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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

705
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...
705
Orthogonal Trajectories01:26

Orthogonal Trajectories

22
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
22
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

443
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
443

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相关实验视频

Updated: Jan 18, 2026

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

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一个分布式的时间变化的神经动力学算法用于多无人机协作目标跟踪问题在海上搜索和救援.

Lingxi Zhang1, Xing He1, Junzhi Yu2

  • 1Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China.

ISA transactions
|September 10, 2025
PubMed
概括

这项研究引入了一种新的神经动力学算法,用于多个无人机 (UAV) 在海上搜救中跟踪目标,即使风速变化. 该系统有效地跟踪目标,无论其轨迹变化如何.

关键词:
分布时间变化的神经动力学算法.固定时间的趋同.在海上搜索和救援.多个无人机空中飞行器.目标追踪器 目标追踪器

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Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
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Behavioral Tracking and Neuromast Imaging of Mexican Cavefish
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相关实验视频

Last Updated: Jan 18, 2026

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
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Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
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Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 优化理论 优化理论
  • 海上运营 海上运营

背景情况:

  • 海上搜索和救援行动通常依赖无人机 (UAV) 来追踪目标.
  • 现有的方法通常假设固定的环境条件,例如恒定的风速,限制了它们在现实世界中的应用.
  • 多个无人机的协作跟踪提供了更好的覆盖范围和稳定性,但在动态环境中面临着挑战.

研究的目的:

  • 开发和分析一个分布式算法,用于多个无人机在时间变化 (TV) 条件下进行协作目标跟踪,特别是针对不同的风速.
  • 在具有动态目标轨迹的场景中调查拟议的算法的性能.
  • 为了确保跟踪算法的固定时间收,独立于初始条件.

主要方法:

  • 制定一个类型的TV凸优化问题与不平等约束.
  • 分布式电视神经动力学算法的设计,集成预测校正和滑动模式控制.
  • 使用利亚普诺夫函数的理论分析来证明固定时间的收性质.
  • 实验验证使用已建立的3D目标轨迹方程与侧面变异进行实验验证.

主要成果:

  • 拟议的分布式电视神经动力学算法实现了协作目标跟踪的固定时间收.
  • 尽管有电视目标轨迹,算法的追踪效率表现仍然很强大.
  • 实验结果证实了该系统在不同风速条件下的有效性.

结论:

  • 开发的算法为动态海上环境中的多无人机协作目标跟踪提供了强大的解决方案.
  • 固定时间收确保可靠和可预测的系统行为,对于搜索和救援任务至关重要.
  • 该系统对电视目标轨迹和风状况的弹性提高了其实际效用.