多智能体机器人平台实现化学实验的自适应执行与实时调控
AgentChemist: A Multi-Agent Experimental Robotic Platform Integrating Chemical Perception and Precise Control
- 多智能体协作分解任务，动态调度并根据实验状态实时调整
- 酸碱滴定验证中实现自主进度追踪与精准液体控制
- 适合需要灵活应对复杂、罕见实验场景的科研团队
化学实验室自动化长期受限于固定流程和对长尾实验任务的适应性差。现有平台在标准化操作上表现良好，但面对多样化、低频且不断变化的真实实验时，难以泛化至新反应条件、非常规仪器配置及意外流程变异。我们提出一个集成化学感知与精确控制的多智能体机器人平台，通过协作任务分解、动态调度与自适应控制，解决长尾挑战。系统结合实时反应监测与反馈驱动执行，可根据实验状态动态调整行为而非依赖预设脚本。酸碱滴定实验验证了其自主进度跟踪、自适应加液控制及端到端可靠执行能力。该平台提升了在多样实验室场景中的泛化性能，为智能、灵活、可扩展的实验室自动化提供了实用路径。
原文摘要 · Abstract (English)
Chemical laboratory automation has long been constrained by rigid workflows and poor adaptability to the long-tail distribution of experimental tasks. While most automated platforms perform well on a narrow set of standardized procedures, real laboratories involve diverse, infrequent, and evolving operations that fall outside predefined protocols. This mismatch prevents existing systems from generalizing to novel reaction conditions, uncommon instrument configurations, and unexpected procedural variations. We present a multi-agent robotic platform designed to address this long-tail challenge through collaborative task decomposition, dynamic scheduling, and adaptive control. The system integrates chemical perception for real-time reaction monitoring with feedback-driven execution, enabling it to adjust actions based on evolving experimental states rather than fixed scripts. Validation via acid-base titration demonstrates autonomous progress tracking, adaptive dispensing control, and reliable end-to-end experiment execution. By improving generalization across diverse laboratory scenarios, this platform provides a practical pathway toward intelligent, flexible, and scalable laboratory automation.
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