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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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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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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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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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Related Experiment Video

Updated: May 5, 2026

Operation of the Collaborative Composite Manufacturing CCM System
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A fast map merging algorithm in the field of multirobot SLAM.

Yanli Liu1, Xiaoping Fan, Heng Zhang

  • 1School of Information Science and Engineering, Central South University, Changsha 410075, China ; School of Information Engineering, East China Jiaotong University, Nanchang 330013, China.

Thescientificworldjournal
|December 5, 2013
PubMed
Summary

This study introduces a novel map merging algorithm for multi-robot simultaneous localization and mapping (SLAM). It addresses challenges like unknown poses and unstable communication, enabling robots to build a unified map effectively.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Vision

Background:

  • Single-robot Simultaneous Localization and Mapping (SLAM) has advanced significantly.
  • Multirobot SLAM presents challenges including unknown robot poses, unshared maps, and unstable communication.

Purpose of the Study:

  • To propose a novel map merging algorithm for multirobot SLAM.
  • To overcome the inherent difficulties in multirobot mapping and localization.

Main Methods:

  • A map merging algorithm based on virtual robot motion is introduced.
  • A thinning algorithm constructs the skeleton of the grid map's empty area.
  • Partial map Monte Carlo localization is performed using simulated data from one map in another, followed by hypothesis verification and heuristic random search optimization.

Main Results:

  • The proposed algorithm enables successful localization and computation of relative pose hypotheses between maps.
  • The rendezvous technique and heuristic random search optimize the estimation of relative poses.

Conclusions:

  • The developed algorithm effectively merges maps in multirobot SLAM scenarios.
  • It provides a robust solution for challenges posed by unknown robot poses and communication instability.