Embodied Science: Closing the Discovery Loop with Agentic Embodied AI

Computer Science > Artificial Intelligence [Submitted on 20 Mar 2026] Embodied Science: Closing the Discovery Loop with Agentic Embodied AI Xiang Zhuang, Chenyi Zhou, Kehua Feng, Zhihui Zhu, Yunfan Gao, Yijie Zhong, Yichi Zhang, Junjie Huang, Keyan Ding, Lei Bai, Haofen Wang, Qiang Zhang, Huajun Chen Artificial intelligence has demonstrated remarkable capability in predicting scientific properties, yet scientific discovery remains an inherently physical, long-horizon pursuit governed by experimental cycles. Most current computational approaches are misaligned with this reality, framing discovery as isolated, task-specific predictions rather than continuous interaction with the physical world. Here, we argue for embodied science, a paradigm that reframes scientific discovery as a closed loop tightly coupling agentic reasoning with physical execution. We propose a unified Perception-Language-Action-Discovery (PLAD) framework, wherein embodied agents perceive experimental environments, reason over scientific knowledge, execute physical interventions, and internalize outcomes to drive subsequent exploration. By grounding computational reasoning in robust physical feedback, this approach bridges the gap between digital prediction and empirical validation, offering a roadmap for autonomous discovery systems in the life and chemical sciences. Comments: Work in progress Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.19782 [cs.AI]   (or arXiv:2603.19782v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.19782 Focus to learn more Submission history From: Xiang Zhuang [view email] [v1] Fri, 20 Mar 2026 09:20:12 UTC (5,617 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)