自动化实验室工作流程中的移动机器人

IF 2.5 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology Pub Date : 2025-02-01 DOI:10.1016/j.slast.2024.100240

J. Huang , H. Liu , S. Junginger , K. Thurow

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引用次数: 0

摘要

生命科学实验室工作流程的自动化对于优化研究设施的效率和准确性变得越来越重要。在本文中，我们提出了一种新的范例，将磨料自动导引车（AGV）集成到生命科学自动化中心（CELISCA）的多层实验室工作流程中，它可以在两层楼的不同工作台之间运输实验室设备和材料。SAMI （Beckman Coulter, California, usa）派遣移动机器人连接高度分布的仪器设备，实现无缝高效的实验室材料自动化运输。MOLAR机器人具有与实验室基础设施交互的能力，包括电梯、自动门、工作台和高级控制系统。这种创新的范例代表了在智能实验室环境中使用移动机器人执行运输任务的综合解决方案，在实际应用中展示了一致的稳定性和卓越的有效性。

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Mobile robots in automated laboratory workflows

The automation of life science laboratory workflows is becoming increasingly important for optimizing efficiency and accuracy in research facilities. In this paper, we present a new paradigm for the integration of MOLAR Automated Guided Vehicles (AGV) into multi-floor laboratory workflows at the Center for Life Science Automation (CELISCA), which transports labware and materials between different workbenches across two floors. SAMI (Beckman Coulter, California, United States) sends mobile robots to connect highly distributed instrument equipment, enabling seamless and efficient laboratory material automated transportation. The MOLAR robot has the capability to interact with laboratory infrastructure, including elevators, automatic doors, workbenches, and the high-level control system. This innovative paradigm represents a comprehensive solution for executing transportation tasks in an intelligent laboratory environment using mobile robots, demonstrating consistent stability and exceptional effectiveness in real-world applications.

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来源期刊

SLAS Technology Computer Science-Computer Science Applications

CiteScore

6.30

自引率

7.40%

发文量

审稿时长

106 days

期刊介绍： SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.