PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories

Abstract:Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs). Rather than building a human-centered graphical user interface (GUI) orchestration layer, PUDA creates a command-line runtime environment that lets agents observe, orient, decide, and act over experiments while hardware execution remains deterministic, atomic, and auditable. Headless by design, devices appear through discoverable command-line interfaces, JSON protocols are routed through a distributed messaging system, and command responses, data products, and reports are preserved as structured records. PUDA organizes protocols, runs, samples, measurements, and command logs into an AI-native data structure linked by run identifiers and timestamps, preserving provenance from submitted protocol through hardware response to resulting data products. PUDA separates scientific orchestration from physical operation and data telemetry: agents choose experiments, while PUDA executes validated commands and captures provenance-linked state, responses, and data. The contribution is not another optimizer, orchestrator, or recipe language. It is a practical execution and data environment for agentic SDLs; the broader physical AI implication is that PUDA provides an AI-native hardware harness for AI systems to interact with physical tools.

Materials Science (cond-mat.mtrl-sci); Artificial Intelligence (cs.AI)

arXiv:2607.26464 [cond-mat.mtrl-sci]

(or arXiv:2607.26464v1 [cond-mat.mtrl-sci] for this version)

https://doi.org/10.48550/arXiv.2607.26464 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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