Self-building labs create flexible robot experiment setups automatically
Self-Building Labs
Artificial IntelligenceMultiagent SystemsRobotics
Summary
Usually, labs with robots can only do experiments they were set up for, and changing them for new experiments takes a lot of work. The authors designed a system called self-building laboratory (SBL) that can start from scratch or an existing lab and figure out how to build and run the right setup automatically. This includes designing the layout, programming robot actions, and organizing experiments based on a scientist’s goals. They tested SBL on real chemistry experiments involving tiny particles and showed it can work with multiple robots. This way, scientists just say what they want to study, and the lab builds itself to do it.
What this means in practice
- •For laboratory automation engineers: Enable automatic creation and configuration of flexible robotic lab setups for diverse scientific experiments without manual reprogramming.
- •For chemical process developers: Use self-building labs to quickly set up robotic experimentation environments for chemical synthesis workflows with minimal initial infrastructure.
Authors
Jiaru Bai, Yuchi Zhao, Han Hao, Miroslav Bogdanovic, Yang Cao, Varinia Bernales, Alán Aspuru-Guzik
Abstract
Self-driving laboratories (SDLs) accelerate scientific discovery by automating experimental execution and optimization. AI agents can increasingly propose new experiments, but existing SDLs can only run the procedures they were built for. Adapting them to a new experiment still takes extensive manual engineering, which makes laboratory flexibility the bottleneck for scaling discovery. We introduce the self-building laboratory (SBL), which designs, configures, and operates its own laboratory setup given a high-level scientific goal. SBL starts from whatever already exists, from an empty room to a working SDL, and builds the missing capabilities: the lab layout, its digital twin, robot skills, and experimental workflows. We demonstrate the system working across different robots and setups, scaling from a single workstation to laboratories with several robots working together. We validate SBL's end-to-end capabilities through a real-world quantum-dot synthesis experiment. By shifting the role of human researchers from manually configuring and programming device automation to specifying scientific objectives, SBL makes scientific automation more accessible, flexible, and scalable. Project website: https://self-building-labs.github.io/