Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI
Sha Zhang, Suorong Yang, Tong Xie, Xiangyuan Xue, Zixuan Hu, Rui Li, Wenxi Qu, Zhenfei Yin, Tianfan Fu, Di Hu, Andres M Bran, Nian Ran, Bram Hoex, Wangmeng Zuo, Philippe Schwaller, Wanli Ouyang, Lei Bai, Yanyong Zhang, Lingyu Duan, Shixiang Tang, Dongzhan Zhou

TL;DR
This paper advocates for the development of Intelligent Science Laboratories that integrate cognitive and embodied AI to enable autonomous, flexible, and iterative scientific experimentation, overcoming current limitations of AI in research.
Contribution
It introduces the concept of ISLs, a multi-layered framework combining foundation models, agent orchestration, and embodied agents for autonomous scientific discovery.
Findings
Embodied AI advances enable physical experimentation.
Integration of cognitive and embodied AI facilitates autonomous research.
ISLs can support iterative and serendipitous scientific discovery.
Abstract
Scientific discovery has long been constrained by human limitations in expertise, physical capability, and sleep cycles. The recent rise of AI scientists and automated laboratories has accelerated both the cognitive and operational aspects of research. However, key limitations persist: AI systems are often confined to virtual environments, while automated laboratories lack the flexibility and autonomy to adaptively test new hypotheses in the physical world. Recent advances in embodied AI, such as generalist robot foundation models, diffusion-based action policies, fine-grained manipulation learning, and sim-to-real transfer, highlight the promise of integrating cognitive and embodied intelligence. This convergence opens the door to closed-loop systems that support iterative, autonomous experimentation and the possibility of serendipitous discovery. In this position paper, we propose the…
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Taxonomy
TopicsCognitive Science and Mapping
