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

14.2K
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...
14.2K
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.3K
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...
4.3K
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

97
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...
97
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

428
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...
428
Elastic Collisions: Introduction01:00

Elastic Collisions: Introduction

13.0K
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...
13.0K
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

12.5K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
12.5K

You might also read

Related Articles

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

Sort by
Same author

Risk-Sensitive Markov Decision Processes of USV Trajectory Planning with Time-Limited Budget.

Sensors (Basel, Switzerland)·2023
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: Jul 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

Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning.

Hongyang Zhu1, Yi Ding2

  • 1College of Mathematics and Computer, Guangdong Ocean University, Zhanjiang 524091, China.

Sensors (Basel, Switzerland)
|May 13, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces the Optimal Collision Avoidance Point (OCAP) method for unmanned surface vehicles (USVs) to enhance ship collision avoidance. OCAP improves path-finding efficiency, especially in complex, multi-obstacle scenarios.

Keywords:
collision avoidanceoptimal collision avoidance pointtrajectory optimizationvelocity obstacle method

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K
MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.7K

Related Experiment Videos

Last Updated: Jul 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
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K
MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.7K

Area of Science:

  • Robotics
  • Marine Engineering
  • Autonomous Systems

Background:

  • Ship collision avoidance is critical for maritime safety and autonomous navigation.
  • Unmanned Surface Vehicles (USVs) require robust systems for real-time decision-making in dynamic environments.
  • Existing methods face challenges with multiple moving obstacles and complex USV dynamics.

Purpose of the Study:

  • To propose a novel Optimal Collision Avoidance Point (OCAP) method for USVs.
  • To enhance the safety and efficiency of collision avoidance maneuvers for autonomous vessels.
  • To develop a real-time collision avoidance strategy for dynamic, multi-obstacle maritime scenarios.

Main Methods:

  • Integration of a two-degrees-of-freedom USV dynamics model with a velocity obstacle method.
  • Calculation of the Optimal Collision Avoidance Point (OCAP) based on relative velocities and kinematic parameters.
  • Dynamic window sampling constrained by velocity and heading increments to reach the OCAP.
  • Collision hazard probability assessment for trajectory evaluation.

Main Results:

  • The OCAP algorithm demonstrates superior and robust path-finding efficiency compared to other methods.
  • Effectiveness shown in scenarios with high dynamic obstacle density.
  • Successful real-time handling of multiple moving obstacles.

Conclusions:

  • The OCAP method provides an effective solution for USV collision avoidance.
  • The algorithm is optimized for USV maneuverability and real-time performance.
  • OCAP enhances navigation safety and efficiency in complex maritime traffic.