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

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

425
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...
425
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

482
Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...
482
Coplanar Forces01:25

Coplanar Forces

4.1K
Consider an object upon which multiple forces are acting. If the lines of action of each force lie within the same plane, the system can be considered coplanar. The Cartesian vector form can be used to resolve each force into its respective components. For a coplanar system, the system will be in equilibrium if each component of the resultant force equals zero and the resultant force on the system is zero. If the sum of the forces is not equal to zero, then the object will not be in equilibrium...
4.1K
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

519
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...
519
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

696
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...
696
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

490
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
490

You might also read

Related Articles

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

Sort by
Same author

Adoption of assistive technologies in long-term care homes: What the pandemic has taught us.

Healthcare management forum·2024
Same author

SoftSAR: The New Softer Side of Socially Assistive Robots-Soft Robotics with Social Human-Robot Interaction Skills.

Sensors (Basel, Switzerland)·2023
Same author

A Meta-Analysis on Remote HRI and In-Person HRI: What Is a Socially Assistive Robot to Do?

Sensors (Basel, Switzerland)·2022
Same author

Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in human-robot interaction.

Science robotics·2021
Same journal

A Survey of Robotic Harvesting Systems and Enabling Technologies.

Journal of intelligent & robotic systems·2023
Same journal

A Sim-to-real Practical Approach to Teach Robotics into K-12: A Case Study of Simulators, Educational and DIY Robotics in Competition-based Learning.

Journal of intelligent & robotic systems·2023
Same journal

Robotics Research Growth in Latin America: Topical Collection on LARS 2020.

Journal of intelligent & robotic systems·2023
Same journal

Co-design Optimization of a Novel Multi-identity Drone Helicopter (MICOPTER).

Journal of intelligent & robotic systems·2022
Same journal

Wheeled Mobile Robots: State of the Art Overview and Kinematic Comparison Among Three Omnidirectional Locomotion Strategies.

Journal of intelligent & robotic systems·2022
Same journal

The Use of Drones in the Area of Minimizing Health Risk during the COVID-19 Epidemic.

Journal of intelligent & robotic systems·2022
See all related articles

Related Experiment Video

Updated: Jul 27, 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

A Concurrent Mission-Planning Methodology for Robotic Swarms Using Collaborative Motion-Control Strategies.

Kasra Eshaghi1, Goldie Nejat1, Beno Benhabib1

  • 1Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Rd, Toronto, ON M5S 3G8 Canada.

Journal of Intelligent & Robotic Systems
|June 5, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for swarm robotics mission planning that optimizes both worker and support robots simultaneously. This concurrent approach improves swarm mission performance by nearly 40% compared to sequential planning.

Keywords:
Constrained optimizationLocalizationMotion planningSwarm RoboticsTask-allocation

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
Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays
07:35

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

Published on: April 7, 2015

24.2K

Related Experiment Videos

Last Updated: Jul 27, 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
Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays
07:35

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

Published on: April 7, 2015

24.2K

Area of Science:

  • Robotics and Artificial Intelligence
  • Swarm Intelligence
  • Mission Planning and Optimization

Background:

  • Swarm robotic systems with limited localization require collaborative motion-control strategies for multi-task missions.
  • Existing mission-planning methods for swarms divide robots into workers and support roles, optimizing sequentially, leading to suboptimal plans.
  • Current approaches optimize worker robot plans first, then use rule-based methods for support robots, failing to achieve swarm-level optimality.

Purpose of the Study:

  • To present a novel mission-planning methodology that concurrently optimizes plans for both worker and support robots in swarm systems.
  • To improve overall swarm mission execution performance by addressing the limitations of sequential planning strategies.
  • To develop a pre-implementation estimator for predicting performance improvements achievable with the proposed methodology.

Main Methods:

  • A five-stage concurrent optimization methodology: division-of-labor, task-allocation, worker robot path-planning, movement-concurrency, and movement-allocation.
  • Simultaneous optimization of all planning stages to find optimal variables for worker and support robots.
  • Development of a machine learning-based pre-implementation estimator to forecast performance gains.

Main Results:

  • The proposed concurrent methodology significantly enhances swarm mission execution performance by nearly 40% over sequential methods.
  • The concurrent approach effectively plans for simultaneous facilitation of multiple independent worker robot group movements.
  • The pre-implementation estimator demonstrated high accuracy, achieving an estimation error of less than 5%.

Conclusions:

  • Concurrent optimization of worker and support robot plans is crucial for efficient swarm mission execution.
  • The novel methodology offers a more effective approach to swarm mission planning, applicable to various collaborative strategies.
  • The developed estimator provides a valuable tool for justifying computational resources for advanced mission planning.