Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan
Andrew I. Cooper, Patrick Courtney, Kourosh Darvish, Moritz Eckhoff,, Hatem Fakhruldeen, Andrea Gabrielli, Animesh Garg, Sami Haddadin, Kanako, Harada, Jason Hein, Maria H\"ubner, Dennis Knobbe, Gabriella Pizzuto, Florian, Shkurti, Ruja Shrestha, Kerstin Thurow, Rafael Vescovi
TL;DR
This paper discusses the potential and challenges of using AI and robotics to automate science laboratories, emphasizing interdisciplinary collaboration to enhance discovery in life sciences and materials.
Contribution
It provides a comprehensive overview of current perspectives, challenges, and future directions in laboratory automation from leading experts across natural sciences.
Findings
Identifies key challenges like robustness, reproducibility, and standardization.
Highlights the importance of interdisciplinary collaboration.
Discusses ethical considerations in automation.
Abstract
Science laboratory automation enables accelerated discovery in life sciences and materials. However, it requires interdisciplinary collaboration to address challenges such as robust and flexible autonomy, reproducibility, throughput, standardization, the role of human scientists, and ethics. This article highlights these issues, reflecting perspectives from leading experts in laboratory automation across different disciplines of the natural sciences.
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