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Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

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Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
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相关实验视频

Updated: Jan 15, 2026

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

677

实时面部基于手势的机器人控制使用GhostNet在统一模拟环境中.

Yaseen1

  • 1Department of Electronics Engineering, Sejong University, Seoul 05006, Republic of Korea.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
概括

这项研究引入了一种新的面部手势识别系统,用于无接触式控制自动驾驶系统. 幽灵网-BiLSTM-注意力 (GBA) 方法达到99.13%的准确性,使直观的人机交互成为可能.

科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 传统的控制系统依赖于物理设备,限制了无接触式交互.
  • 人工智能和计算机视觉的进步使面部手势识别能够用于人机交互.

研究的目的:

  • 为运行自主系统开发一种轻量级的实时面部手势识别系统.
  • 将系统与3D机器人模拟进行集成,以实现沉浸式控制.

主要方法:

  • 提出了一个GhostNet-BiLSTM-Attention (GBA) 模型用于面部手势识别.
  • 在FaceGest数据集上训练了GBA模型.
  • 通过插座通信将系统与Unity 3D机器人模拟集成在一起.

主要成果:

  • 在FaceGest数据集上实现了99.13%的分类准确性.
  • 在实时评估中展示了高精度和低推断延迟.
  • 在各种用户和照明条件下展示了强度.

结论:

  • GBA系统为无接触式机器人控制提供了准确有效的方法.
关键词:
幽灵网络-BiLSTM-注意事项模拟单位的模拟.人与机器人的互动实时识别 实时识别时间面部手势识别功能无触摸的无触摸控制器

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  • 面部手势识别为人机交互提供了一个直观的界面.
  • 潜在的应用包括辅助机器人,远程操作和沉浸式接口.