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

Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.4K
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...
4.4K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

461
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.
Here, in order to determine the magnitude of velocity and acceleration for point...
461
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

137
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...
137
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

200
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
200
Vertical Curve: Problem Solving01:23

Vertical Curve: Problem Solving

204
Vertical curves provide the transition between two roadway grades, ensuring safety, comfort, and functionality. Calculating elevations at specific stations along the curve involves several systematic steps based on the curve's geometry and provided design parameters.The vertical curve is defined by its length, grades, Point of Vertical Intersection (P.V.I.) location, and P.V.I. elevation. The stations of the Point of Vertical Curvature (P.V.C.), where the curve begins, and the Point of Vertical...
204
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

566
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
566

You might also read

Related Articles

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

Sort by
Same author

A Deep Learning System for Fully Automated Retinal Vessel Measurement in High Throughput Image Analysis.

Frontiers in cardiovascular medicine·2022
Same author

A perylene five-membered ring diimide for organic semiconductors and π-expanded conjugated molecules.

Chemical communications (Cambridge, England)·2022
Same author

Patients With Bicuspid Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis.

Frontiers in cardiovascular medicine·2022
Same author

Two-dimensional coordination polymers with high proton conductivity and ultrafast highly efficient molecular sieving constructed by the structural inductive effect.

Dalton transactions (Cambridge, England : 2003)·2022
Same author

Bounded Antisynchronization of Multiple Neural Networks via Multilevel Hybrid Control.

IEEE transactions on neural networks and learning systems·2022
Same author

Chiral wheel anions of copper(II)-early lanthanides(III) with high optical-limiting properties.

Dalton transactions (Cambridge, England : 2003)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 30, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K

Cooperative Obstacle Avoidance for Multiple UAVs Using Spline_VO Method.

Mingzhu Peng1, Wei Meng1

  • 1The Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.

Sensors (Basel, Switzerland)
|March 10, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a cooperative algorithm for multiple unmanned aerial vehicle (UAV) dynamic collision avoidance, enhancing safety and communication efficiency using a novel filtering mechanism and velocity obstacle method for smooth path generation.

Keywords:
cooperative obstacle avoidancecubic B-splinemultiple UAVvelocity obstacle

More Related Videos

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.1K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.3K

Related Experiment Videos

Last Updated: Sep 30, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.1K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.3K

Area of Science:

  • Robotics
  • Aerospace Engineering
  • Artificial Intelligence

Background:

  • Multiple unmanned aerial vehicle (UAV) systems require robust dynamic collision avoidance strategies.
  • Existing methods often neglect kinematic constraints, limiting real-world applicability.
  • Efficient communication protocols are crucial for cooperative UAV operations.

Purpose of the Study:

  • To develop a cooperative obstacle avoidance algorithm for multiple UAVs.
  • To incorporate UAV kinematic constraints into the collision avoidance strategy.
  • To enhance communication performance and path smoothness for practical applications.

Main Methods:

  • A Heartbeat information filtering mechanism screens and fuses relevant UAV data.
  • User Datagram Protocol (UDP) communication enhances data exchange efficiency.
  • The velocity obstacle (VO) method is combined with cubic uniform B-spline curves for path planning.

Main Results:

  • The algorithm effectively addresses dynamic collision avoidance for multiple UAVs.
  • Communication performance is improved through efficient information filtering and UDP.
  • Smooth and dynamically feasible paths are generated, suitable for practical scenarios.

Conclusions:

  • The developed cooperative algorithm successfully enables dynamic collision avoidance for multiple UAVs.
  • The integration of kinematic constraints and advanced path planning ensures safe and efficient operation.
  • The proposed method offers a viable solution for complex multi-UAV systems.