Accelerating laboratory automation through robot skill learning

Transforming materials discovery plays a pivotal role in addressing global challenges. The applications of new materials could range from clean energy storage, to sustainable polymers and packaging for consumer products towards a more circular economy, to drugs and therapeutics. Stemming from the COVID-19 pandemic, where scientists had to halt experiments due to stringent social distancing measures or accelerate their efforts towards quickly producing a vaccine, there has recently been an increased interest in using robotics and automation in laboratory environments. The challenge here is that laboratories have been designed by and for humans and thus the available glassware, tools and equipment pose difficult problems for traditional automation methods that are inherently open loop and not adaptable. Learning-based methods that rely on autonomous trial and error are increasingly being used to achieve robotic tasks that could not be previously addressed with automation.