Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation

The orchestration software (OS) for controlling self-driving laboratories (SDLs) has been advanced significantly in recent years. We developed NIMO (formerly NIMS-OS, NIMS Orchestration System), an OS explicitly designed to integrate multiple artificial intelligence (AI) algorithms with diverse exploratory objectives. NIMO provides a framework for integrating AI into robotic experimental systems that are controlled by other OS platforms based on both Python and non-Python languages. In this study, we demonstrate the realization of an SDL via NIMO by integrating AI into a legacy robotic system. As a proof of concept, we integrated an automated liquid handling system controlled by a Visual Basic (VB) program into the SDL through NIMO and performed parameter optimization of the dispensing process using Bayesian optimization, thereby enabling autonomous and automated experiments. NIMO facilitates AI integration through straightforward file exchanges, ensuring compatibility with robotic experimental systems programmed in non-Python languages such as VB and LabVIEW, as well as SDLs managed by other OS platforms. We anticipate that NIMO’s ability to support a broad spectrum of AI-driven autonomous experiments will significantly enhance the functionality and versatility of SDLs.