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

Feedback control systems01:26

Feedback control systems

462
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
462
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

180
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
180
PD Controller: Design01:26

PD Controller: Design

370
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
370
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

3.8K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
3.8K
Response Surface Methodology01:16

Response Surface Methodology

305
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
305
Dose-Response Relationship: Selectivity and Specificity01:25

Dose-Response Relationship: Selectivity and Specificity

8.5K
Drugs exert their therapeutic effects by interacting with receptors, enzymes, or ion channels that are present throughout the human body. The strength and duration of the interaction between a drug and its target receptor are characterized by the selectivity and specificity of the drug. Selectivity refers to a drug's strong preference for its intended target over other targets. For instance, isoprenaline, a non-selective β-adrenergic agonist, interacts with both β1- and...
8.5K

You might also read

Related Articles

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

Sort by
Same author

Joint Optimization of User Association and Dynamic Multi-UAV Deployment for Maritime Emergency Communications.

Entropy (Basel, Switzerland)·2026
Same author

Periodic event-triggered generalized dissipative state estimation for hidden semi-Markov jump systems.

ISA transactions·2026
Same author

Revisiting the Model Human Processor: a neurophysiological investigation based on P300 and Bereitschaftspotential.

Frontiers in human neuroscience·2025
Same author

Data-driven dual-channel dynamic event-triggered load frequency control for multiarea power systems with uniform quantizer.

Science progress·2025
Same author

Neural SDE-based spike control of noisy neurons.

PloS one·2025
Same author

Swarm shepherding using bearing-only measurements.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025
Same journal

Modeling the impact of budget limitation on the screening and treatment pathway of HPV-induced precancerous cervical lesions.

Mathematical biosciences and engineering : MBE·2026
Same journal

Modeling the effects of trait-mediated dispersal on coexistence of two species: Competition and non-consumptive predator-prey.

Mathematical biosciences and engineering : MBE·2026
Same journal

A close look at the viral reduction rate in target cell limited models.

Mathematical biosciences and engineering : MBE·2026
Same journal

A stochastic agent-based model for simulating tumor-immune dynamics and evaluating therapeutic strategies.

Mathematical biosciences and engineering : MBE·2026
Same journal

Addressing domain shift via imbalance-aware domain adaptation in embryo development assessment.

Mathematical biosciences and engineering : MBE·2026
Same journal

Effect of drug resistance on an HIV epidemic in heterogeneous populations.

Mathematical biosciences and engineering : MBE·2026
See all related articles

Related Experiment Video

Updated: Sep 28, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K

Iterative shepherding control for agents with heterogeneous responsivity.

Ryoto Himo1, Masaki Ogura1, Naoki Wakamiya1

  • 1Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.

Mathematical Biosciences and Engineering : MBE
|March 28, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel sheepdog algorithm to guide unresponsive sheep in multi-agent systems. The new method iteratively guides agents, enabling control over the entire flock for successful navigation to a goal region.

Keywords:
farthest-agent targetingheterogeneitymulti-agent systemsshepherding

More Related Videos

Modeling Verbal Behavior Deficits with the Stimulus Control Ratio Equation, SCoRE
06:57

Modeling Verbal Behavior Deficits with the Stimulus Control Ratio Equation, SCoRE

Published on: May 14, 2019

10.6K
WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.1K

Related Experiment Videos

Last Updated: Sep 28, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K
Modeling Verbal Behavior Deficits with the Stimulus Control Ratio Equation, SCoRE
06:57

Modeling Verbal Behavior Deficits with the Stimulus Control Ratio Equation, SCoRE

Published on: May 14, 2019

10.6K
WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.1K

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Multi-Agent Systems

Background:

  • The shepherding problem involves guiding a flock of agents (sheep) into a goal region using a herding agent (sheepdog).
  • Existing algorithms are effective but often fail when sheep agents are unresponsive to the sheepdog.
  • A significant gap exists in addressing the shepherding problem with unresponsive agents.

Purpose of the Study:

  • To propose a new sheepdog algorithm capable of guiding unresponsive sheep.
  • To develop a method that enables control over flocks with heterogeneous agent responsiveness.
  • To enhance the robustness of multi-agent system navigation.

Main Methods:

  • The proposed algorithm iteratively applies the farthest-agent targeting algorithm.
  • The sheepdog dynamically switches its destination during the herding process.
  • This approach facilitates the incremental growth of a controllable flock.

Main Results:

  • The algorithm successfully guides unresponsive sheep into the goal region.
  • Numerical simulations demonstrate the algorithm's effectiveness.
  • The proposed method outperforms the standard farthest-agent targeting algorithm.

Conclusions:

  • The developed sheepdog algorithm effectively addresses the challenge of unresponsive agents in multi-agent systems.
  • This research expands the applicability of shepherding algorithms to more complex and realistic scenarios.
  • The findings contribute to the advancement of autonomous navigation and coordination in multi-agent systems.