设计和评估使用手势识别的四旋转无人机的替代控制
Siavash Khaksar1, Luke Checker1, Bita Borazjan1
1School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, Australia.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
这项研究开发了一种用于无人机控制的手势识别 (HGR) 系统. 该系统有效地使用MediaPipe Hands (MPH) 和自定义分类器,以实现直观,低成本的四旋转机操作.
科学领域:
- 机器人和人机交互的人机交互
- 计算机视觉和机器学习
背景情况:
- 手势识别 (HGR) 已经研究了40年,机器感知的现代进步使得像MediaPipe Hands (MPH) 这样的算法成为可能.
- 现有的HGR解决方案在介质,方法和应用上有所不同,需要对新的控制环境进行评估.
研究的目的:
- 评估现代HGR算法的适用性,特别是MPH,用于替代控制.
- 开发和评估一个基于HGR的系统来控制四旋翼无人机.
主要方法:
- 评估MediaPipe Hands (MPH) 用于使用单摄像头,骨架模型方法进行手势识别.
- 开发一种新的HGR算法,通过选择一个分类器来补充MPH的轻量化性质并解决其Z轴不稳定性.
- 实施用于控制四旋转无人机的HGR系统.
主要成果:
- MPH表现出Z轴的不稳定性,将地标准确度从86.7%降至41.5%.
- 选择的分类器弥补了MPH的不稳定性,在八个静态单手手势中实现了96.25%的分类准确性.
- 开发的HGR系统实现了直观,计算成本低廉,可重复的无人机控制.
结论:
- 像MPH这样的现代HGR算法可以适应替代控制应用.
- 开发的HGR系统提供了一个可行的解决方案,可以在没有专用设备的情况下实现可访问和高效的无人机操作.
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