A system of AI agents creates experimental protocols for lab robots, tests them in a virtual lab, and directs the physical lab, according to an arXiv preprint.
By Hermes-Vector AI Desk
A system of artificial-intelligence agents can design laboratory procedures for robots, test them in a virtual lab, and direct the robots in a physical lab, according to a preprint posted in October to arXiv that has not been peer reviewed.
A scientist describes their research programme and lab set-up to the agents. The agents then create step-by-step experimental protocols for the lab’s robots and generate a virtual version of the lab to test the protocols. They can then direct the robots in the real lab to perform the research. The agents can also design an entire lab from scratch, using a virtual one to work out the ideal placement for instruments and robots.
In a test, the agents wrote more than 200 commands directing a robotic arm to move between and interact with instruments in an existing lab space. The agent simulated the steps in the virtual lab to ensure that it all worked smoothly, then directed the real-life arm to carry out procedures to measure the optical properties of nanocrystals.
The concept is “very cool” and could drastically reduce the effort required to set up automated labs, says Evan Collins, a bioengineer at the Massachusetts Institute of Technology in Cambridge. But integrating the cameras and sensors that the agents need to direct experiments effectively could require more resources than does setting up a lab manually, he says.
The simulations would make it easy to plan robotic movements that avoid collisions between robots and other objects in the lab, says Collins. Because the agents conduct all the planning and testing in a simulated environment, there is no need for researchers to “babysit the system” after it’s built, says Yuchi (Allan) Zhao, a roboticist at the University of Toronto in Canada and co-author of the preprint.
Setting up an automated lab is often a time-consuming process of trial and error followed by extensive testing and troubleshooting. The system described in the preprint aims to reduce that effort by conducting planning and testing in a simulated environment before directing physical robots.
Sources
This article was drafted with AI assistance and checked against the sources above. Company claims are reported as claims. Cover image is AI-generated.
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