TARMAC as a taxonomy for robot manipulation in chemistry
Abstract Laboratory automation has benefited substantially from well-defined protocols and machine-readable representations of chemical procedures. Yet a long tail of context-dependent physical tasks, including setup, adjustment, and cleanup, continues to require manual intervention or bespoke robotic implementations tailored to individual workflows and platforms. This study examines whether this apparent diversity can be organized into a structured and reusable action space. TARMAC ( TA xonomy for R obot MA nipulation in C hemistry), an empirical taxonomy of laboratory actions, is derived through a bottom-up analysis of instructional chemistry practice. The taxonomy comprises 18 physically meaningful primitives organized by three dimensions: wrench dependence, actuation directness, and motion periodicity. Evaluation through cross-corpus protocol decomposition and robotic instantiation addresses expressive coverage and proof-of-concept executability. Across 23 procedures, 904 of 917 manipulative steps map to the primitive set, while robotic tests instantiate 8 primitives in five tasks across four robotic configurations. Together, these results indicate that laboratory manipulation can be organized as a structured action space across the examined contexts. TARMAC therefore provides a descriptive basis for organizing and comparing manipulation requirements across experimental workflows and robotic embodiments.
Authors
- Barnabas A. Franklin (ORCID: https://orcid.org/0009-0004-6149-9156)
- Tianyuan Wang (ORCID: https://orcid.org/0000-0003-3545-4937)
- Alice Martin (ORCID: https://orcid.org/0000-0002-0939-2042)
- Christopher S. Horbaczewskyj (ORCID: https://orcid.org/0000-0003-2393-0246)
- Ian J. S. Fairlamb (ORCID: https://orcid.org/0000-0002-7555-2761)
- Jihong Zhu (ORCID: https://orcid.org/0000-0001-6830-1211)
- Keting Huang
- Jonathon Pipe
- Andy M. Tyrrell
Publication Details
- Journal
- Communications Chemistry
- Published
- 2026-11-04
- DOI
- https://doi.org/10.1038/s42004-026-02249-3
- Primary Topic
- Robot Manipulation and Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00