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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

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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...
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Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

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In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
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Kinematic Equations: Problem Solving01:15

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When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
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Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

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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...
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Kinematic Equations - I01:26

Kinematic Equations - I

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When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
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Kinematic Equations - III01:18

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The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
Using the kinematic equations,...
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Updated: Jun 5, 2025

Operation of the Collaborative Composite Manufacturing CCM System
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基于图像的视觉服务,避免动态奇点,用于移动操纵器.

Jesus Hernandez-Barragan1, Carlos Villaseñor1, Carlos Lopez-Franco1

  • 1University Center for Exact Sciences and Engineering, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico.

PeerJ. Computer science
|December 9, 2024
PubMed
概括
此摘要是机器生成的。

本研究使用基于图像的视觉伺服 (IBVS) 实现了对冗余移动操纵器的视觉伺服. 缓和最小平方和任务优先级有效减少奇点,改善机器人控制.

关键词:
可以操纵性的操作性.移动操纵器移动操纵器冗余的机器人机器人视觉服务器提供服务

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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
  • 控制系统 控制系统

背景情况:

  • 视觉伺服 (VS) 使机器人能够使用相机反来进行精确的控制.
  • 冗余的移动操纵器提供了增强的灵巧性,但也带来了控制挑战.
  • 眼睛在手中的配置需要复杂的雅科比矩阵计算.

研究的目的:

  • 为冗余移动操纵器实施强大的视觉伺服策略.
  • 为了解决眼在手的配置中常见的动态奇点.
  • 为了提高机器人姿势控制的准确性和操纵性.

主要方法:

  • 使用基于图像的视觉服务 (IBVS) 方案.
  • 使用压缩最小方形 (DLS) 逆转雅可比矩阵,减轻奇点.
  • 实施了主要IBVS和次要操纵性最大化任务优先级计划.
  • 基于图像空间错误的内置重力补偿.

主要成果:

  • 成功证明了拟议的视觉伺服算法的有效性.
  • 减少动力奇点和平滑机器人运动中的不连续性.
  • 通过对Kuka YouBot进行模拟和实验来验证该方法.

结论:

  • 拟议的视觉伺服方法增强了冗余移动操纵器的控制.
  • DLS和任务优先级是有效的克服奇点问题.
  • 综合的方法确保了强大而准确的机器人操纵在眼睛在手系统.