Embodied Intelligence Enables Agentic Exploration in Microscopy

Microscopy has fundamentally transformed our understanding of life; however, despite relentless technological iteration, its underlying operational paradigm remains strikingly static. Current instruments persist as passive data collectors, rigidly executing predefined commands while remaining blind to the stochastic and dynamic nature of biological systems. This reliance on passive observation creates a semantic gap between high-level scientific inquiry and physical execution, limiting the generalizability in adapting to uncertain tasks or dynamic biological events. To bridge this gap, we present an Embodied Intelligence Microscope System (EIMS) that reconceptualizes the microscope as an autonomous robot capable of active exploration. By physically grounding the reasoning capabilities of intelligent system, EIMS closes the loop between scientific intent, physical perception, and action, enabling a transition from hypothesis-driven verification to discovery-driven explore. The system achieves zero-shot generalization across complex, multi-step tasks and can autonomously formulate experimental protocols, navigate unknown spatiotemporal environments to locate regions of interest, and dynamically optimizes imaging parameters in real-time to resolve ambiguity. This work establishes a new paradigm for self-driving instruments, providing a generalizable framework where embodied intelligence acts not merely as a tool, but as an active partner in autonomous scientific discovery.