Sensor embedded glove systems have been reported to require careful, time consuming and precise calibrations on a per user basis in order to obtain consistent usable data. We have developed a low cost, flex sensor based smart glove system that may be resilient to the common limitations of data gloves. This system utilizes an Arduino based micro controller as well as a single flex sensor on each finger. Feedback from the Arduinos analog to digital converter can be used to infer objects dimensional properties, the reactions of each individual finger will differ with respect to the size and shape of a grasped object. In this work, we report its use in statistically differentiating stationary objects of spherical and cylindrical shapes of varying radii regardless of the variations introduced by gloves users. Using our sensor embedded glove system, we explored the practicability of object classification based on the tactile sensor responses from each finger of the smart glove. An estimated standard error of the mean was calculated from each of the of five fingers averaged flex sensor readings. Consistent with the literature, we found that there is a systematic dependence between an objects shape, dimension and the flex sensor readings. The sensor output from at least one finger, indicated a non-overlapping confidence interval when comparing spherical and cylindrical objects of the same radius. When sensing spheres and cylinders of varying sizes, all five fingers had a categorically varying reaction to each shape. We believe that our findings could be used in machine learning models for real-time object identification.
翻译:据报道,嵌入式传感器手套系统需要每个用户仔细、耗时和精确校准,以便获得一致的可用数据。我们开发了一个低成本、机动感应器和智能手套系统,可以适应数据手套的常见限制。该系统使用阿杜诺型微控制器和每个手指上的一个单一感应器。Arduinos模拟器和数字转换器的反馈可用于推断物体的尺寸特性,每个手指的反应在被捕获物体的大小和形状方面将有所不同。在这项工作中,我们报告在统计上区分了球形和圆柱形的固定物体,不管手套使用者采用何种变异。我们利用我们的传感器嵌入式手套系统,探索根据智能手套每个手指的触动感应反应进行物体分类的可行性。从五个手指的平均弹性感应读数中计算出平均值的标准误差。与文献一致,我们发现,在每一个物体的形状、尺寸和圆柱形形状之间,不管手套使用者采用何种变形,在每一个方向上都存在系统的依赖性依赖性,我们从一个不易变式的物体的形状、尺寸和弹性感应变式传感器上,从一个显示一个不易变的尺寸。感感官输出输出,从一个感官的等级到一个不同的感判分。