{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Salazar-Villacis P"],"funding":["RCUK | Engineering and Physical Sciences Research Council (EPSRC)","EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)"],"pagination":["99"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12923569"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9(1)"],"pubmed_abstract":["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 di"],"journal":["Communications chemistry"],"pubmed_title":["The ADePT framework for assessing autonomous laboratory robotics."],"pmcid":["PMC12923569"],"funding_grant_id":["101057430","EP/V062077/1"],"pubmed_authors":["Salazar-Villacis P","Benyahia B"],"additional_accession":[]},"is_claimable":false,"name":"The ADePT framework for assessing autonomous laboratory robotics.","description":"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 di","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Feb","modification":"2026-07-16T14:50:01.081Z","creation":"2026-07-09T11:02:57.485Z"},"accession":"S-EPMC12923569","cross_references":{"pubmed":["41720921"],"doi":["10.1038/s42004-026-01932-9"]}}