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相关概念视频

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
81
Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

71
A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
71
Root-Locus Method01:19

Root-Locus Method

145
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
145
Adjusting a Traverse01:12

Adjusting a Traverse

56
In the site survey of a four-sided traverse, internal angles are essential to ensure geometric accuracy. The survey revealed that the sum of the measured internal angles was 359 degrees and 48 minutes, which is 12 minutes less than the expected 360 degrees. This discrepancy signals an error likely arising from measurement inaccuracies during the fieldwork.To rectify this error, the adjustment process involved distributing the 12-minute shortfall equally across the four internal angles. By...
56

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相关实验视频

Updated: Jun 23, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

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人与机器人导航中的交叉点估计-统计线性化与西格玛点转换.

Rainer Palm1, Achim J Lilienthal2

  • 1Center for Applied Autonomous Sensor Systems (AASS), Department of Technology, Örebro University, SE-701 82 Örebro, Sweden.

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

本研究通过计算预期的交互区域来解决人机导航中的安全问题. 它使用统计线性化和西格玛点转换来处理模糊和杂的轨迹数据,以实现更安全的机器人导航.

科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人与机器人的交互
  • 导航系统 导航系统

背景情况:

  • 移动机器人和人类操作员在共享空间的安全导航至关重要.
  • 轨道规划和避开障碍是关键的安全考虑因素.
  • 由于噪音的影响,计划轨迹的不确定性会影响安全.

研究的目的:

  • 开发用于计算人类和机器人之间预期交互区域的方法.
  • 解决人类机器人导航中模糊和杂信息的挑战.
  • 分析机器人/人类状态和轨道交叉区域之间的非线性关联.

主要方法:

  • 对于噪音输入的非线性转换的统计线性化.
  • 用于不确定性传播的西格玛点转换.
  • 两种方法的模糊近似值.
  • 讨论参数估计的反向问题.

主要成果:

  • 考虑轨迹不确定性的预期相互作用区域的量化.
  • 从运动输入到交叉区域的非线性映射的演示.
  • 模糊近似的演示,用于实际应用.
关键词:
高斯式噪声 (Gaussian noise) 是一种高斯式噪声.人与机器人的互动西格玛点转换的转换.没有香味的卡尔曼过器.

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相关实验视频

Last Updated: Jun 23, 2025

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结论:

  • 提出的方法有效地计算了人机导航中预期的交互区域.
  • 处理模糊和杂数据对于稳健的轨迹规划至关重要.
  • 了解这些交互区域可以提高共享环境中的安全性.