Issue 11, 2025

The 2D-drone swarm, a safe open-source sample transfer system for fully automated laboratories

Abstract

Laboratory automation is an active field in biology, drug discovery, and more recently in synthetic chemistry and materials science. Local automation has existed in the field for quite some time, but long-range or total laboratory automation is much less developed. In this article, we present a complete, open and decentralized global automation system called the 2D drone swarm system. It is based on a simple approach of small mobile robots moving autonomously in a dedicated track suspended above the scientific equipment for the long-distance sample and closely connected to localized robotic arms dedicated to short-distance transfers, interaction with scientific equipment and direct sample processing. This approach is inspired by the Kiva/Amazon model, where isolated autonomous mobile robots automatically deliver goods to external operators. It is also inspired by the modern automotive industry, such as Tesla's Gigafactories, to provide an evolutionary and flexible system that can adapt to numerous types of tasks with a minimum amount of resources and easily adapt to different types of workstations. This global automation system is controlled directly from the Laboratory Scheduler by a Robot Subscheduler, coded in an open-source environment, which takes care of all mobile and local robot operations. The result is an operator and scientific equipment safe, cost and energy-efficient, easily extensible and open-source global laboratory automation system that can be adapted to many different applications and laboratories.

Graphical abstract: The 2D-drone swarm, a safe open-source sample transfer system for fully automated laboratories

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Article information

Article type
Paper
Submitted
04 Aug 2025
Accepted
02 Oct 2025
First published
17 Oct 2025
This article is Open Access
Creative Commons BY license

Digital Discovery, 2025,4, 3162-3174

The 2D-drone swarm, a safe open-source sample transfer system for fully automated laboratories

E. Mariano, Y. Coderey, Y. El Goumi, J. Tan, T. Cavagna, J. Cousty, V. Scamarcio, J. Hughes and P. Miéville, Digital Discovery, 2025, 4, 3162 DOI: 10.1039/D5DD00342C

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