GPT-enhanced robotic automation platform with user-friendly instruction framework for versatile applications
To address the challenges of hardware integration and system complexity in laboratory automation, this work introduces a universal platform built on two key innovations. First, a standardized instruction framework unifies the control of multi-brand robots by converting complex operations into simple, tabular instructions. Second, a zero-code natural language interface, powered by OpenAI's GPTs platform, translates user commands into executable workflows, which are reviewed by trained domain scientists before execution, with an automated validation mechanism providing an additional safeguard. The platform's performance was validated through complex, multi-device experiments, including an automated Cell Counting Kit-8 (CCK-8) cell viability assay, which yielded results highly consistent with those of manual operations. With a 99.0% success rate in translating natural language test instructions, this work demonstrates a practical framework to assist domain scientists in multi-robot laboratory automation.
Authors
- Litao Shao
- Xiangqing Li (ORCID: https://orcid.org/0000-0003-4820-6334)
- Limiao Yin
- Sai Zhang
- Na Sun
- Zhitao Wang
Institutions
- Harbin University of Science and Technology (CN)
- Harbin University (CN)
- Harbin Engineering University (CN)
- Shandong First Medical University (CN)
- Heilongjiang University (CN)
Publication Details
- Journal
- SLAS TECHNOLOGY
- Published
- 2026-04-17
- DOI
- https://doi.org/10.1016/j.slast.2026.100418
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Shandong Province
- Key Technology Research and Development Program of Shandong