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Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan

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arxiv 2501.06847 v1 pith:RQZVJYYH submitted 2025-01-12 cs.RO

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
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Kanako Harada Jason Hein Maria H\"ubner Dennis Knobbe Gabriella Pizzuto Florian Shkurti Ruja Shrestha Kerstin Thurow Rafael Vescovi Birgit Vogel-Heuser \'Ad\'am Wolf Naruki Yoshikawa Yan Zeng Zhengxue Zhou Henning Zwirnmann
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classification cs.RO
keywords automationchallengesdiscoverylaboratorynaturalperspectivessciencesciences
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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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