Work

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

Year: 2026

Type: article

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.

Source: SLAS TECHNOLOGY

DOI: 10.1016/j.slast.2026.100418

Authors: Zhitao Wang, Sai Zhang, Litao Shao, Limiao Yin, Na Sun, Xiangqing Li

Institutions: Shandong First Medical University, Harbin University of Science and Technology

Language: English

Topic: Robotics and Automated Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,070