残疾人和老年人无线手势控制机器人的设计与实现

Mahbuba Alam, M. Yousuf
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引用次数: 8

摘要

手势控制机器人应该通过嵌入式系统来完成它的工作,嵌入式系统是硬件和软件的组合,设计用于执行特定用户的专用任务,可以通过手势控制。在本文中,我们提出了一种针对残疾人和老年人的手势控制机器人。机器人使用运动传感器来识别五种手势。这五个手势用来控制停止或稳定、前进、后退、左右五个方向。在本文中,手势被运动传感器识别,并且没有任何图像处理,以保持系统的简单和高效。原型装置可以改装成轮椅、手推车床或任何由两个以上轮子组成的物理平台。Arduino Nano v3嵌入式系统,带有加速度计陀螺仪,由用户手持,信号将无线传输到平台的电机,旨在根据用户的手势移动平台,以便在周围环境中携带自己。机器学习用于准确分类手势。结果表明,该方法的分类准确率接近94%(93.8%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing and Implementation of a Wireless Gesture Controlled Robot for Disabled and Elderly People
Gesture controlled robot should perform its job with the embedded system, combination of hardware and software that is designed for performing dedicated tasks for specific users which can be controlled by hand gestures. In this paper, we propose a gesture controlled robot for physically challenged and elderly people. The robot uses motion sensors to recognize five gestures of hand. These five hand gestures are employed to control five directions such as stop or steady, forward, backward, left and right. In this paper, the gesture has been recognized by motion sensors and without any image processing to keep the system simple & efficient. The prototype device can be modified into a wheelchair, trolley bed or any physical platform consisting of more than two wheels. An Arduino Nano v3 embedded system with accelerometer gyroscope held by the user and the signals will be transferred wirelessly to the motors of the platform intended to move it as per the users hand gestures in order to carry themselves in their surrounding environment. Machine learning is used to classify hand gesture accurately. The result shows that the classification accuracy is near to 94% (93.8%).
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