{"ID":2851543,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.19289","arxiv_id":"2510.19289","title":"TARMAC: A Taxonomy for Robot Manipulation in Chemistry","abstract":"Chemistry laboratory automation aims to increase throughput, reproducibility, and safety, yet many existing systems still depend on frequent human intervention. Advances in robotics have reduced this dependency, but without a structured representation of the required skills, autonomy remains limited to bespoke, task-specific solutions with little capacity to transfer beyond their initial design. Current experiment abstractions typically describe protocol-level steps without specifying the robotic actions needed to execute them. This highlights the lack of a systematic account of the manipulation skills required for robots in chemistry laboratories. To address this gap, we introduce TARMAC - a Taxonomy for Robot Manipulation in Chemistry - a domain-specific framework that defines and organizes the core manipulations needed in laboratory practice. Based on annotated teaching-lab demonstrations and supported by experimental validation, TARMAC categorizes actions according to their functional role and physical execution requirements. Beyond serving as a descriptive vocabulary, TARMAC can be instantiated as robot-executable primitives and composed into higher-level macros, enabling skill reuse and supporting scalable integration into long-horizon workflows. These contributions provide a structured foundation for more flexible and autonomous laboratory automation. More information is available at https://tarmac-paper.github.io/","short_abstract":"Chemistry laboratory automation aims to increase throughput, reproducibility, and safety, yet many existing systems still depend on frequent human intervention. Advances in robotics have reduced this dependency, but without a structured representation of the required skills, autonomy remains limited to bespoke, task-sp...","url_abs":"https://arxiv.org/abs/2510.19289","url_pdf":"https://arxiv.org/pdf/2510.19289v1","authors":"[\"Kefeng Huang\",\"Jonathon Pipe\",\"Alice E. Martin\",\"Tianyuan Wang\",\"Barnabas A. Franklin\",\"Andy M. Tyrrell\",\"Ian J. S. Fairlamb\",\"Jihong Zhu\"]","published":"2025-10-22T06:46:46Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[\"Generative Adversarial Network\"]","has_code":false}