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Related Concept Videos

Collisions in Multiple Dimensions: Problem Solving01:06

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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

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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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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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Elastic Collisions: Introduction01:00

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An elastic collision is one that conserves both internal kinetic energy and momentum. Internal kinetic energy is the sum of the kinetic energies of the objects in a system. Truly elastic collisions can only be achieved with subatomic particles, such as electrons striking nuclei. Macroscopic collisions can be very nearly, but not quite, elastic, as some kinetic energy is always converted into other forms of energy such as heat transfer due to friction and sound. An example of a nearly...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

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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.
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Three-Dimensional Force System:Problem Solving01:30

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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.
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Photorealistic Learned Landscapes for Augmented Reality
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A 3D roaming and collision detection algorithm applicable for massive spatial data.

Mingxia Xie1,2, Xinqiang Niu2

  • 1Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen, China.

Plos One
|February 22, 2020
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Summary
This summary is machine-generated.

This study introduces a novel 3D roaming algorithm for massive spatial data, enhancing collision detection and interaction. The method improves efficiency and solves common issues in complex virtual environments.

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Area of Science:

  • Computer Graphics
  • Virtual Reality
  • Computational Geometry

Background:

  • Massive spatial data presents challenges for real-time 3D roaming and collision detection.
  • Existing methods often struggle with complex scenes and large datasets, limiting user interaction.

Purpose of the Study:

  • To propose a novel 3D roaming algorithm for efficient collision detection and interaction with massive spatial data.
  • To enhance the practicability and timeliness of 3D scene navigation in complex environments.

Main Methods:

  • Utilizing a triangle mesh for organizing massive spatial data.
  • Implementing a customized bounding box intersector for rapid identification of potential collisions.
  • Developing a method for calculating collision point coordinates considering sphere-triangle spatial relationships.
  • Incorporating 3D scene-path training and adaptive sphere radius adjustment to overcome navigation limitations.

Main Results:

  • Significantly improved calculation efficiency for collision point coordinates compared to native OpenSceneGraph (OSG) methods.
  • Successfully addressed issues like viewpoints falling off scenes or inaccessible regions due to scene topology.
  • Demonstrated enhanced performance for complex, large-scale 3D scenes.

Conclusions:

  • The proposed algorithm provides effective technical support for free browsing and roaming in massive 3D indoor/outdoor and underground environments.
  • This method overcomes limitations of existing techniques, enabling navigation in scenes with large data volumes and complex models.