Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis
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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866917375062835200 |
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| author | Deng, Han Zou, Anqi Zhang, Hanling Fei, Ben Zhang, Chengyu Wang, Haobo Guo, Xinru Li, Zhenyu Wang, Xuzhu Yang, Peng Zhang, Fujian Guo, Weiyu Shao, Xiaohong Liu, Zhaoyang Tang, Shixiang Wang, Zhihui Ouyang, Wanli |
| author_facet | Deng, Han Zou, Anqi Zhang, Hanling Fei, Ben Zhang, Chengyu Wang, Haobo Guo, Xinru Li, Zhenyu Wang, Xuzhu Yang, Peng Zhang, Fujian Guo, Weiyu Shao, Xiaohong Liu, Zhaoyang Tang, Shixiang Wang, Zhihui Ouyang, Wanli |
| contents | Scientific discovery increasingly depends on high-throughput characterization, yet automation is hindered by proprietary GUIs and the limited generalizability of existing API-based systems. We present Owl-AuraID, a software-hardware collaborative embodied agent system that adopts a GUI-native paradigm to operate instruments through the same interfaces as human experts. Its skill-centric framework integrates Type-1 (GUI operation) and Type-2 (data analysis) skills into end-to-end workflows, connecting physical sample handling with scientific interpretation. Owl-AuraID demonstrates broad coverage across ten categories of precision instruments and diverse workflows, including multimodal spectral analysis, microscopic imaging, and crystallographic analysis, supporting modalities such as FTIR, NMR, AFM, and TGA. Overall, Owl-AuraID provides a practical, extensible foundation for autonomous laboratories and illustrates a path toward evolving laboratory intelligence through reusable operational and analytical skills. The code are available at https://github.com/OpenOwlab/AuraID. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_29828 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis Deng, Han Zou, Anqi Zhang, Hanling Fei, Ben Zhang, Chengyu Wang, Haobo Guo, Xinru Li, Zhenyu Wang, Xuzhu Yang, Peng Zhang, Fujian Guo, Weiyu Shao, Xiaohong Liu, Zhaoyang Tang, Shixiang Wang, Zhihui Ouyang, Wanli Artificial Intelligence Computation and Language Scientific discovery increasingly depends on high-throughput characterization, yet automation is hindered by proprietary GUIs and the limited generalizability of existing API-based systems. We present Owl-AuraID, a software-hardware collaborative embodied agent system that adopts a GUI-native paradigm to operate instruments through the same interfaces as human experts. Its skill-centric framework integrates Type-1 (GUI operation) and Type-2 (data analysis) skills into end-to-end workflows, connecting physical sample handling with scientific interpretation. Owl-AuraID demonstrates broad coverage across ten categories of precision instruments and diverse workflows, including multimodal spectral analysis, microscopic imaging, and crystallographic analysis, supporting modalities such as FTIR, NMR, AFM, and TGA. Overall, Owl-AuraID provides a practical, extensible foundation for autonomous laboratories and illustrates a path toward evolving laboratory intelligence through reusable operational and analytical skills. The code are available at https://github.com/OpenOwlab/AuraID. |
| title | Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis |
| topic | Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2603.29828 |