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Secondary Motives: Affiliation Motivation and Aggression Motivation01:21

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Affiliation motivation is the intrinsic desire to connect with others and belong to a social group, which plays a crucial role in forming and maintaining personal relationships. This type of motivation is essential for psychological well-being, as it provides individuals with a sense of community and support. An example of this is a student who joins a study group in order to feel a sense of connection. People with high affiliation motivation actively seek social approval, take satisfaction in...
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Tactile and Chemical Senses01:27

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Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex.
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Related Experiment Video

Updated: Jan 28, 2026

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping
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Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor.

Carmelo Sferrazza1, Raffaello D'Andrea2

  • 1Institute for Dynamic Systems and Control, ETH Zurich, 8092 Zurich, Switzerland. csferrazza@ethz.ch.

Sensors (Basel, Switzerland)
|March 1, 2019
PubMed
Summary

This study introduces a novel vision-based tactile sensor that uses a random pattern and deep neural networks to achieve high-resolution force sensing. The artificial tactile sensor demonstrates performance comparable to human fingertips.

Keywords:
computer visionmachine learningoptical tactile sensorsroboticstactile sensing

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Area of Science:

  • Robotics and Artificial Intelligence
  • Biomimetic Engineering
  • Sensor Technology

Background:

  • Human skin possesses remarkable tactile sensing capabilities, crucial for interaction with the environment.
  • Developing artificial tactile sensors requires mimicking high resolution, accuracy, and scalability.
  • Existing artificial touch systems often struggle with large surface areas and complex shapes.

Purpose of the Study:

  • To develop a scalable, high-resolution artificial tactile sensor.
  • To reconstruct normal force distribution on a soft material using visual data.
  • To achieve tactile sensing performance comparable to the human fingertip.

Main Methods:

  • Utilizing a vision-based approach with high-resolution image sensors.
  • Embedding a random pattern within a soft material to leverage full camera resolution.
  • Training a deep neural network on experimental data for force reconstruction.
  • Analyzing sensor design and motivation using a simplified elasticity model.

Main Results:

  • The vision-based tactile sensor accurately reconstructs normal force distribution.
  • The system achieves high accuracy for a specific indenter.
  • Demonstrates spatial resolution and sensing range comparable to the human fingertip.
  • Exploits the full resolution of modern image sensors effectively.

Conclusions:

  • The proposed vision-based tactile sensor offers a promising solution for artificial touch.
  • The approach enables scalable and high-resolution force sensing for complex surfaces.
  • Deep neural networks combined with visual deformation analysis are effective for tactile sensing.