自动化数据采集和分析方法支持下的学前陪伴机器人性能评估  

Performance evaluation of preschool companion robots supported by automateddata collection and analysis methods

作　　者：黄艳雁[1] 姚金秀[1] HUANG Yanyan;YAO Jinxiu(Guangxi Vocational&Technical Institute of Industry,Nanning 530001,China)

机构地区：[1]广西工业职业技术学院,南宁530001

出　　处：《自动化与仪器仪表》2024年第6期199-202,共4页Automation & Instrumentation

基　　金：2022年度广西职业教育教学改革研究项目《专业认证视域下学前教育专业教学过程质量监控及评价机制研究》(GXGZJG2022B034)。

摘　　要：研究采用自动化数据采集和分析,建立全面的学前陪伴机器人互动模型。注重有形交互设计,考虑双目立体视觉测量模型。结果显示FDMF消噪算法在频域中值方差0.421时效果最佳。专家评分反映机器人在教育和个性化适应方面良好,评分范围85分~97分,个性化适应最低80分,总体最高96分。用户整体满意度80分以上,尤其在双目立体视觉测量模型下的交互反应时间方面表现出色,这为学前教育提供了重要参考。The research uses automated data collection and analysis to establish a comprehensive preschool companion robot interaction model.Focus on tangible interaction design and consider the binocular stereoscopic vision measurement model.The results show that the FDMF denoising algorithm works best when the median variance in the frequency domain is 0.421.Expert scores reflect that the robot is good in education and personalized adaptation,with scores ranging from 85 to 97 points,with a minimum of 80 points for personalized adaptation and an overall maximum of 96 points.The overall user satisfaction score is above 80 points,especially in terms of interactive reaction time under the binocular stereoscopic vision measurement model.This provides an important reference for preschool education.

关 键 词：数据采集 性能分析 学前教育 陪伴机器人 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置]