Towards Robotic Laboratory Automation Plug & Play: The "LAPP" Framework

TL;DR

This paper proposes a flexible, standardized framework for integrating diverse laboratory devices into automated pharmaceutical systems using mobile manipulators, vision, and cloud-based device interface learning.

Contribution

It introduces the LAPP framework enabling plug-and-play integration of lab devices through vision and cloud-based interface learning, addressing industry-specific challenges.

Findings

Concept of device pose learning with vision and barcodes

Use of a universal cloud database for device interface info

Standardization approach for diverse lab devices

Abstract

Increasing the level of automation in pharmaceutical laboratories and production facilities plays a crucial role in delivering medicine to patients. However, the particular requirements of this field make it challenging to adapt cutting-edge technologies present in other industries. This article provides an overview of relevant approaches and how they can be utilized in the pharmaceutical industry, especially in development laboratories. Recent advancements include the application of flexible mobile manipulators capable of handling complex tasks. However, integrating devices from many different vendors into an end-to-end automation system is complicated due to the diversity of interfaces. Therefore, various approaches for standardization are considered in this article, and a concept is proposed for taking them a step further. This concept enables a mobile manipulator with a vision system to "learn" the pose of each device and - utilizing a barcode - fetch interface information from a universal cloud database. This information includes control and communication protocol definitions and a representation of robot actions needed to operate the device. In order to define the movements in relation to the device, devices have to feature - besides the barcode - a fiducial marker as standard. The concept will be elaborated following appropriate research activities in follow-up papers.