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Related Experiment Video

Updated: Jun 23, 2025

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
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Design and Control of a Tendon-Driven Robotic Finger Based on Grasping Task Analysis.

Xuanyi Zhou1,2,3, Hao Fu2,4, Baoqing Shentu1

  • 1State Key Laboratory of Chemical Engineering, College of Chemical and Biological Engineering, Zhejiang University, 38 Zheda Road, Hangzhou 310027, China.

Biomimetics (Basel, Switzerland)
|June 26, 2024
PubMed
Summary

Researchers analyzed human hand grasping by designing 12 tendon-driven finger paths. Specific paths optimized tendon tension, joint angle control, and reduced friction, offering valuable insights for robotic hand design.

Keywords:
grasphuman-inspiredmanipulationprosthetic hand

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Area of Science:

  • Robotics
  • Biomechanics
  • Human-Computer Interaction

Background:

  • Understanding human hand structural characteristics is crucial for developing advanced robotic hands.
  • Grasping tasks involve complex manipulation, finger pressure, and joint angle dynamics.

Purpose of the Study:

  • To analyze human hand structural characteristics during grasping tasks.
  • To design and evaluate novel tendon rope transmission paths for tendon-driven fingers.
  • To develop a motion performance model for tendon-driven fingers.

Main Methods:

  • Data collection gloves were used to record hand manipulation characteristics, finger end pressure, and joint bending angles during typical grasping tasks.
  • Twelve types of tendon rope transmission paths were designed under an N + 1 type tendon drive mode.
  • The motion performance of each path was evaluated using a defined metric.

Main Results:

  • Tendon path (d) demonstrated effective control of tendon tension fluctuations (within 0.25 N).
  • Tendon path (e) provided the best control over the joint angle of the tendon-driven finger.
  • Tendon path (l) was most effective in minimizing friction between the tendon and pulley.

Conclusions:

  • The study provides a motion performance model for tendon-driven fingers based on 12 evaluated paths.
  • The findings serve as a valuable reference for future tendon-driven finger structure design and control strategies.
  • Optimized tendon path designs can significantly improve the performance of robotic hands.