仿生腱驱动机械手实现高精度力控，提升工业抓取性能。
Development of the Bioinspired Tendon-Driven DexHand 021 with Proprioceptive Compliance Control
- 采用肌腱驱动与本体感觉力控结合，19自由度轻量化设计。
- 单指承重超10牛，力估误差低于0.2牛，重复定位精度达0.001米。
- 适合工业精密操作，助力智能制造业发展。
人类手在日常生活和工业应用中起着关键作用，但要复制其多功能能力——包括运动、感知及与机器人系统的协调操作——仍面临巨大挑战。开发灵巧的机器人手需在类人敏捷性与工程约束（如复杂性、尺寸重量比、耐用性、力感知性能）之间取得平衡。本文提出Dex-Hand 021，一款高性能、缆绳驱动的五指机器人手，具有12个主动自由度和7个被动自由度，共19个自由度，整体重量仅1公斤。我们提出一种基于本体感觉力感知的阻抗控制方法，以增强操控性能。实验结果表明：单指负载能力超过10 N，指尖重复性优于0.001 m，力估计误差低于0.2 N。相比传统PID控制，在多物体抓取中关节扭矩降低31.19%，显著提升力感知能力并防止碰撞过载。该手能完成33种GRASP分类动作及复杂操作任务，在力量与精度抓握上均表现优异。本研究推动了轻量化、工业级灵巧手的设计，并强化了本体感觉控制，为机器人操作与智能制造提供支持。
原文摘要 · Abstract (English)
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.
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