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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

29
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

267
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
267
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

343
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
343
Machines: Problem Solving I01:22

Machines: Problem Solving I

272
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
272
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

502
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...
502
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

578
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...
578

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像蛇一样的机器人工作空间解决方法基于改进的蒙特卡洛方法

ZhiYong Yang1, Wang Tian1, HaoYang Wang1

  • 1Hubei Key Laboratory of Modern Manufacturing Quantity Engineering, School of Mechanical Engineering, Hubei University of Technology, Wuhan, Hubei 430068, China.

Applied bionics and biomechanics
|April 14, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种改进的蒙特卡洛方法,用于绘制电力线周围的蛇形机器人工作空间. 新方法增强了点分布和边界提取,以精确避免障碍.

关键词:
蒙特卡洛方法 蒙特卡洛方法像蛇一样的机器人计算体积的计算量量.工作空间工作空间.一个α形的形状.

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 计算几何学的计算几何学
  • 机械工程 机械工程

背景情况:

  • 蛇形机器人越来越多地用于基础设施检查,特别是在高压传输电缆上.
  • 传统的工作空间确定方法面临着点云边界提取和准确性的挑战.
  • 避免障碍物对于复杂环境中的安全和高效的机器人操作至关重要.

研究的目的:

  • 开发一种改进的蒙特卡洛方法,以准确确定在高压传输电缆上运行的蛇形机器人的避障工作空间.
  • 解决传统蒙特卡洛方法的局限性,包括不均的点分布和边界提取中的困难.
  • 为了提高工作空间体积计算的精度,以改善机器人导航.

主要方法:

  • 提出了一种改进的蒙特卡洛方法,从传统蒙特卡洛方法生成的种子工作空间开始.
  • 种子工作空间被包裹,分成较小的立方体,然后使用高斯分布概率密度函数扩展.
  • 阿尔法形算法被用来提取点云边界,并准确计算工作空间体积.

主要成果:

  • 改进的方法有效地解决了点分布不均和边界提取困难的问题.
  • 高斯分布采样增强了机器人的工作空间的生成.
  • 阿尔法形态算法准确地重建工作空间边界,通过模拟实验验证.

结论:

  • 拟议的改进的蒙特卡洛方法,结合alpha-shape算法,为确定蛇形机器人工作空间提供了准确可靠的方法.
  • 这种方法显著改进了传统技术,在电力线路检查场景中提供了更高的准确度来避免障碍.
  • 精确的工作空间确定对于提高蛇形机器人的安全性和效率在具有挑战性的工业应用中至关重要.