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<p>Self-driving laboratories (SDLs) combine robotics with algorithmic decision-making to autonomously design, execute, and analyze experiments, and deftly explore the large, high-dimensional parameter spaces that confound conventional experimental approaches. This <i>Perspective</i> examines autonomous robotics’ roles in SDLs, challenges currently limiting generalizability and scalability, and emerging innovations in robotics could address them, thereby highlighting how the integration of advanced robotics could enable far more rapid, reproducible, and accessible experimentation across disciplines.</p>

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The rise of robotics in self-driving labs

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月16日

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  • Christopher H. J. Moran,
  • Jinge Xu,
  • Milad Abolhasani

摘要

Self-driving laboratories (SDLs) combine robotics with algorithmic decision-making to autonomously design, execute, and analyze experiments, and deftly explore the large, high-dimensional parameter spaces that confound conventional experimental approaches. This Perspective examines autonomous robotics’ roles in SDLs, challenges currently limiting generalizability and scalability, and emerging innovations in robotics could address them, thereby highlighting how the integration of advanced robotics could enable far more rapid, reproducible, and accessible experimentation across disciplines.