arXiv:2607.20662cs.ROcond-mat.mtrl-sci2026-07

用千元级3D打印机改造出可远程监控的自动化液体处理机器人。

Scalable Low-Cost Laboratory Automation: A Digital Twin-Integrated Robotic Platform for Autonomous Liquid Handling (RAINBOT)

论文配图:Scalable Low-Cost Laboratory Automation: A Digital Twin-Integrated Robotic Platform for Autonomous Liquid Handling (RAINBOT)
图 1 · 摘自论文原文
  • 将消费级3D打印机改装为带精确移液功能的机器人,通过Python控制
  • 数字孪生系统实现远程实时监控与紧急停机,误差仅2个百分点
  • 适合实验室自动化入门者、低成本科研团队及人机协作实验设计

实验室自动化加速科学发现,但受限于商业液体处理系统的高成本、专有设计和远程监控能力不足。本文提出RAINBOT™,一种基于消费级笛卡尔3D打印机(Elegoo Neptune 4 Max)改造的低成本、可公开复现的液体处理机器人。将打印机挤出头替换为由打印机自身G-code驱动的X-Y-Z龙门架控制的精密单通道移液器,通过两个小型线性执行器在Python控制下完成活塞与吸头弹出动作。为实现实验透明化与远程可监督性,构建了基于浏览器的双向数字孪生系统,实时同步物理平台的运动学与移液状态,支持任意网页端的远程监控、干预与紧急停止。作为概念验证,RAINBOT™完成了不同颜色水溶液的顺序交换,集成色传感器量化混合结果;测得的红、黄、蓝(RYB)响应值与预期混合行为的平均绝对误差仅为2个百分点,验证了执行准确性和实时追踪能力。进一步将平台与CEID™(协同逆向设计探索框架)耦合,将实验从手动试错转变为有目标的逆向设计搜索,同时保持人类参与。全套硬件成本低于1300美元,约为入门级商用设备的十分之一,建立了一个可访问的物理-虚拟自驱动实验室自动化框架。

原文摘要 · Abstract (English)

Laboratory automation accelerates discovery, yet its adoption is constrained by the high cost, proprietary design, and limited remote supervisability of commercial liquid-handling systems. This work presents RAINBOT\textsuperscript{TM}, a low-cost, openly reproducible liquid-handling robot built by converting a consumer-grade Cartesian 3D printer (Elegoo Neptune 4 Max). The printer extruder is replaced by a precision single-channel pipette actuated through the printer's own G-code-driven X--Y--Z gantry, with plunger and tip-eject motions effected by two compact linear actuators under Python control. To make experiments transparent and remotely supervisable, a browser-based digital twin is implemented to synchronise bidirectionally with the physical platform, mirroring kinematics and pipetting states in real time and exposing remote monitoring, intervention, and an emergency stop from any web browser. As a proof of concept, RAINBOT\textsuperscript{TM} performed sequential exchanges of differently coloured aqueous solutions while an integrated colour sensor quantified the resulting mixtures; measured red, yellow, and blue (RYB) responses agreed with expected mixing behaviour to within a mean absolute error of two percentage points, validating correct execution and real-time tracking. Closing the loop, the platform is coupled to the CEID\textsuperscript{TM} (Cooperative Explorer for Inverse Design) framework, which recasts experimentation from iterative manual guessing into a goal-directed inverse-design search while keeping a human in the loop. The complete hardware costs under US\$1300, which is roughly an order of magnitude below entry-level commercial handlers, thereby establishing an accessible physical--virtual framework for self-driving laboratory automation.

实验室自动化数字孪生低成本机器人移液机器人

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