人机接触运动交互中人体舒适感知的测量方法

Method for Measurement of Human Comfort Perception in Human-robot Interaction

目的完善人机接触运动交互中用户的舒适度测量方法,提高机器人作业的智能感知能力。方法基于机器人按摩作业平台,收集测试者人机接触中皮肤所受的力与变形等作业数据,以及主观触觉感知评价。建立以疼痛感、牵扯感和灼热感为基本维度的三维舒适度感知空间,通过反向传播神经网络建立客观测量数据与人体触觉感知的映射关系;采用支持向量机算法对人体触觉感知进行舒适、不舒适可作业和不舒适需停机分类。结果实验结果显示,触觉感知预测模型和状态分类模型,能有效实现从作业特征信息到触觉感知再到人机作业状态的整体辨识。结论该方法对人机交互过程中的作业特征和人体主观触觉感知进行联系和模式识别,为机器人安全、舒适的作业规划和在线控制提供了有效依据。

The work aims to improve the user comfort measurement method in human-robot interaction and enhance the intelligent perception ability of robots.Based on a robot massage operation platform,measurement data,including the force and deformation of the skin during human-robot interaction,as well as subjective perception evaluation were collected.A three-dimensional comfort perception space based on pain,stretching,and burning sensation was built.Then a mapping relationship between objective measurement data and human perception was established through the back propagation neural network.The support vector machine algorithm was used for comfort classification of human.Results showed that the perception prediction model and state classification model can effectively achieve overall identification from feature information to human perception,and then to comfort identification.This method can be used to connect and recognize the operation characteristics and the subjective perception of human body in human-robot interaction,and provide an effective basis for safe and comfortable operation planning and online control of robots.