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
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909454592638976 |
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| author | Cooper, Andrew I. Courtney, Patrick Darvish, Kourosh Eckhoff, Moritz Fakhruldeen, Hatem Gabrielli, Andrea Garg, Animesh Haddadin, Sami Harada, Kanako Hein, Jason Hübner, Maria Knobbe, Dennis Pizzuto, Gabriella Shkurti, Florian Shrestha, Ruja Thurow, Kerstin Vescovi, Rafael Vogel-Heuser, Birgit Wolf, Ádám Yoshikawa, Naruki Zeng, Yan Zhou, Zhengxue Zwirnmann, Henning |
| author_facet | Cooper, Andrew I. Courtney, Patrick Darvish, Kourosh Eckhoff, Moritz Fakhruldeen, Hatem Gabrielli, Andrea Garg, Animesh Haddadin, Sami Harada, Kanako Hein, Jason Hübner, Maria Knobbe, Dennis Pizzuto, Gabriella Shkurti, Florian Shrestha, Ruja Thurow, Kerstin Vescovi, Rafael Vogel-Heuser, Birgit Wolf, Ádám Yoshikawa, Naruki Zeng, Yan Zhou, Zhengxue Zwirnmann, Henning |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_06847 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan Cooper, Andrew I. Courtney, Patrick Darvish, Kourosh Eckhoff, Moritz Fakhruldeen, Hatem Gabrielli, Andrea Garg, Animesh Haddadin, Sami Harada, Kanako Hein, Jason Hübner, Maria Knobbe, Dennis Pizzuto, Gabriella Shkurti, Florian Shrestha, Ruja Thurow, Kerstin Vescovi, Rafael Vogel-Heuser, Birgit Wolf, Ádám Yoshikawa, Naruki Zeng, Yan Zhou, Zhengxue Zwirnmann, Henning Robotics 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. |
| title | Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan |
| topic | Robotics |
| url | https://arxiv.org/abs/2501.06847 |