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

Elastic Strain Energy for Shearing Stresses01:20

Elastic Strain Energy for Shearing Stresses

277
As discussed in previous lessons, strain energy in a material is the energy stored when it is elastically deformed, a concept crucial in materials science and mechanical engineering. This energy results from the internal work done against the cohesive forces within the material. When a material undergoes shearing stress and corresponding shearing strain, the strain energy density, which is the energy stored per unit volume, is calculated. Within the elastic limit, where the stress is...
277
Shear and Bending Moment Diagram: Problem Solving01:24

Shear and Bending Moment Diagram: Problem Solving

1.9K
When analyzing a beam supporting concentrated loads and a distributed load, drawing the shear and bending moment diagrams is essential. These diagrams help understand the internal forces and moments acting on the beam, which is crucial for designing safe and efficient structures. Follow these steps to create the shear and bending moment diagrams:
Draw a Free-Body Diagram: Start by drawing a free-body diagram of the entire beam, including the concentrated loads, distributed load, and reaction...
1.9K
Angle of Twist - Elastic Range01:13

Angle of Twist - Elastic Range

392
Consider a cylindrical shaft with a length denoted by L and a consistent cross-sectional radius referred to as r. This shaft undergoes a torque at the free end. The highest shearing strain within the shaft is directly proportional to the twist angle and the radial distance from the shaft axis. When the shaft behaves elastically, this shearing strain can be articulated using variables such as the applied torque, radial distance, the polar moment of inertia, and the modulus of rigidity. By...
392
Shearing Strain01:20

Shearing Strain

620
The shearing strain represents a cubic element's angular change when subjected to shearing stress. This type of stress can transform a cube into an oblique parallelepiped without influencing normal strains. The cubic element experiences a significant transformation when exposed solely to shearing stress. Its shape alters from a perfect cube into a rhomboid, clearly demonstrating the effect of shearing strain. The degree of this strain is considered positive if it reduces the angle between...
620
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

853
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...
853
Shearing Stress01:19

Shearing Stress

850
Shearing stress, denoted by the Greek letter tau (τ), is stress caused by forces acting transversely on an object. These forces create internal ones within the entity in the plane where the external forces are applied. The resultant of these internal forces is the shear in the section.
The average shearing stress can be calculated by dividing the shear by the area of the cross-section.
850

You might also read

Related Articles

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

Sort by
Same author

The undulating tripod gait as a model of the locomotion of walking fish.

Nature communications·2026
Same author

A minimalistic walking fish robot twin based on the single actuator wave-like mechanism.

Bioinspiration & biomimetics·2025
Same author

Soft robotics: what's next in bioinspired design and applications of soft robots?

Bioinspiration & biomimetics·2025
Same author

Embodied intelligence paradigm for human-robot communication.

Science robotics·2025
Same author

Automated Benchmarking of Variable-Property Soft Robotic Fingertips to Enable Task-Optimized Sensor Selection.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

Multimodal information structuring with single-layer soft skins and high-density electrical impedance tomography.

Science robotics·2025
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 9, 2025

Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements
05:49

Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements

Published on: December 2, 2022

2.8K

Soft Shear Sensing of Robotic Twisting Tasks Using Reduced-Order Conductivity Modeling.

Dhruv Trehan1, David Hardman1, Fumiya Iida1

  • 1Bio-Inspired Robotics Laboratory, University of Cambridge, Cambridge CB2 1PZ, UK.

Sensors (Basel, Switzerland)
|August 28, 2025
PubMed
Summary
This summary is machine-generated.

Researchers developed new models for soft robotic fingertips using electrical impedance tomography (EIT) to predict shear forces during tasks like screwdriver twisting. This advance improves robotic manipulation by enabling faster, more accurate tactile sensing.

Keywords:
electrical impedance tomographyrobotic tool usesoft sensors

More Related Videos

Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets
09:38

Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets

Published on: November 7, 2016

8.9K
Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation
07:49

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation

Published on: August 2, 2016

8.9K

Related Experiment Videos

Last Updated: Sep 9, 2025

Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements
05:49

Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements

Published on: December 2, 2022

2.8K
Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets
09:38

Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets

Published on: November 7, 2016

8.9K
Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation
07:49

Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation

Published on: August 2, 2016

8.9K

Area of Science:

  • Robotics
  • Sensor Technology
  • Materials Science

Background:

  • Dexterous robotic manipulation relies on rich tactile feedback from artificial fingertips.
  • Shear sensing is crucial for tasks like twisting and dragging, but research in soft sensors using electrical impedance tomography (EIT) is limited.
  • EIT technology offers a promising avenue for developing advanced tactile sensors.

Purpose of the Study:

  • To investigate soft shear predictions using EIT for robotic manipulation.
  • To develop and analyze reduced-order models for relating screwdriver twisting tasks to conductivity maps in EIT sensors.
  • To enable high-speed, closed-loop robotic control through improved tactile sensing.

Main Methods:

  • Proposed and investigated five reduced-order models for EIT-based shear sensing.
  • Analyzed EIT signals generated during screwdriver twisting tasks.
  • Correlated reduced-order model parameters with physical measurements like torque and diameter.

Main Results:

  • Achieved high correlations (0.96 for torque, 0.97 for diameter) between reduced-order parameters and physical measurements.
  • Demonstrated that insights can be deduced from noisy EIT signals using the proposed models.
  • Showcased the potential for precalculating Finite Element Method (FEM) model signals, unlike traditional methods.

Conclusions:

  • The developed reduced-order models effectively predict shear-based twisting in robotic fingertips using EIT.
  • This approach offers a pathway towards real-time, high-speed closed-loop robotic manipulation systems.
  • The findings advance the field of soft robotics and tactile sensing for complex manipulation tasks.