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

Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

401
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
401
Velocity of an Object01:18

Velocity of an Object

199
Understanding how an object moves along a path requires distinguishing between motion over a time span and motion at a precise moment. A useful example is a vehicle traveling along a straight and level path, where its position at any given time is known. The initial step in analyzing this motion is to measure how far the vehicle travels over a fixed time period. This measurement, called average velocity, is computed by dividing the total change in position by the duration over which the change...
199
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

490
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
490
Potential Due to a Polarized Object01:29

Potential Due to a Polarized Object

770
A neutral atom consists of a positively charged nucleus surrounded by a negatively charged electron cloud. When placed in an external electric field, the external electric force pulls the electrons and nucleus apart, opposite to the intrinsic attraction between the nucleus and the electrons. The opposing forces balance each other with a slight shift between the center of masses of the nucleus and the electron cloud, resulting in a polarized atom. On the other hand, a few molecules, like water,...
770
Potential Due to a Magnetized Object01:24

Potential Due to a Magnetized Object

793
Magnetic dipoles in magnetic materials are aligned when placed under an external magnetic field. For paramagnets and ferromagnets, dipole alignment occurs in the direction of the magnetic field. However, the dipoles align opposite to the field in the case of diamagnets. This state of magnetic polarization due to the external field is called magnetization. Magnetization is defined as the dipole moment per unit volume. It plays a similar role to polarization in electrostatics.
The vector...
793
Moment of Inertia of Compound Objects01:07

Moment of Inertia of Compound Objects

7.6K
The moment of inertia is a quantitative measure of the rotational inertia of an object. It is defined as the sum of the products obtained by multiplying the mass of each particle of matter in a given body by the square of its distance from the axis. The total moment of inertia for compound objects can be found by determining and adding the moment of inertia of individual components together.
Consider a child of mass (mc) 25 kg standing at a distance (rc) of 1 m from the axis of a rotating...
7.6K

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

Observation of Anisotropic Magnetoresistance in Layered Nonmagnetic Semiconducting PdSe<sub>2</sub>.

ACS applied materials & interfaces·2021
Same author

Reopening International Borders without Quarantine: Contact Tracing Integrated Policy against COVID-19.

International journal of environmental research and public health·2021
Same author

Do the positioning variables of the cage contribute to adjacent facet joint degeneration? Radiological and clinical analysis following intervertebral fusion.

Annals of translational medicine·2021
Same author

HID: The Hybrid Image Decomposition Model for MRI and CT Fusion.

IEEE journal of biomedical and health informatics·2021
Same author

Genetically Predicted Cigarette Smoking in Relation to Risk of Polycystic Ovary Syndrome.

Clinical epidemiology·2021
Same author

Assessing the Country-Level Excess All-Cause Mortality and the Impacts of Air Pollution and Human Activity during the COVID-19 Epidemic.

International journal of environmental research and public health·2021
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jan 29, 2026

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

15.2K

基于图像点云实例匹配的机器人对象检测和跟踪.

Hongxing Wang1, Rui Zhu1, Zelin Ye2

  • 1Jiangxi Provincial Key Laboratory of Precision Drive and Equipment, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了移动机器人的实例感知融合框架,有效地将摄像头图像和LiDAR数据结合起来,以增强环境感知和对象跟踪. 该系统实现了高精度和低延迟,对于现实世界机器人应用至关重要.

关键词:
3D对象检测检测 3D对象检测卡尔曼过器可以过.跨模态感知交叉模态感知实例细分 实例细分 实例细分多对象跟踪多对象跟踪多模式传感器融合技术机器人感知系统 机器人感知系统

更多相关视频

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.7K
A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement
06:24

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

Published on: May 11, 2020

9.3K

相关实验视频

Last Updated: Jan 29, 2026

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

15.2K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.7K
A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement
06:24

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

Published on: May 11, 2020

9.3K

科学领域:

  • 机器人技术和自主系统
  • 计算机视觉 计算机视觉
  • 传感器融合式传感器

背景情况:

  • 移动机器人的环境感知依赖于融合各种传感器数据.
  • 整合语义图像信息与精确的LiDAR几何数据是一个重大挑战.
  • 现有的方法往往在有效的对齐和对异质感官输入的统一建模方面扎.

研究的目的:

  • 为移动机器人感知提出一个高度可扩展的实例意识的融合框架.
  • 为了实现RGB图像和LiDAR点云的高效对齐和统一建模.
  • 提高复杂环境中的多对象跟踪精度和稳定性.

主要方法:

  • 利用实例分段网络从RGB图像中提取语义.
  • 采用一个投影机制,用于图像像素和LiDAR点之间的空间对应.
  • 通过点云集群和几何拟合实现了3D界限框重建,并基于再投影验证.
  • 集成了一个数据关联模块和卡尔曼过器,用于闭环多对象跟踪.

主要成果:

  • 在KITTI数据集上实现了强大的二维和三维检测性能.
  • 获得了47.8的多对象追踪精度 (MOTA) 和71.93.3的IDF1得分.
  • 在现实世界的实验中显示了173.9ms的平均端到端延迟.
  • 废弃性研究证实了单个系统组件的有效性.

结论:

  • 拟议的框架提供了强大的几何重建精度和跟踪稳定性.
  • 它的轻量级设计和低延迟满足实际的机器人部署要求.
  • 该系统有效地融合了异构的感觉数据,以实现先进的移动机器人感知和跟踪.