Liquid HandlingControl softwareAutomationCurated metadata

PyLabRobot: An open-source, hardware-agnostic interface for liquid-handling robots and accessories

Not hardware itself, but critical open control layer for heterogeneous open liquid-handling setups.

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Publication data

Crossref and OpenAlex

Publication record

Matched by doi · retrieved 2026-07-21

Abstract

Abstract Liquid handling robots are often limited by proprietary programming interfaces that are only compatible with a single type of robot and operating system, restricting method sharing and slowing development. Here we present PyLabRobot, an open-source, cross-platform Python interface capable of programming diverse liquid-handling robots, including Hamilton STARs, Tecan EVOs, and Opentron OT-2s. PyLabRobot provides a universal set of commands and representations for deck layout and labware, enabling the control of diverse accessory devices. The interface is extensible and can work with any robot that manipulates liquids within a Cartesian coordinate system. We validated the system through unit tests and several application demonstrations, including a browser-based simulator, a position calibration tool, and a path-teaching tool for complex movements. PyLabRobot provides a flexible, open, and collaborative programming environment for laboratory automation. Figure Abstract PyLabRobot overcomes the limitations of proprietary robotic systems. (a) Scientists with access to liquid-handling robots are currently limited by proprietary interfaces that require specialized knowledge, hinder cross-platform operability, and restrict sharing of methods among different robot types. For complex tasks, many researchers need assistance from a specialist familiar with their particular system, most notably when creating or editing protocols. (b) PyLabRobot ( https://github.com/PyLabRobot/pylabrobot ) offers a single interface that allows any person with basic Python skills to program diverse types of liquid-handling robots and share protocols freely, fostering a more collaborative and efficient research environment. The Python API makes it easy to interact with a large scientific computing ecosystem and allows users to leverage large language models for programming assistance.

Bibliographic details

Published
2023-07-10
Journal/source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
DOI
10.1101/2023.07.10.547733
Type
posted-content
Language
en
Volume / issue
Not supplied
Pages
Not supplied
ISSN
Not supplied

Access and metrics

Open access
Yes
OA status
green
License
cc-by
Version
acceptedVersion
Cited by
0
References
23
Retracted
No

Authors and affiliations

  1. Rick P. WierengaLeiden University · Massachusetts Institute of Technology
  2. Stefan GolasMassachusetts Institute of Technology
  3. Wilson HoMassachusetts Institute of Technology
  4. Connor W. ColeyMassachusetts Institute of Technology
  5. Kevin M. EsveltCorresponding authorMassachusetts Institute of Technology

Topics and keywords

Modular Robots and Swarm IntelligenceElectrowetting and Microfluidic TechnologiesSmart Agriculture and AIComputer sciencePython (programming language)RobotInterface (matter)Open sourceExtensibilityEmbedded systemGraphical user interfaceAutomationScripting languageOperating systemHuman–computer interaction