Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping

by   Gabriella Pizzuto, et al.

The potential use of robotics for laboratory experiments offers an attractive route to alleviate scientists from tedious tasks while accelerating the process of obtaining new materials, where topical issues such as climate change and disease risks worldwide would greatly benefit. While some experimental workflows can already benefit from automation, it is common that sample preparation is still carried out manually due to the high level of motor function required when dealing with heterogeneous systems, e.g., different tools, chemicals, and glassware. A fundamental workflow in chemical fields is crystallisation, where one application is polymorph screening, i.e., obtaining a three dimensional molecular structure from a crystal. For this process, it is of utmost importance to recover as much of the sample as possible since synthesising molecules is both costly in time and money. To this aim, chemists have to scrape vials to retrieve sample contents prior to imaging plate transfer. Automating this process is challenging as it goes beyond robotic insertion tasks due to a fundamental requirement of having to execute fine-granular movements within a constrained environment that is the sample vial. Motivated by how human chemists carry out this process of scraping powder from vials, our work proposes a model-free reinforcement learning method for learning a scraping policy, leading to a fully autonomous sample scraping procedure. To realise that, we first create a simulation environment with a Panda Franka Emika robot using a laboratory scraper which is inserted into a simulated vial, to demonstrate how a scraping policy can be learned successfully. We then evaluate our method on a real robotic manipulator in laboratory settings, and show that our method can autonomously scrape powder across various setups.


page 1

page 6


SOLIS: Autonomous Solubility Screening using Deep Neural Networks

Accelerating material discovery has tremendous societal and industrial i...

Powder-Bot: A Modular Autonomous Multi-Robot Workflow for Powder X-Ray Diffraction

Powder X-ray diffraction (PXRD) is a key technique for the structural ch...

From the DESK (Dexterous Surgical Skill) to the Battlefield – A Robotics Exploratory Study

Short response time is critical for future military medical operations i...

Sample Efficient Robot Learning with Structured World Models

Reinforcement learning has been demonstrated as a flexible and effective...

Toward Process Controlled Medical Robotic System

Medical errors, defined as unintended acts either of omission or commiss...

ARChemist: Autonomous Robotic Chemistry System Architecture

Automated laboratory experiments have the potential to propel new discov...

Please sign up or login with your details

Forgot password? Click here to reset