园区机器人性能标准化检测系统研究

摘要：

【目的】针对园区机器人性能检测中标准适配性不足、场景复现与现行标准脱节、检测流程无标准化闭环的问题，明确标准化检测体系构建需求，为检测标准化落地及智慧园区安全运营提供技术支撑。【方法】基于国内外机器人与低速自动驾驶测试标准，解构园区典型工况与标准核心要求，研发标准化一体化检测平台，构建完整检测技术流程。【结果】构建园区机器人性能标准化检测系统，实现标准与场景匹配及检测全流程闭环，解决传统检测与标准脱节、结果不可追溯难题。【结论】该系统可提升检测规范性、准确性和可追溯性，满足标准化需求，为智慧园区机器人安全运营提供保障。

Abstract:

[Objective] To address the core issues in the performance test of robots in parks, such as insufficient standard adaptability, disconnection between scenario reproduction and standards, and failure to form a standardized closedloop testing process, this research clarifies the construction needs of a standardized testing system, so as to provide technical support for the standardized implementation of park robot testing and the safe operation of smart parks. [Methods] Based on domestic and international testing standards for robots and low-speed autonomous driving, this research deconstructs the typical working conditions of parks and the core technical requirements of standards, develops a standardized integrated testing platform, and constructs a complete technical process covering standard interpretation, scenario construction, automated testing, and compliance judgment. [Results] A standardized performance testing system for park robots is constructed, which can achieve the matching between standards and testing scenarios, complete the closed-loop of the entire automated testing process, and effectively solve the practical problems of traditional testing being disconnected from standards and untraceable testing results. [Conclusion] The standardized testing system can improve the standardization, accuracy and traceability of park robot performance testing, meet the needs of standardized implementation of park robot testing, and provide reliable technical support for the safe and orderly operation of robots in smart parks.

引用格式：许文倩. 园区机器人性能标准化检测系统研究[J]. 标准化学报，2026(8)：46-53.

基金项目：本文受福建省市场监督管理局科技项目“园区复杂场景自动驾驶感知设备一体化智能检测装置研发与应用”（项目编号：FJMS2024030）；2026年度福建省科学技术厅科技人员育成项目“人机交互地面移动机器人检测系统”（项目编号：2026350177）资助。

作者简介：许文倩，硕士，工程师，研究方向为特种机器人检验检测、自动化技术。