Development of the Bioinspired Tendon-Driven DexHand 021 with Proprioceptive Compliance Control

TL;DR

This paper introduces Dex-Hand 021, a lightweight, highly dexterous robotic hand with advanced proprioceptive force control, demonstrating superior manipulation capabilities and force sensing accuracy for industrial and complex tasks.

Contribution

The development of a novel cable-driven robotic hand with integrated proprioceptive force sensing and admittance control, achieving high dexterity, lightweight design, and improved manipulation performance.

Findings

Single-finger load capacity exceeds 10 N

Fingertip repeatability under 0.001 m

Force estimation errors below 0.2 N

Abstract

The human hand plays a vital role in daily life and industrial applications, yet replicating its multifunctional capabilities-including motion, sensing, and coordinated manipulation with robotic systems remains a formidable challenge. Developing a dexterous robotic hand requires balancing human-like agility with engineering constraints such as complexity, size-to-weight ratio, durability, and force-sensing performance. This letter presents Dex-Hand 021, a high-performance, cable-driven five-finger robotic hand with 12 active and 7 passive degrees of freedom (DoFs), achieving 19 DoFs dexterity in a lightweight 1 kg design. We propose a proprioceptive force-sensing-based admittance control method to enhance manipulation. Experimental results demonstrate its superior performance: a single-finger load capacity exceeding 10 N, fingertip repeatability under 0.001 m, and force estimation errors below 0.2 N. Compared to PID control, joint torques in multi-object grasping are reduced by 31.19%, significantly improves force-sensing capability while preventing overload during collisions. The hand excels in both power and precision grasps, successfully executing 33 GRASP taxonomy motions and complex manipulation tasks. This work advances the design of lightweight, industrial-grade dexterous hands and enhances proprioceptive control, contributing to robotic manipulation and intelligent manufacturing.