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相关概念视频

Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

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It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
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Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Plane Potential Flows01:23

Plane Potential Flows

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Plane potential flows simplify fluid motion by assuming the fluid to be irrotational and incompressible. These characteristics allow these flows to be described by a velocity potential function, ϕ, representing the flow speed in a given direction, and a stream function, ψ, that visualizes the flow path, both governed by Laplace's equation. These parameters help in estimating flow patterns, velocity distributions, and pressure fields around various hydraulic structures.
Uniform...
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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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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...
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Body Planes01:06

Body Planes

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Body planes in anatomy are imaginary flat surfaces used as reference points to divide the body into sections for anatomical study. These planes are essential for understanding the orientation, relationships, and spatial organization of anatomical structures.
The sagittal plane is the plane that divides the body or an organ vertically into right and left sides. If this vertical plane runs directly down the middle of the body resulting in equal division, it is called the midsagittal or median...
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Updated: Jul 18, 2025

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一种基于深度的混合方法,用于在无记忆规划中安全的飞行走廊生成.

Thai Binh Nguyen1, Manzur Murshed2, Tanveer Choudhury1

  • 1Institute of Innovation, Science and Sustainability, Federation University Australia, Churchill, VIC 3842, Australia.

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

这项研究引入了一种基于深度的新方法,用于生成安全的飞行走廊,这对于自主导航至关重要. 这种方法确保了无碰撞的路径与最小的重叠,提高无人机在复杂环境中的安全性.

关键词:
无人机无人机无人机是什么?深度感应 感应深度感应无人机 无人机 无人机没有内存的规划.安全飞行走廊安全飞行走廊

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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
  • 人工智能的人工智能

背景情况:

  • 自主系统需要在未知的环境中可靠的导航.
  • 地方规划往往依赖于事先存在的地图,限制了实时的适应性.
  • 创建安全的飞行走廊对于避免碰撞至关重要.

研究的目的:

  • 开发一种基于深度的混合方法,用于生成安全的飞行走廊.
  • 为了使没有内存的本地导航计划器能够有效地运行.
  • 确保无碰撞的走廊与路径规划的最小重叠.

主要方法:

  • 使用原始深度图像作为基于学习的对象检测引擎的直接输入.
  • 使用物体检测网络来预测多面体安全走廊.
  • 实施一个验证程序,以保证无碰撞的走廊.
  • 尽量减少走廊重叠,实现整个欧盟 (IoU) 的平均交叉率低于2%.

主要成果:

  • 成功集成到一个没有内存的规划器,使用直线路径规划算法.
  • 在合成和现实世界障碍密集的环境中表现出高的成功率.
  • 该方法有效地产生了独立的,无碰撞的安全走廊.

结论:

  • 提出的基于深度的混合方法具有很高的能力,可以为无记忆的当地规划生成安全的走廊.
  • 这种方法消除了对地图融合的需求,使实时导航成为可能.
  • 这种技术在复杂场景中显著提高了自动飞行的安全性和效率.