Abstract
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.
Abstract (translated)
腱驱动欠驱动手在自适应抓取方面表现卓越，但常受运动学不可预测性及高度非线性的力传递问题困扰。这种模糊性限制了其在复杂操作任务中实现精确自由运动塑形和可靠负载输送的能力。针对此问题，我们提出了PHANTOM手（混合精度增强顺应性系统）：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（DoFs）。我们提出一个统一框架，弥合精确解析塑形与稳健顺应抓取之间的鸿沟。通过从物理几何推导稀疏映射，并整合基于力学的补偿模型，我们有效抑制了由弹簧反向张力和腱弹性引起的运动学漂移。该方法在保持稳定物理交互所需固有机械顺应性的同时，实现了自由运动规划的亚度级运动学复现精度。实验验证通过以下四点确认了系统能力：（1）运动学分析验证了工作空间内亚度级的全局精度；（2）静态表现力测试展示了复杂手势；（3）涵盖动力抓取、精确抓取及工具使用类别的多样化抓取实验；（4）定量指尖力表征。结果表明，PHANTOM手成功结合了解析运动学精度与连续、可预测的力输出，显著拓展了欠驱动手的负载能力和灵巧性。为推动欠驱动操作生态系统发展，所有硬件设计与控制脚本均已完全开源以供社区使用。
URL
https://arxiv.org/abs/2603.23152
