Humans rely on directional fingertip forces to probe and regulate contact during manipulation, yet most wearable haptic gloves render only vibration or single-axis force, leaving force direction ambiguous. Without directional cues, users must infer contact force from vision alone, often leading to over-pressing, inconsistent control, and reduced precision in robotic teleoperation. We present the N2D Haptic Glove, a multi-finger wearable device that renders planar flexion-extension fingertip forces using capstan-drive transmissions for high-transparency force feedback. Through benchtop validations and a user study involving haptic teleoperation of a robotic arm and hand, we demonstrate that compared to visual-only and single-axis haptic baselines, planar fingertip feedback significantly reduces contact force error during precise manipulation, improves trial-to-trial consistency, and enhances overall user experience in axial probing tasks. These findings establish the N2D Haptic Glove and directional finger-based haptics devices as a promising modality for contact-rich teleoperation, immersive virtual reality simulations, and robot learning from demonstrations. N2D Haptic Glove's hardware and software system will be fully open-sourced at \href{https://ucsdarclab.github.io/n2d-glove/}{this https URL}.

翻译：人类在操作过程中依赖指尖方向力来探测和调节接触，然而大多数可穿戴触觉手套仅能提供振动或单轴力反馈，导致力的方向模糊不清。缺乏方向提示时，用户只能通过视觉推断接触力，这经常导致过度按压、控制不一致以及机器人遥操作精度下降。我们提出N2D触觉手套，这是一种利用绞盘驱动传动实现高透明度力反馈、可提供平面屈伸指尖力的多指可穿戴设备。通过台架验证以及涉及机器人手臂和手部触觉遥操作的用户研究，我们证明：与纯视觉和单轴触觉基线相比，平面指尖力反馈能够显著降低精确操作过程中的接触力误差，提高试验间一致性，并增强轴向探测任务中的整体用户体验。这些发现确立了N2D触觉手套及基于方向手指的触觉设备在接触丰富遥操作、沉浸式虚拟现实模拟以及机器人示教学习中的发展潜力。N2D触觉手套的硬件和软件系统将在\href{https://ucsdarclab.github.io/n2d-glove/}{此网址}完全开源。