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Related Experiment Video

Updated: Dec 18, 2025

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Discrimination of Object Curvature Based on a Sparse Tactile Sensor Array.

Weiting Liu1, Binpeng Zhan1, Chunxin Gu1

  • 1State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310007, China.

Micromachines
|June 14, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for estimating object curvature using a tactile sensor array and artificial neural networks (ANNs). The approach achieves high accuracy, offering a promising solution for robotic manipulation and grasping.

Keywords:
compliant contactdiscrimination of curvaturemachine learningneural networksparse tactile sensor array

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Sensor Technology

Background:

  • Object curvature is crucial for effective grasping and manipulation.
  • Traditional vision-based methods are limited during object manipulation due to occluded contact areas.
  • Tactile sensing offers an alternative for extracting local curvature information.

Purpose of the Study:

  • To develop an object curvature estimation method using a sparse tactile sensor array and artificial neural network (ANN) algorithm.
  • To evaluate the performance of the proposed method on various object shapes and radii.
  • To compare the method's performance with human tactile discrimination capabilities.

Main Methods:

  • A lab-developed sparse tactile sensor array with a compliant layer was utilized.
  • An artificial neural network (ANN) algorithm was employed for curvature estimation.
  • Experiments were conducted using plane, convex sphere, and convex cylinder samples with radii ranging from 1 mm to 30 mm.

Main Results:

  • The overall classification accuracy for object curvature was 93.1%.
  • The average curvature radius estimation error using the ANN algorithm was 1.87 mm.
  • For radii larger than 5 mm, the average relative error was less than 20%.

Conclusions:

  • The proposed tactile sensing method with ANN provides accurate object curvature estimation.
  • The method demonstrates performance comparable to human tactile sensory receptors (SAII).
  • This technique shows significant potential for applications in robotic manipulation and grasping.