full notification).
• 11 December 2027: Full compliance — Security by Design, lifecycle support (minimum 5 years), technical documentation, and CE marking.

For robotics fleets (AMRs, cobots, autonomous systems, and ROS 2-based platforms) the stakes are particularly high. These systems are “products with digital elements” (often Class II or critical), generating massive multimodal data streams (camera feeds, LiDAR, IMU, logs, ROS bags) under real production constraints: intermittent connectivity, edge hardware limits, and high physical safety risks.

Generic storage solutions force painful trade-offs: either accept data loss and compliance gaps, or accept exploding costs and slow performance. ReductStore eliminates this trade-off.

Robots generate massive amounts of data, and managing it well is harder than it looks. Storage fills up fast, cloud transfer gets expensive, and real time ingestion is unforgiving when you're running cameras and sensors at high frequency.

This article covers practical strategies for handling robotic data, introduces ReductStore, and walks through a hands on example. Along the way, we cover native ROS integration, Grafana dashboards, MCAP export for Foxglove, a Zenoh API, and native S3 and Azure backends. We also compare ReductStore against Rosbag and MongoDB so you can pick the right tool for each part of your stack.

Drones in air-gapped environments produce a lot of data (camera images, telemetry, logs, model outputs). Storing this data reliably on each drone and syncing it to a ground station later can be hard. ReductStore makes this easier: it's a lightweight, time-series object store that works offline and replicate data when a connection is available.

This guide explains a simple setup where each drone stores data locally with labels, replicates records to a ground station based on what it detects, and keeps a clear audit trail of what was captured and replicated.