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相关概念视频

Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

240
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
240
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

421
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...
421
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

486
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...
486
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

378
A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
378
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

388
A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
388
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

355
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. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
355

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机器学习用于人类运动意图检测的机器学习

Jun-Ji Lin1, Che-Kang Hsu1, Wei-Li Hsu2

  • 1Department of Mechanical Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei City 106319, Taiwan.

Sensors (Basel, Switzerland)
|August 26, 2023
PubMed
概括
此摘要是机器生成的。

检测步态转变,而不仅仅是运动,是及时控制外骨的关键. 这项研究表明,机器学习可以快速识别步态变化,即使是跨不同用户,提高安全性和可用性.

关键词:
料前神经网络 (FNN) 是一个神经网络.人类意图检测检测人类意图检测人与机器人的交互惯性测量单位 (IMU) 是指惯性测量单位.长时间的短期记忆 (LSTM)

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科学领域:

  • 生物医学工程 生物医学工程
  • 机器人技术 机器人技术 机器人技术
  • 机器学习 机器学习

背景情况:

  • 外骨控制需要精确了解用户的意图,以防止受伤.
  • 当前的方法经常与意图识别的时间扎,导致操作问题.
  • 识别步态转换为实时检测提供了一种新的方法.

研究的目的:

  • 为了研究检测步态转变以改善外骨控制的可行性.
  • 评估机器学习模型在识别步态变化的有效性.
  • 评估过渡检测的速度和通用性.

主要方法:

  • 使用惯性测量单元 (IMU) 传感器数据进行步态分析.
  • 训练并测试了线性Feedforward神经网络和长期短期记忆网络.
  • 来自五个受试者的员工步行数据用于模型开发和验证.

主要成果:

  • 机器学习网络成功地区分了步态过渡期与连续运动.
  • 实现了快速检测步行到坐的过渡 (0.17秒),适用于控制应用.
  • 检测站立到走路的转变显示出更长的延迟 (高达1.2s).
  • 模型证明了跨主题的概括性,而不会降低性能.

结论:

  • 步态转变检测是实时外骨控制的可行策略.
  • 机器学习模型为实时的步态变化识别提供了有希望的结果.
  • 开发的方法显示了强大的和可适应的人类外骨相互作用的潜力.