arXiv:2603.23152cs.RO2026-03

PHANTOM手通过精准建模与补偿,让柔性机械手既灵活又可预测。

PHANTOM Hand

  • 基于物理几何与力学补偿,抑制肌腱弹性带来的运动漂移
  • 实现亚度级运动重复性,支持复杂手势与稳定抓握
  • 开源设计,适合机器人抓取与人机交互研究者使用

肌腱驱动的欠驱动手在自适应抓握中表现优异,但常面临运动学不可预测和力传递高度非线性的问题,限制了其在精确自由运动规划和复杂操作中的应用。为此,我们提出PHANTOM Hand(混合高精度增强柔顺性):一个模块化、1:1人体尺度的系统,配备6个执行器和15个自由度。通过推导物理几何的稀疏映射并引入基于力学的补偿模型,有效抑制了弹簧反张力和肌腱弹性引起的运动漂移。该方法实现了自由运动规划下的亚度级运动重复性,同时保留了稳定物理交互所需的固有机械柔顺性。实验验证表明:(1)运动学分析证实工作空间内全局精度达亚度级;(2)静态表达测试展示复杂手势能力;(3)涵盖强力抓握、精细抓握和工具使用等多类抓握实验;(4)定量测量指尖受力特性。结果表明,PHANTOM手成功融合解析运动精度与连续可预测的力输出,显著提升欠驱动手的承载能力和灵巧性。为推动欠驱动操作生态发展,所有硬件设计与控制脚本均开源,供社区使用。

原文摘要 · Abstract (English)

Tendon-driven underactuated hands excel in adaptive grasping but often suffer from kinematic unpredictability and highly non-linear force transmission. This ambiguity limits their ability to perform precise free-motion shaping and deliver reliable payloads for complex manipulation tasks. To address this, we introduce the PHANTOM Hand (Hybrid Precision-Augmented Compliance): a modular, 1:1 human-scale system featuring 6 actuators and 15 degrees of freedom (DoFs). We propose a unified framework that bridges the gap between precise analytic shaping and robust compliant grasping. By deriving a sparse mapping from physical geometry and integrating a mechanics-based compensation model, we effectively suppress kinematic drift caused by spring counter-tension and tendon elasticity. This approach achieves sub-degree kinematic reproducibility for free-motion planning while retaining the inherent mechanical compliance required for stable physical interaction. Experimental validation confirms the system's capabilities through (1) kinematic analysis verifying sub-degree global accuracy across the workspace; (2) static expressibility tests demonstrating complex hand gestures; (3) diverse grasping experiments covering power, precision, and tool-use categories; and (4) quantitative fingertip force characterization. The results demonstrate that the PHANTOM hand successfully combines analytic kinematic precision with continuous, predictable force output, significantly expanding the payload and dexterity of underactuated hands. To drive the development of the underactuated manipulation ecosystem, all hardware designs and control scripts are fully open-sourced for community engagement.

机械手欠驱动力控开源

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