Multidimensional Performance Comparison and Evolutionary Trends of Typical Transmission Systems for Underactuated Robotic Hands

Main Article Content

Songyi Wang
School of Mechanical Engineering, Shenyang Aerospace University, Shenyang 110136, China

DOI: https://doi.org/10.70267/cai.26v3n3.121127

Keywords

underactuated robotic hand, transmission system, rigid-flexible coupling, nonlinear control

Abstract

This review focuses on the transmission systems of underactuated robotic hands. It aims to compare the dynamic characteristics of three mainstream approaches—linkage, tendon-driven, and flexible structures—to reveal their performance bottlenecks and provide guidance for design optimization. Based on relevant theoretical and experimental data, the study comparatively analyzes key indicators such as force transmission efficiency, degrees of freedom, and environmental adaptability. The findings indicate that linkage transmission offers high stiffness and superior precision, making it suitable for heavy-load scenarios and widely used in aerospace applications. However, its bulky structure affects dynamic response speed. Tendon-driven transmission is lightweight and compliant, producing almost no rigid impact, which makes it ideal for biomimetic grasping and widely applied in medical rehabilitation due to its high safety. Nevertheless, it has insufficient lateral stiffness. Flexible structures exhibit strong adaptability to complex environments and are advantageous for handling fragile objects, such as in agricultural picking tasks, but suffer from low control precision and response lag. In summary, no universal solution exists. Future development should involve task-specific trade-offs in selection, exploration of hybrid mechanisms, or the integration of rigid-flexible coupled hybrid actuation systems.

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Published
Jun 12, 2026
Issue
Vol. 3 No. 3 (2026)
Section
Research Articles
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How to Cite

Wang, S. (2026). Multidimensional Performance Comparison and Evolutionary Trends of Typical Transmission Systems for Underactuated Robotic Hands. Computers and Artificial Intelligence, 3(3), 121-127. https://doi.org/10.70267/cai.26v3n3.121127