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Localization, inspection, and reasoning (LIRA) module for autonomous workflows in self-driving laboratories
Zhengxue Zhou1,2, Satheeshkumar Veeramani1, Francisco Munguia-Galeano1
1Department of Chemistry and Materials Innovation Factory, University of Liverpool, Liverpool, United Kingdom.
Communications Chemistry
|November 29, 2025
Summary
Self-driving labs (SDLs) now feature enhanced robotic decision-making with LIRA (Localization, Inspection, and Reasoning). This AI module improves reliability and efficiency in autonomous experimentation by enabling real-time error correction.
Area of Science:
- Robotics
- Artificial Intelligence
- Laboratory Automation
Background:
- Self-driving labs (SDLs) utilize robotic automation and AI for high-throughput experimentation.
- Current SDL workflows often lack real-time error detection and correction in robot manipulation, reducing reliability and efficiency.
Purpose of the Study:
- To introduce LIRA (Localization, Inspection, and Reasoning), an edge computing module designed to enhance robotic decision-making in SDLs.
- To enable robots to dynamically adapt to workflow variations through precise localization, automated inspection, and reasoning.
Main Methods:
- Integration of LIRA with a client-server framework for remote vision inspection and multi-platform communication.
- Utilizing vision-language models (VLMs) within LIRA for enhanced robotic perception and decision-making.
Main Results:
- LIRA demonstrated high localization accuracy and a tenfold reduction in localization time.
- Achieved real-time inspection capabilities across diverse experimental tasks, significantly improving autonomous workflow efficiency and robustness.
- LIRA operates as an open-source solution, promoting accessibility and adoption.
Conclusions:
- LIRA enhances the reliability, efficiency, and flexibility of autonomous workflows in self-driving labs.
- Facilitates AI-driven automation, advancing towards intelligent and resilient laboratory environments.
- Aims to accelerate scientific discovery through improved human-machine collaboration.
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