Gesture-Controlled Robotic Arm Utilizing OpenCV

Jedidiah Paterson, Ahmed Aldabbagh
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引用次数: 3

Abstract

In this paper, a low-cost, 3D printed robotic arm that uses a system of gesture recognition controlled via computer vision is presented. The developed approach of Human-Computer Interaction (HCI) employs a single commonly available USB2.0 High-Definition camera to capture hand movements and gestures, implementing the OpenCV library. This enables the translation of those movements and gestures into commands that can be transferred using internet protocols to a Raspberry Pi; then interfaces with the robotic arm. Using computer vision as a method of HCI reduces components and overall cost. The Raspberry Pi uses individual commands to control the robotic arm’s servo motors while monitoring multiple pressure sensors and limit switches to ensure the robotic arm operates within a certain limit of load. This prevents the arm from overextending itself while protecting the integrity of items within its grasp.
基于OpenCV的手势控制机械臂
本文介绍了一种低成本的3D打印机械臂,该机械臂采用计算机视觉控制的手势识别系统。开发的人机交互(HCI)方法采用单个常用的USB2.0高清摄像机来捕捉手部动作和手势,实现OpenCV库。这使得这些动作和手势转换成命令,可以使用互联网协议传输到树莓派;然后与机械臂连接。使用计算机视觉作为HCI的一种方法可以减少组件和总体成本。树莓派使用单独的命令来控制机械臂的伺服电机,同时监控多个压力传感器和限位开关,以确保机械臂在一定的负载限制内运行。这可以防止手臂过度伸展,同时保护其掌握的物品的完整性。
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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