The Experiment Orchestration System (EOS): Comprehensive Foundation for Laboratory Automation
Angelos Angelopoulos, Cem Baykal, Jade Kandel, Matthew Verber, James Cahoon, Ron Alterovitz
Abstract
As scientific research in chemistry, materials science, and applied sciences becomes increasingly complex and data-driven, there is a growing need for efficient, scalable, and flexible automation to accelerate discoveries and reduce human burden and error in laboratories. We introduce the Experiment Orchestration System (EOS), an open-source software framework and runtime offering a comprehensive foundation for laboratory automation. EOS offers an extensible framework allowing users to define labs, devices, tasks, experiments, and optimization criteria using YAML and Python plugins, and also offers a distributed runtime for managing and executing automation. EOS has a central orchestrator that communicates with and controls laboratory equipment to execute tasks. EOS implements autonomous experiment campaigns, parameter optimization, task scheduling, result aggregation, and more. By providing a common infrastructure for laboratory automation, EOS aims to reduce automation implementation barriers and accelerate discoveries in science laboratories.
BibTeX
@inproceedings{icra2025_theexperimentorc,
title = {The Experiment Orchestration System (EOS): Comprehensive Foundation for Laboratory Automation},
author = {Angelos Angelopoulos and Cem Baykal and Jade Kandel and Matthew Verber and James Cahoon and Ron Alterovitz},
booktitle = {ICRA 2025},
year = {2025}
}