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

5.6K
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...
5.6K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

7.3K
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...
7.3K
Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

21.0K
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...
21.0K
Elastic Collisions: Introduction01:00

Elastic Collisions: Introduction

15.5K
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...
15.5K
Types of Collisions - II01:19

Types of Collisions - II

10.4K
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...
10.4K
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

923
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...
923

You might also read

Related Articles

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

Sort by
Same author

Apoptosis-inducing effect and structural basis of Polygonatum cyrtonema lectin and chemical modification properties on its mannose-binding sites.

BMB reports·2008
Same author

The catalytic intermediate stabilized by a "down" active site loop for diaminopimelate decarboxylase from Helicobacter pylori. Enzymatic characterization with crystal structure analysis.

The Journal of biological chemistry·2008
Same author

Monitoring prostate thermal therapy with diffusion-weighted MRI.

Magnetic resonance in medicine·2008
Same author

Removal of ammonia nitrogen in wastewater by microwave radiation.

Journal of hazardous materials·2008
Same author

[Three-dimensional anatomical position of rotatory center in cervical rotatory and local manipulation].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University·2008
Same author

Dysregulation of CREB binding protein triggers thrombin-induced proliferation of vascular smooth muscle cells.

Molecular and cellular biochemistry·2008
Same journal

Stackelberg differential game-based fuzzy adaptive hierarchical optimal control for a nonlinear system with unknown dynamics.

ISA transactions·2026
Same journal

Composite fault-tolerant predictive control strategy for PMSM demagnetization faults.

ISA transactions·2026
Same journal

Bias-compensated Q-learning for optimal tracking control under denial-of-service attacks.

ISA transactions·2026
Same journal

Motion prediction for leader manipulator of teleoperation system with large time delay based on inverse optimal control.

ISA transactions·2026
Same journal

Neural network parameter identification-based prescribed-time adaptive control for morphing glide aircraft.

ISA transactions·2026
Same journal

Nonlinear system-guided continuous-time generalization for cross-aircraft engine state monitoring.

ISA transactions·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

7.2K

Formation control and collision avoidance for multi-agent systems based on position estimation.

Yuanqing Xia1, Xitai Na1, Zhongqi Sun1

  • 1School of Automation, Beijing Institute of Technology, Beijing 100081, PR China.

ISA Transactions
|January 21, 2016
PubMed
Summary
This summary is machine-generated.

This study presents optimal and consensus-based formation control strategies for double-integrator systems using position estimation. The methods ensure agents achieve desired formations while avoiding collisions, validated by simulations and experiments.

Keywords:
Collision avoidanceFormation controlOptimal controlSecond-order systems

More Related Videos

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.4K
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

12.4K

Related Experiment Videos

Last Updated: Mar 26, 2026

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

7.2K
A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.4K
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

12.4K

Area of Science:

  • Robotics
  • Control Theory
  • Distributed Systems

Background:

  • Formation control is crucial for multi-agent systems.
  • Accurate position estimation is essential for effective control.
  • Existing methods may lack optimality or collision avoidance.

Purpose of the Study:

  • To develop and analyze novel formation control strategies for double-integrator systems.
  • To investigate optimal control and consensus-based approaches.
  • To incorporate collision avoidance into formation control.

Main Methods:

  • Derivation of an optimal control strategy based on a position estimator.
  • Presentation of an estimator-based consensus law for cooperative formation.
  • Integration of inter-collision avoidance control inputs.
  • Validation through simulation and experimental results.

Main Results:

  • The optimal control strategy drives agents to predefined formations.
  • The consensus law enables cooperative convergence to formations.
  • Collision avoidance is effectively integrated into the consensus strategy.
  • Proposed strategies demonstrate effectiveness in simulations and experiments.

Conclusions:

  • The developed formation control strategies are effective for double-integrator systems.
  • Optimality and stability are proven under specific conditions.
  • The integrated approach ensures both formation achievement and collision avoidance.