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<p>Laboratory robotics is advancing from routine automation toward autonomous systems capable of intelligent decision-making and flexible execution. This perspective outlines key milestones and introduces the ADePT framework, which defines four core dimensions of robotic capability proficiency: adaptability and learning, dexterity, perception, and task complexity. We discuss future directions for self-driving laboratories, including robot-centric, end-to-end robotic integration, and collaborative human–robot environments. These scenarios highlight the importance of technological enablers and evolving regulatory paradigms. By connecting present technologies to emerging system configurations, this work offers a foundation for designing autonomous laboratory ecosystems that support scientific discovery and operational efficiency.</p><p></p>

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The ADePT framework for assessing autonomous laboratory robotics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月20日

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  • Pablo Salazar-Villacis,
  • Brahim Benyahia

摘要

Laboratory robotics is advancing from routine automation toward autonomous systems capable of intelligent decision-making and flexible execution. This perspective outlines key milestones and introduces the ADePT framework, which defines four core dimensions of robotic capability proficiency: adaptability and learning, dexterity, perception, and task complexity. We discuss future directions for self-driving laboratories, including robot-centric, end-to-end robotic integration, and collaborative human–robot environments. These scenarios highlight the importance of technological enablers and evolving regulatory paradigms. By connecting present technologies to emerging system configurations, this work offers a foundation for designing autonomous laboratory ecosystems that support scientific discovery and operational efficiency.