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相关概念视频

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

453
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
453
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

549
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
549
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
561

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基于回归的对接系统,用于使用单眼相机和ArUco标记器的自主移动机器人.

Jun Seok Oh1, Min Young Kim2,3,4

  • 1School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.

Sensors (Basel, Switzerland)
|June 27, 2025
PubMed
概括

本研究介绍了一种低成本的自主充电系统,使用单眼相机和ArUco标记器. 新的基于回归的方法准确地估计了距离和方向,超过了工业应用的传统视觉技术.

关键词:
这是ArUco标记器.自主对接的自主对接单眼相机是一个单眼相机.回归模型是一种回归模型.

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科学领域:

  • 机器人和自动化 机器人和自动化
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 传统的单眼视觉系统由于对视角,照明和校准的敏感性而难以准确地进行空间估计.
  • 像SolvePnP这样的现有方法在距离和方向估计中表现出严重的错误.

研究的目的:

  • 开发一个具有成本效益的自主充电对接系统,使用单眼相机和ArUco标记器.
  • 通过克服传统方法的局限性,提高自主对接空间估计的准确性.

主要方法:

  • 提出了一种基于回归的新方法,从ArUco标记器变化 (大小,形状) 中学习几何特征,用于距离和方向估计.
  • 该模型使用来自LiDAR传感器的地面真实数据进行训练.
  • 实时操作仅依赖于单眼相机输入.

主要成果:

  • 拟议系统的平均距离误差为1.18厘米,平均方向误差为3.11°.
  • 这显著优于SolvePnP,其误差为58.54厘米和6.64°.
  • 现实世界对接测试显示,平均位置误差为2厘米,定向误差为3.07°.

结论:

  • 精确可靠的自主对接可以通过低成本,仅视觉硬件实现.
  • 开发的系统为工业自主充电应用提供了实用且可扩展的解决方案.
  • 基于回归的方法有效地解决了传统单眼视觉技术的局限性.