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This paper establishes a computable representation of physical laboratories through the use of typed research objects and a compositional workflow algebra, enabling the expression of scientific workflows as programs that account for evolving laboratory states. The approach allows for the generation of capability-relative workflows and utilizes stateful simulation to verify operation preconditions and laboratory constraints, thus ensuring reliable execution. Key results demonstrate the framework's application in a modular robotic laboratory, paving the way for end-to-end autonomous scientific discovery.
Transforming physical laboratories into computable entities could revolutionize how we automate scientific discovery and verification.
Making science computable requires representations of both scientific knowledge and the physical world in which scientific claims are tested. A computable representation of the physical laboratory is established through typed research objects, capability-bound operations and a compositional workflow algebra. It provides the physical-world counterpart to machine-readable knowledge, expressing workflows as programs over evolving laboratory states with explicit dependencies, decisions, iteration and concurrency. The representation was implemented in a modular agentic robotic laboratory by binding formal operations to executable Function Skills. For diverse scientific intents, capability-relative workflows were generated, while stateful simulation propagated object transformations and verified operation preconditions and laboratory constraints before dispatch. The proposed representation and its engineering framework jointly establish a general computational interface between agent reasoning and capability-bound physical transformations, providing a foundation for end-to-end autonomous scientific discovery.
