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

839
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...
839
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

1.0K
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...
1.0K
Open and closed-loop control systems01:17

Open and closed-loop control systems

2.0K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
2.0K

You might also read

Related Articles

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

Sort by
Same author

Catecholamine precursor modulation of human exploration: Evidence from a large gender-balanced sample.

PLoS computational biology·2026
Same author

The earlier you know, the smoother you act: anticipatory control in solo and dyadic juggling.

Experimental brain research·2026
Same author

Exploration Strategies and Feature Prioritisation in Contour-based Haptic Perception of 2D Shape.

IEEE transactions on haptics·2026
Same author

Open science practices in behavioral addictions: An exploratory survey.

Journal of behavioral addictions·2026
Same author

[Use of continuous passive motion in inpatient rehabilitation after shoulder replacement-a retrospective study].

Orthopadie (Heidelberg, Germany)·2026
Same author

Hoffa-Kastert Syndrome: A Rare Cause of Acute Knee Blockade.

Indian journal of orthopaedics·2025
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

IEEE transactions on neural networks and learning systems·2026
Same journal

CAFF-CIL: Causality-Aware Freedom Forgetting Approach for Class-Incremental Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Harmonic Autoencoding Framework for Multiple Tasks in Magnetic Particle Imaging Reconstruction.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Survey on Human-Centric Voice-Face Multimodal Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Vision-Assisted Foundation Model for Solving Multitask Vehicle Routing Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

FP3O: Enabling Proximal Policy Optimization in Multiagent Cooperation With Parameter-Sharing Versatility.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Apr 30, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

11.5K

Online kernel-based learning for task-space tracking robot control.

Duy Nguyen-Tuong, Jan Peters

    IEEE Transactions on Neural Networks and Learning Systems
    |May 9, 2014
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel local kernel-based learning method for robot control. It addresses challenges in learning task-space control models from data, enabling more accurate robot tracking control.

    More Related Videos

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
    10:51

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

    Published on: March 10, 2011

    16.1K
    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

    11.0K

    Related Experiment Videos

    Last Updated: Apr 30, 2026

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
    11:18

    Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

    Published on: March 2, 2015

    11.5K
    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
    10:51

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

    Published on: March 10, 2011

    16.1K
    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

    11.0K

    Area of Science:

    • Robotics
    • Control Systems
    • Machine Learning

    Background:

    • Analytical models for task-space control of redundant robots are sensitive to modeling errors.
    • Data-driven methods offer an alternative but learning task-space tracking control from data is ill-posed.
    • Existing regression methods fail due to non-convex solution spaces arising from data ambiguity.

    Purpose of the Study:

    • To develop a robust online model learning approach for task-space tracking control.
    • To overcome the ill-posed nature of learning control mappings from sampled data.
    • To enable accurate control of redundant robot systems in the task space.

    Main Methods:

    • Formulated a local kernel-based learning approach leveraging the locally well-defined nature of the problem.
    • Proposed a specific local model parametrization suitable for redundant robot task-space tracking control.
    • Utilized the kernel-trick for efficient computation within the kernel learning framework.

    Main Results:

    • Demonstrated the capability of the proposed method for online model learning.
    • Successfully applied the local kernel-based approach to task-space tracking control.
    • Validated the effectiveness in handling redundant robot systems.

    Conclusions:

    • The local kernel-based learning approach effectively addresses the ill-posed problem of learning task-space control mappings.
    • The proposed method enables accurate online model learning for redundant robot task-space tracking control.
    • This approach offers a viable data-driven alternative to traditional analytical modeling methods.