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.

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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

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article

GPT-enhanced robotic automation platform with user-friendly instruction framework for versatile applications

Litao Shao, Xiangqing Li, Limiao Yin, Sai Zhang et al.
SLAS TECHNOLOGY
Robotics and Automated Systems
article

GPT-enhanced robotic automation platform with user-friendly instruction framework for versatile applications

Litao Shao, Xiangqing Li, Limiao Yin, Sai Zhang, Na Sun, Zhitao Wang
article en

Abstract

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.

SLAS TECHNOLOGYVol. 38
Harbin University of Science and Technology (CN), Harbin University (CN), Harbin Engineering University (CN), Shandong First Medical University (CN), Heilongjiang University (CN)
Natural Science Foundation of Shandong Province, Key Technology Research and Development Program of Shandong
Openalex Percentile: Top 19%
Robotics and Automated Systems
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GPT-enhanced robotic automation platform with user-friendly instruction framework for versatile applications — Litao Shao, Xiangqing Li, et al. · SLAS TECHNOLOGY (2026) | TGRS Research Map | TGRS