Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Using Full Pose Measurement for Serial Robot Calibration.

Applied sciences (Basel, Switzerland)·2023
Same author

Software to Determine Sphere Center from Terrestrial Laser Scanner Data per ASTM Standard E3125-17.

Journal of research of the National Institute of Standards and Technology·2021
Same author

Concept to Commercialization of an Artifact for Evaluating Three-Dimensional Imaging Systems per ASTM E3125-17.

Journal of research of the National Institute of Standards and Technology·2021
Same author

Propagation of Error from Registration Parameters to Transformed Data.

Journal of research of the National Institute of Standards and Technology·2021
Same author

Comparative Study of Two Pose Measuring Systems Used to Reduce Robot Localization Error.

Sensors (Basel, Switzerland)·2020
Same author

An Overview of Activities at NIST Towards the Proposed ASTM E57 3D Imaging System Point-to-point Distance Standard.

Journal of the CMSC·2019

相关实验视频

Updated: Jun 29, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.6K

过有组织的3D点云用于垃圾拾取应用程序.

Marek Franaszek1, Prem Rachakonda1, Kamel S Saidi1

  • 1National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.

Applied sciences (Basel, Switzerland)
|April 3, 2024
PubMed
概括

本研究介绍了一种新的过技术,用于在机器人垃圾选中从3D数据中删除异常点. 与现有程序相比,新方法在混乱的制造场景中显著提高了异常值移除效率.

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
  • 感知系统 感知系统

背景情况:

  • 机器人垃圾拾取依赖于对象识别的感知系统.
  • 虚假的3D数据点 (异常值) 污染了感知数据,阻碍了障碍回避和部分细分.
  • 现有的异常值去除方法,通常是为户外场景而设计的,在制造环境中的有组织的3D点云中表现不佳.

研究的目的:

  • 开发和介绍一种新的过技术,用于在有组织的3D点云中去除异常值,这对于机器人垃圾挑选任务来说是特别的.
  • 为了解决杂乱的制造场景中通用异常值移除程序的局限性.

主要方法:

  • 为有组织的3D点云开发了一种新的过技术.
  • 该技术是专门设计的,以处理杂乱的场景典型的垃圾拾取.
  • 使用六个不同的数据集对通用统计异常值删除程序进行了性能评估.

主要成果:

  • 新的过技术证明了与通用统计异常值删除程序相比,更高的异常值删除效率.
  • 该方法在具有异常值高密度的数据集上表现出特别高的有效性.
  • 在机器人垃圾拾取应用的背景下,观察到更好的性能.
关键词:
垃圾桶挑选 垃圾桶挑选 垃圾桶挑选过 3D 点云的过.细分化 细分化的细分化删除统计异常值的删除

更多相关视频

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

442
A Pipeline to Investigate the Structures and Signaling Pathways of Sphingosine 1-Phosphate Receptors
12:27

A Pipeline to Investigate the Structures and Signaling Pathways of Sphingosine 1-Phosphate Receptors

Published on: June 8, 2022

3.4K

相关实验视频

Last Updated: Jun 29, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.6K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

442
A Pipeline to Investigate the Structures and Signaling Pathways of Sphingosine 1-Phosphate Receptors
12:27

A Pipeline to Investigate the Structures and Signaling Pathways of Sphingosine 1-Phosphate Receptors

Published on: June 8, 2022

3.4K

结论:

  • 拟议的过技术对于在机器人垃圾选中从有组织的3D点云中删除异常值非常有效.
  • 这一进步可以提高制造业中自主机器人操作的可靠性和效率.
  • 该方法为混乱的工业环境中的感知挑战提供了专门的解决方案.