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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

839
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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相关实验视频

Updated: May 5, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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移动机器人的障碍回避技术在自主的人机协作仓库环境中

Lucas C Sousa1, Yago M R Silva2, Vinícius B Schettino3

  • 1Federal Center for Technological Education Celso Suckow da Fonseca, CEFET, Rio de Janeiro 20271-110, Brazil.

Sensors (Basel, Switzerland)
|April 26, 2025
PubMed
概括

本研究介绍了一种集成的模糊逻辑和卷积神经网络 (CNN) 技术,用于移动机器人在人机器人协作 (HRC) 中避开障碍. 该方法在动态的工业环境中增强了自主导航和安全性.

关键词:
人与机器人的共存.工业环境 工业环境 工业环境机器人导航 机器人导航安全合作 安全合作可共享的工作空间

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Last Updated: May 5, 2026

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 控制系统 控制系统

背景情况:

  • 人机协作 (HRC) 需要在动态环境中为移动机器人提供先进的导航.
  • 在HRC任务中确保安全和生产力是一个重大挑战,需要智能避开障碍.
  • 现有的方法可能难以实时适应复杂,不断变化的工作空间.

研究的目的:

  • 开发和评估基于移动机器人的综合模糊逻辑和卷积神经网络 (CNN) 的障碍回避技术.
  • 加强自主导航能力,确保HRC任务期间人员和设备的安全.
  • 为实时适应和工业环境中安全交互提供强大的解决方案.

主要方法:

  • 一种综合方法,将模糊逻辑规则和卷积神经网络 (CNN) 结合起来,用于机器人运动期间的物体检测.
  • 使用机器人操作系统 (ROS) 和Gazebo进行基于模拟的测试,以测试避障系统.
  • 实施控制系统,调整机器人的速度和曲率,以实现动态避障.

主要成果:

  • 拟议的技术有效地检测物体,并使移动机器人的自主导航成为可能.
  • 该系统在模拟的动态和复杂的工业环境中展示了实时适应能力.
  • 成功避免了包括人类在内的静态和移动障碍物.

结论:

  • 综合模糊逻辑和CNN方法为HRC的移动机器人避障提供了有效的解决方案.
  • 开发的技术可以提高操作安全性,而不会影响协作机器人的生产力.
  • 该框架为动态工业工作空间中安全的人机交互提供了可靠的方法.