Towards robotic laboratory automation plug & play: Reference architecture model for robot integration.

Supportive robotic solutions take over mundane, but essential tasks from human workforce in biomedical research and development laboratories. The newest technologies in collaborative and mobile robotics enable the utilization in the human-centered and low-structured environment. Their adaptability, however, is hindered by the additional complexity that they introduce. In our paper we aim to entangle the convoluted laboratory robot integration architectures. We begin by hierarchically decomposing the laboratory workflows, and mapping the activity representations to layers and components of the automation control architecture. We elaborate the framework in detail on the example of pick-and-place labware transportation - a crucial supportive step, which we identified as the number one area of interest among experts of the field. Our concept proposal serves as a reference architecture model, the key principles of which were used in reference implementations, and are in line with international standardization efforts.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Adam Wolf reports financial support was provided by Baxalta Innovations GmbH. Adam Wolf reports financial support was provided by Obuda University Doctoral School of Applied Informatics and Applied Mathematics. Peter Galambos reports financial support was provided by National Research, Development and Innovation Fund of Hungary. Karoly Szell reports financial support was provided by National Research, Development and Innovation Fund of Hungary. Adam Wolf reports a relationship with Association Consortium Standardization in Lab Automation (SiLA) that includes: board membership. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)