摘要:挖掘机有十分广泛的应用场景，但在某些危险工况下，对其采用遥操作是更好的选择。同时，近年来随着机器视觉和深度学习的发展，涌现出一系列手势识别的算法和框架。为了探究基于MediaPipe的手势识别算法在挖掘机遥操作中的应用，本文将手部不同手势与挖掘机的不同动作相对应，提出一种利用手势实现挖掘机遥操作的新型控制方式。在实验室环境下，对实验用挖掘机器人进行运动学分析，采用MediaPipe对15种手势类型进行实时静态识别，生成指令并利用Arduino单片机实现对挖掘机的控制。结果显示，该系统具有良好的性能，可以用于挖掘机的遥操作控制，为挖掘机的远程控制提供了一种新型的人机交互形式。

Abstract: Excavators have broad application scenarios, but in certain hazardous working conditions, using teleoperation is a better option. Meanwhile, with the development of machine vision and deep learning in recent years, a number of algorithms and frameworks for gesture recognition are becoming available. In order to explore the application of MediaPipe-based gesture recognition algorithms in excavator teleoperation, this paper corresponds different hand gestures to different movements of the excavator, and proposes a new control method using hand gestures to achieve excavator teleoperation. The kinematic analysis of the experimental excavation robot was carried out in a laboratory environment, and MediaPipe was used to perform real-time static recognition of 15 gesture types, generate commands and realise the control of the excavator using an Arduino microcontroller. The results show that the system has good performance and can be used for teleoperation control of the excavator, which provides a new form of human-computer interaction for remote control of the excavators.