Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

20.8K
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...
20.8K
Elastic Collisions: Introduction01:00

Elastic Collisions: Introduction

15.3K
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...
15.3K
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

5.5K
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...
5.5K
Types of Collisions - II01:19

Types of Collisions - II

10.2K
When two or more objects collide with each other, they can stick together to form one single composite object (after collision). The total mass of the object after the collision is the sum of the masses of the original objects, and it moves with a velocity dictated by the conservation of momentum. Although the system's total momentum remains constant, the kinetic energy decreases, and thus such a collision is an inelastic collision. Most of the collisions between objects in daily life are...
10.2K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

7.1K
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...
7.1K
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

1.4K
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...
1.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same journal

Trap tales: The influence of red alder stand conditions and forest fragmentation on family-level beetle bycatch diversity.

PloS one·2026
Same journal

MamNet-PT: A Mamba-enhanced hybrid architecture with selective state-space modeling for uncertainty-aware brain tumor segmentation.

PloS one·2026
Same journal

Multicenter evaluation of BACT-Info. and an infection algorithm using Urine Flow Cytometry among clinically diagnosed UTI patients in Indonesia.

PloS one·2026
Same journal

Cross-cultural adaptation and psychometric properties study of Prolonged Grief Disorder Questionnaire (PG-12-R) for caregivers of terminal cancer patients, Thai version.

PloS one·2026
Same journal

Design and in silico validation of donor DNA for RNA-guided recombinase-mediated knockout of mstnb gene in Labeo rohita.

PloS one·2026
Same journal

ViT-MultiRAGNet: A scalable and reliable retrieval-augmented Vision Transformer framework for memory-guided feature fusion multi-modal mammogram classification.

PloS one·2026

Related Experiment Video

Updated: Feb 22, 2026

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
13:44

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

14.7K

Performance improvement of haptic collision detection using subdivision surface and sphere clustering.

A Ram Choi1, Mee Young Sung1

  • 1Department of Computer Science and Engineering, Incheon National University, Incheon, Korea.

Plos One
|September 27, 2017
PubMed
Summary

This study compares subdivision surface methods for precise haptic collision detection. The Least Squares Subdivision Surface (LS3) method enhances accuracy, while adaptive clustering improves performance in haptic simulations.

More Related Videos

Impacts of Free-falling Spheres on a Deep Liquid Pool with Altered Fluid and Impactor Surface Conditions
08:49

Impacts of Free-falling Spheres on a Deep Liquid Pool with Altered Fluid and Impactor Surface Conditions

Published on: February 17, 2019

7.1K
Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.2K

Related Experiment Videos

Last Updated: Feb 22, 2026

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
13:44

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

14.7K
Impacts of Free-falling Spheres on a Deep Liquid Pool with Altered Fluid and Impactor Surface Conditions
08:49

Impacts of Free-falling Spheres on a Deep Liquid Pool with Altered Fluid and Impactor Surface Conditions

Published on: February 17, 2019

7.1K
Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.2K

Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Robotics

Background:

  • Haptic applications, like surgery simulations, demand high-precision collision detection.
  • Previous work introduced an efficient collision detection method using bounding sphere clustering.

Purpose of the Study:

  • To analyze and compare the impact of five common subdivision surface methods on 3D models for haptic collision detection.
  • To identify the most suitable subdivision method for enhancing precision in haptic simulations.

Main Methods:

  • Comparison of Butterfly, Catmull-Clark, Mid-point, Loop, and LS3 (Least Squares Subdivision Surface) methods.
  • Experimental analysis of subdivision effects on 3D models for haptic collision detection.
  • Integration of adaptive clustering with subdivision methods to mitigate performance degradation.

Main Results:

  • The LS3 method demonstrated superior appropriateness for haptic simulations.
  • Increased surface subdivision generally led to more precise collision detection results.
  • Performance gains from subdivision were observed up to a certain threshold, after which degradation occurred.

Conclusions:

  • The LS3 subdivision surface method is recommended for precise haptic simulations.
  • Adaptive clustering significantly improved the speed of collision detection, addressing performance limitations.
  • Balancing subdivision levels and adaptive techniques is key for optimal haptic collision detection performance.