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相关概念视频

Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

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Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...
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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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Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

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A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
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Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

1.2K
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
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One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
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Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

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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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相关实验视频

Updated: Jan 15, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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A*-TEB:一个改进的A*算法,基于多机器人运动规划的TEB策略.

Xu Li1, Tuanjie Li1,2, Yan Zhang2

  • 1College of Information Engineering, Tarim University, Alar City 843300, China.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
概括

这项研究引入了一种新的多机器人运动规划框架,可以增强A*和定时弹性带算法. 综合方法提高了路径效率,并减少了动态环境中的完成时间.

关键词:
时间弹性带 (TEB)自主导航自主导航自主导航改进了A*算法综合运动规划 综合运动规划多机器人系统是多机器人系统.

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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:

  • 多机器人运动规划 (MRMP) 需要强大的本地规划和全球一致性,目前的方法往往无法平衡.
  • 由于缺乏同时进行全球和本地规划,现有的方法在实时路径执行冲突中扎.
  • 对于全球路径规划,A*算法是最受欢迎的,而定时弹性带 (TEB) 算法在本地轨迹优化和动态避障方面表现出色.

研究的目的:

  • 开发一种新的运动规划框架,以协作方式解决多机器人系统的全球和本地规划.
  • 以提高方向成本和动态权重来增强A*算法,以提高路径流性和效率.
  • 改进TEB算法,使用层次障碍处理来实现优越的局部避开能力.

主要方法:

  • 整合了改进的A*算法 (带有转向成本和动态权重) 和增强的TEB战略.
  • 在TEB算法中实现层次障碍处理,以进行精细的本地路径调整.
  • 通过使用机器人操作系统 (ROS) 的模拟和现实实验进行验证.

主要成果:

  • 拟议的框架显示了与传统的A*算法相比的显著改进.
  • 实现了平均路径长度减少5.2%,完成时间减少11.5%.
  • 减少了66.7%的拐点,表明更平稳,更有效的路径.

结论:

  • 新的框架有效地整合了多机器人系统的全球和地方规划.
  • 与传统方法相比,增强的A*-TEB方法在动态环境中提供了卓越的性能.
  • 该方法在现实世界多机器人应用中是可行的和有效的.