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相关概念视频

Deformation of Member under Multiple Loadings01:11

Deformation of Member under Multiple Loadings

163
When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
In the case of a member with a variable cross-section, the strain is not constant but depends on the position. The deformation of an...
163

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相关实验视频

Updated: Jun 23, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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多视图金属零件基于单个摄像头进行估计.

Chen Chen1, Xin Jiang1

  • 1Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China.

Sensors (Basel, Switzerland)
|June 19, 2024
PubMed
概括

本研究提出了一种新的方法,用于仅使用RGB图像对金属部件进行6D姿势估计. 该方法利用多个视图和射线造来准确确定反射工业部件的姿势.

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
  • 工业自动化 工业自动化

背景情况:

  • 精确的6D姿势估计对于金属零件的工业抓取至关重要.
  • 金属零件的反射特性阻碍了完全采集点云.
  • 现有的方法通常需要深度信息或与光亮表面作斗争.

研究的目的:

  • 开发一种方法,使用单个RGB摄像头恢复CAD模型中已知的金属零件的6度自由 (6D) 姿势.
  • 为了克服反射表面在获得准确的姿势估计方面所带来的挑战.
  • 为了能够在不需要深度数据的情况下进行姿势估计.

主要方法:

  • 使用多个视图来估计金属零件的位置.
  • 采用射线射来模拟额外的视图,并确定相机的下一个最佳视角.
  • 集成相机转换与多视图姿势数据进行最终的姿势改进.

主要成果:

  • 拟议的方法有效地估计了闪亮的金属零件的6D姿势.
  • 仅使用RGB图像证明成功的姿势恢复.
  • 尽管目标对象具有反射性质,但仍能获得准确的结果.
关键词:
在RGB感知方面,RGB感知深度学习用于视觉感知.构成估计估计的估计.

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相关实验视频

Last Updated: Jun 23, 2025

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结论:

  • 使用射线造的多视图方法对于金属零件的6D姿势估计是有效的.
  • 该方法为需要准确的姿势数据的工业抓取应用提供了可行的解决方案.
  • 对于具有挑战性的反射物体,仅使用RGB的姿势估计是可行的.