# AlabOS: A Python-based Reconfigurable Workflow Management Framework for Autonomous Laboratories

arXiv: https://arxiv.org/abs/2405.13930 · HTML: https://mlsanity.com/paper/2405.13930/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2024.

## Built on by (most cited first, 10 of 10)

- [El Agente: An Autonomous Agent for Quantum Chemistry](https://mlsanity.com/paper/2505.02484/) (2025)
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- [R-LAM: Reproducibility-Constrained Large Action Models for Scientific Workflow Automation](https://mlsanity.com/paper/2601.09749/) (2026)
- [Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis](https://mlsanity.com/paper/2603.29828/) (2026)
- [LAP: An Agent-to-Instrument Protocol for Autonomous Science](https://mlsanity.com/paper/2606.03755/) (2026)
- [Self-Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers](https://mlsanity.com/paper/2509.05351/) (2025)
- [NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol](https://mlsanity.com/paper/2605.15227/) (2026)
- [From Prompts to Protocols: An AI Agent for Laboratory Automation](https://mlsanity.com/paper/2605.16552/) (2026)
- [Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaboration](https://mlsanity.com/paper/2606.30246/) (2026)
- [PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories](https://mlsanity.com/paper/2607.26464/) (2026)

## Abstract (arXiv)

The recent advent of autonomous laboratories, coupled with algorithms for high-throughput screening and active learning, promises to accelerate materials discovery and innovation. As these autonomous systems grow in complexity, the demand for robust and efficient workflow management software becomes increasingly critical. In this paper, we introduce AlabOS, a general-purpose software framework for orchestrating experiments and managing resources, with an emphasis on automated laboratories for materials synthesis and characterization. AlabOS features a reconfigurable experiment workflow model and a resource reservation mechanism, enabling the simultaneous execution of varied workflows composed of modular tasks while eliminating conflicts between tasks. To showcase its capability, we demonstrate the implementation of AlabOS in a prototype autonomous materials laboratory, A-Lab, with around 3,500 samples synthesized over 1.5 years.