让机器人实验可复现、可信任，通过虚拟实验室与数字孪生追踪执行过程。
Open, Reproducible and Trustworthy Robot-Based Experiments with Virtual Labs and Digital-Twin-Based Execution Tracing
- 用语义化追踪记录传感器数据和机器人信念状态。
- 构建云端虚拟研究大楼，支持大规模实验共享与验证。
- 适合科研人员与机器人开发者提升实验透明度与可复现性。
我们设想一个未来：自主机器人以精确、可重复且开放、可信、透明的方式开展科学实验。为实现这一愿景，本文提出两项关键贡献：一是语义化执行追踪框架，将传感器数据与语义标注的机器人信念状态同步记录，确保自动化实验的透明与可复现；二是AICOR虚拟研究大楼（VRB），一个基于云的平台，支持机器人任务执行的共享、复现与验证。二者结合，通过确定性执行、语义记忆与开放知识表示，实现可复现的机器人驱动科学，为自主系统参与科学发现奠定基础。
原文摘要 · Abstract (English)
We envision a future in which autonomous robots conduct scientific experiments in ways that are not only precise and repeatable, but also open, trustworthy, and transparent. To realize this vision, we present two key contributions: a semantic execution tracing framework that logs sensor data together with semantically annotated robot belief states, ensuring that automated experimentation is transparent and replicable; and the AICOR Virtual Research Building (VRB), a cloud-based platform for sharing, replicating, and validating robot task executions at scale. Together, these tools enable reproducible, robot-driven science by integrating deterministic execution, semantic memory, and open knowledge representation, laying the foundation for autonomous systems to participate in scientific discovery.
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