Goal-Driven Autonomous Optical Experimentation via a Self-Recursive Hardware-Software Harness

Abstract:We propose goal-driven self-recursive optical research in which agents use physical evidence to revise the hardware, software, models, and protocols used to pursue a scientific goal. The framework can be instantiated with different stimulus systems and measurement devices. We formalize its updates and derive a relation between physical attainability, command access, and model approximation error. We demonstrate the concept in an optical see-through color-matching case study using an iPad, RayNeo X3 glasses, and a TOP 300 probe coupled to a CAS140D spectroradiometer, both from Instrument Systems. A revised glasses application adds USB-controlled RGB holds and frame acknowledgements, keeping model-generated colors displayed during spectral acquisition. The interface passes 12 live control checks. Spectral feedback reduces one target color difference from 19.756 to 1.211 {\Delta}E_76^*; all five targets improve in a separate comparison. These measurements demonstrate the concept in one configuration. The resulting software and protocols remain available for subsequent investigations.

Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)

arXiv:2611.04481 [cs.AI]

(or arXiv:2611.04481v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2611.04481 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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