A rule based fuzzy gesture recognition system to interact with Sphero 2.0 using a smart phone

Aykut Beke, Ahmet Arda Yuceler, T. Kumbasar
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引用次数: 5

Abstract

In this study, we will present a rule based fuzzy gesture recognition system where a user will interact with a spherical robot with hand gestures performed with a smart phone and the droid will respond by imitating this movements. In this context, we will take up the Gesture Recognition, Fuzzy Logic and Internet of Things (IoT) frameworks to construct such a Human-Machine Interface (HMI). In the proposed structure, the IoT collect the necessary IMU data from the smart phone for classification purposes while also providing the necessary data to the Sphero 2.0 droid. To recognize/classify the hand gestures performed with a smart phone, we will use and train fuzzy classifier. For proof of concept purposes, we have defined two hand gesture movements which are circular and linear gesture movement. The presented results clearly show that the performance of the fuzzy classifier is satisfactory even though each user has unique gesture characteristic (different magnitudes and velocities). Finally, we have also tested the proposed system in real-time with a user from whom we have not collected any IMU data. The presented results of the paper will show that the performance fuzzy logic based gesture recognition and interaction system is satisfactory.
基于规则的模糊手势识别系统与Sphero 2.0智能手机交互
在这项研究中,我们将提出一个基于规则的模糊手势识别系统,用户将与一个球形机器人交互,用智能手机执行手势,机器人将通过模仿这个动作来做出反应。在此背景下,我们将采用手势识别,模糊逻辑和物联网(IoT)框架来构建这样的人机界面(HMI)。在提议的结构中,物联网从智能手机收集必要的IMU数据用于分类目的,同时也向Sphero 2.0机器人提供必要的数据。为了识别/分类用智能手机执行的手势,我们将使用和训练模糊分类器。为了验证概念,我们定义了两种手势运动,即圆形手势运动和线性手势运动。结果清楚地表明,即使每个用户具有独特的手势特征(不同的幅度和速度),模糊分类器的性能也令人满意。最后,我们还用一个没有收集任何IMU数据的用户对所提出的系统进行了实时测试。本文的研究结果表明,基于模糊逻辑的手势识别交互系统的性能是令人满意的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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