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

You might also read

Related Articles

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

Sort by
Same author

Trends and Influencing Factors in Temporal Psychological Well-Being of Adolescents: Evidence from a Longitudinal Study.

Behavioral sciences (Basel, Switzerland)·2026
Same author

Self-Healing Bilayer Hydrogel Solid-State Electrochemical Platform: Time-Resolved In Situ Dynamic Monitoring of <i>Escherichia coli</i> Activity.

Gels (Basel, Switzerland)·2026
Same author

Tightened coupling of organic nitrogen and organic carbon synthesis governs integrity of soil organic matter in black soils.

Environmental research·2026
Same author

Silica sphere-directed N-doped carbon-supported Ni catalysts boost electrochemical CO evolution for syngas production.

Chemical communications (Cambridge, England)·2026
Same author

Genome and transcriptome analyses reveal parallel altitude adaptation in Chenopodium.

Genome biology·2026
Same author

Dual roles and mechanisms of adipokines in nerve injury repair and pain regulation: a research review.

International immunopharmacology·2026
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

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

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

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

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

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

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

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

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

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

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

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

Related Experiment Video

Updated: Jul 29, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.7K

Learning-Based Slip Detection for Dexterous Manipulation Using GelStereo Sensing.

Shaowei Cui, Shuo Wang, Rui Wang

    IEEE Transactions on Neural Networks and Learning Systems
    |May 24, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a learning-based slip detection system using GelStereo (GS) tactile sensing, achieving 95.79% accuracy. The system enables adaptive robot control for dexterous manipulation tasks.

    More Related Videos

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
    08:15

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

    Published on: March 28, 2025

    671
    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
    07:05

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

    Published on: October 27, 2016

    9.3K

    Related Experiment Videos

    Last Updated: Jul 29, 2025

    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
    09:41

    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

    Published on: April 21, 2023

    1.7K
    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
    08:15

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

    Published on: March 28, 2025

    671
    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
    07:05

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

    Published on: October 27, 2016

    9.3K

    Area of Science:

    • Robotics
    • Artificial Intelligence
    • Materials Science

    Background:

    • Robots require tactile perception for improved manipulation dexterity and human-like touch.
    • GelStereo (GS) tactile sensing provides high-resolution 2-D displacement fields and 3-D point clouds of contact surfaces.

    Purpose of the Study:

    • To develop a learning-based slip detection system using GS tactile sensing.
    • To propose a general framework for slip feedback adaptive control in robot manipulation.

    Main Methods:

    • Utilized GelStereo (GS) tactile sensing for high-resolution contact geometry data.
    • Developed and trained a neural network for slip detection.
    • Implemented a slip feedback adaptive control framework.

    Main Results:

    • The learning-based slip detection system achieved 95.79% accuracy on an unseen testing dataset.
    • The proposed control framework demonstrated effectiveness and efficiency in real-world grasping and screwing tasks.
    • The GS tactile feedback system surpassed existing model-based and learning-based visuotactile methods.

    Conclusions:

    • The developed learning-based slip detection system with GS tactile sensing is highly accurate.
    • The proposed adaptive control framework effectively enhances dexterous robot manipulation using tactile feedback.