开源工具Kleinkram帮机器人研究者高效管理海量非结构化数据。
Kleinkram: Open Robotic Data Management
- 模块化本地云系统，支持ROS和MCAP格式数据存储
- 已管理超30TB机器人数据，支持自动化数据验证与评测
- 适合需要统一管理实验数据的机器人科研团队
我们提出Kleinkram，一个免费开源的系统，用于解决大规模非结构化机器人数据管理难题。该系统采用模块化、本地部署的云架构，支持从单个实验到大规模研究数据集的可扩展存储、索引与共享。Kleinkram原生兼容ROS bags和MCAP标准格式，并使用S3兼容存储以提升灵活性。除存储外，系统集成'Action Runner'，可通过自定义Docker工作流实现数据验证、清洗与基准测试。Kleinkram已成功管理超过30 TB来自多样化机器人系统的数据，通过现代化网页界面和强大的命令行接口，显著优化了研究生命周期。
原文摘要 · Abstract (English)
We introduce Kleinkram, a free and open-source system designed to solve the challenge of managing massive, unstructured robotic datasets. Designed as a modular, on-premises cloud solution, Kleinkram enables scalable storage, indexing, and sharing of datasets, ranging from individual experiments to large-scale research collections. Kleinkram natively integrates with standard formats such as ROS bags and MCAP and utilises S3-compatible storage for flexibility. Beyond storage, Kleinkram features an integrated "Action Runner" that executes customizable Docker-based workflows for data validation, curation, and benchmarking. Kleinkram has successfully managed over 30 TB of data from diverse robotic systems, streamlining the research lifecycle through a modern web interface and a robust Command Line Interface (CLI).
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