Roughness evaluation by wearable tactile sensor utilizing human active sensing
Roughness evaluation by wearable tactile sensor utilizing human active sensing
复制标题
利用人体主动传感的可穿戴触觉传感器评估粗糙度
DOI：
10.1299/mej.15-00460
复制
发表时间：
2016
影响因子：
4.4
通讯作者：
A. Sano
中科院分区：
文献类型：
--
作者：
Yoshihiro Tanaka;Yuichiro Ueda;A. Sano
人类可以评估各种形状表面的粗糙度。传统的粗糙度测量传感器难以应用于曲面或小型产品的表面。在本文中，一个简单的触觉传感器，利用人类的能力，触觉双向性的基础上开发的粗糙度评价。人类可以在感知触觉的同时移动手指，并根据触觉感知和任务目标改变接触力，扫描速度，方向等探索性运动。我们开发的传感器是由两个麦克风，并安装在人的指尖。它允许用户在没有触觉障碍的情况下触摸对象。用户可以应用传感器，同时保持他们正常的触觉感知，并同时获得基于手指和物体之间的机械相互作用的振动和声音。首先，研究了接触力和扫描速度对传感器输出的影响。实验结果表明，传感器输出随接触力的增加而增加，但扫描速度的影响因人而异。在此基础上，分别对平面和曲面进行了粗糙度评定实验。施加恒定的法向力和扫描速度，并通过使用中等粗糙度样品的传感器输出来校准所收集的传感器输出。结果表明，该传感器能够在相同的等级下评估平面和曲面的粗糙度。
Humans can evaluate roughness on various shaped surfaces. Conventional roughness measurement sensors are difficult to apply to curved surface or small product's surface. In this paper, a simple tactile sensor utilizing human ability based on haptic bidirectionality is developed for the roughness evaluation. Humans can move their fingers while perceiving tactile sensations and change exploratory movements like contact force, scanning velocity, direction, etc. according to haptic perception and task objective. Our developed sensor is composed of two microphones and is mounted on a human fingertip. It allows users to touch the object without haptic obstruction. Users can apply the sensor while retaining their normal haptic perception and simultaneously obtaining vibrations and sound based on the mechanical interaction between the finger and the object. First, influence of contact force and scanning velocity on the sensor output is investigated. The experimental results show that the sensor output increases with a rise in the contact force but the influence of the scanning velocity varies between individuals. Then, on the basis of the results, experiment of roughness evaluation is conducted for flat surface and curved surface. A constant normal force and scanning velocity are exerted and the collected sensor output is calibrated by using the sensor output for the middle-roughness sample. The results show that the sensor is capable of evaluating roughness on both flat surface and curved surface in the same rating.