手动控制机器人手臂 - 机械项目188金宝搏怎么样

ABSTRACT:

在今天的世界，大多数各个部门，该工作由机器人或机器人手臂根据要求提供不同程度的自由度（DOF）。这个想法是改变对致动手动操作机器人臂的遥控器的感知。嗯，本文呈现了一种思考和一种方法来消除按钮，操纵杆和用一些更直观的技术替换它们，这些技术是通过操作员手势控制完整的机器人手臂。所提出的电子系统识别将在网络摄像机前面执行的特定手势，并通过RF模块无线地传输备受尊重的信号。根据所接收的信号，接着的机器人臂，其后的AVR微控制器在接收器部分执行接受运动。

介绍
Nowadays, the most of the human-computer interaction (HCI) is based on mechanical devices such as keyboards, mouse, joysticks or gamepads. In recent years there has been a growing interest in a class of methods based on computational vision due to its ability to recognize the human gestures in a natural way. Such methods use as input the images acquired from a camera or from a stereo pair of cameras. The main goal of such algorithms is to measure the hand configuration in each time instant. To facilitate this process many gesture识别应用程序诉诸手上或手指上的唯一彩色手套或标记。另外，使用受控背景使得可以有效地甚至实时地本地化不同的手。这两个条件对用户和接口设置施加限制。由于我们的应用的初始要求，我们专门避免了需要彩色手套或标记和受控背景的解决方案。它必须为不同的人员工作，没有任何补充它们以及不可预测的背景。

Our application uses images from a low-cost web camera placed in front of the work area, where the recognized gestures act as the input for particular robotic arm motion. Here, webcam is connected with computer or laptop for human machine interface. Computer is already loaded with MATLAB 7 tool having Windows XP installed. Webcam precedes several of recognizing values to the computer. MATLAB tool recognizing the preferred gestures by comparing stored gestures values & gives respective outputs. The output which was generated by comparison has been transmitted wirelessly through RF module. Receiver section accepts the transmitting signals and given to AVR microcontroller which check the several values. The output of microcontroller is given to the motor which has been mounted in robotic arm and we will get a respective motion of robotic arm.

在机器人领域，已经针对识别人类手势的几项研究努力。
Following are the few popular systems:

A.基于视觉的手势识别 -

此识别系统基本上在服务机器人领域工作，研究人员终于设计了一种执行清洁任务的机器人。它们设计了一种基于手势的界面，可以控制配备有机械手的移动机器人。该界面使用相机跟踪一个人并识别涉及手臂运动的不同手势。快速的自适应跟踪算法使机器人能够通过具有变化照明条件的办公环境可靠地跟踪和遵循一个人。比较基于模板的方法和基于模板的方法和基于神经的方法，并与Viterbi算法组合用于识别通过臂运动定义的手势。它导致交互式清理任务，用户指导机器人转到需要清洁的特定位置，并且还指示机器人拾取可用垃圾。

B.运动捕获传感器识别 -

这种识别技术使得可以实现基于加速度计的系统，以无线地与工业机器人臂通信。在该特定项目中，机器人臂通过基于ARM7的LPC1768核心供电。实际上，MEMS是三维加速度计传感器，其捕获人臂的手势并在三维轴上产生三种不同的模拟输出电压。两个柔性传感器用于控制夹持器运动。

C.加速度计的手势识别 -

This Gesture Recognition methodology has become increasingly popular in a very short span of time. The low-moderate cost and relative small size of the accelerometers are the two factors that make it an effective tool to detect and recognize different human body gestures. Several studies have been conducted on the recognition of gestures from the acceleration data using Artificial Neural Networks (ANNs).

结论
A low cost computer vision system that can be executed in a common PC equipped with low power USB web cam was one of the main objectives of our work, which has been implemented successfully. We have experimented with around 30 hand gesture images and achieved higher average precision. The best classification rate of 97% was obtained under different light conditions. But the drawback in this method is that the hand should be properly placed with respect to the webcam so that the entire hand region is captured. If the hand is not placed properly the gesture is not recognized appropriately. Gesture made in this method involves only one hand and this reduces the number of gestures that can be made using both hands.

Reference and report Download :

http://ijiird.com/wp-content/uploads/2018/03/s151122-hand-motion-controlled-robotic-arm.pdf.