Chemistry experimentation is often resource- and labor-intensive. Despite the many benefits incurred by the integration of advanced and special-purpose lab equipment, many aspects of experimentation are still manually conducted by chemists, for example, polishing an electrode in electrochemistry experiments. Traditional lab automation infrastructure faces challenges when it comes to flexibly adapting to new chemistry experiments. To address this issue, we propose a human-friendly and flexible robotic system, ORGANA, that automates a diverse set of chemistry experiments. It is capable of interacting with chemists in the lab through natural language, using Large Language Models (LLMs). ORGANA keeps scientists informed by providing timely reports that incorporate statistical analyses. Additionally, it actively engages with users when necessary for disambiguation or troubleshooting. ORGANA can reason over user input to derive experiment goals, and plan long sequences of both high-level tasks and low-level robot actions while using feedback from the visual perception of the environment. It also supports scheduling and parallel execution for experiments that require resource allocation and coordination between multiple robots and experiment stations. We show that ORGANA successfully conducts a diverse set of chemistry experiments, including solubility assessment, pH measurement, recrystallization, and electrochemistry experiments. For the latter, we show that ORGANA robustly executes a long-horizon plan, comprising 19 steps executed in parallel, to characterize the electrochemical properties of quinone derivatives, a class of molecules used in rechargeable flow batteries. Our user study indicates that ORGANA significantly improves many aspects of user experience while reducing their physical workload. More details about ORGANA can be found at https://ac-rad.github.io/organa/.

翻译：化学实验通常需要大量资源和人力投入。尽管先进及专用实验设备的集成带来了诸多益处，但实验过程中的许多环节仍需化学家手动完成，例如电化学实验中电极的抛光。传统实验室自动化基础设施在灵活适应新型化学实验时面临挑战。为解决这一问题，我们提出了一种人性化且灵活的机器人系统ORGANA，能够实现多种化学实验的自动化。该系统可通过自然语言与实验室中的化学家交互，并借助大型语言模型（LLMs）实现。ORGANA通过提供包含统计分析在内的及时报告，确保科学家获得最新信息。同时，在需要消歧或故障排除时，它会主动与用户互动。该系统能够对用户输入进行推理以推导实验目标，并规划涵盖高层任务和低层机器人动作的长期序列，同时利用环境视觉感知的反馈信息。它还支持需资源分配及多机器人与实验站协调的实验调度与并行执行。我们证明，ORGANA成功完成了多种化学实验，包括溶解度评估、pH测量、重结晶及电化学实验。在电化学实验中，我们展示了ORGANA稳健执行包含19个并行步骤的长期规划，以表征醌类衍生物（一类用于可充电液流电池的分子）的电化学性质。用户研究显示，ORGANA在显著改善用户体验各维度的同时，降低了用户的体力负荷。更多关于ORGANA的详细信息，请访问https://ac-rad.github.io/organa/。