低成本力反馈手套让机器人操作更灵巧，成本低于600美元
DOGlove: Dexterous Manipulation with a Low-Cost Open-Source Haptic Force Feedback Glove
- 自研21自由度运动捕捉结构，5自由度多向力反馈
- 实现高精度远程操控，复杂接触任务成功率高
- 开源硬件与软件，适合机器人、人机交互研究者
灵巧手遥操作在实现机器人人类级操作灵巧性方面至关重要。然而，现有系统通常依赖昂贵设备且缺乏多模态感知反馈，限制了操作者对物体属性的感知和复杂操作能力。为此，我们提出DOGlove——一种低成本、高精度、带力反馈的手套系统，可在数小时内组装完成，成本低于600美元。该系统包含21-DoF定制关节结构用于运动捕捉，5-DoF紧凑缆绳驱动扭矩传输机制实现多向力反馈，以及5-DoF指尖触觉反馈线性共振执行器。通过动作与力反馈重映射，DOGlove实现了灵巧机器人手的精确沉浸式遥操作，在复杂接触任务中取得高成功率。我们在无视觉反馈场景下评估，验证了力反馈对任务表现的关键作用。此外，利用收集的操作数据训练模仿学习策略，展示了系统的潜力与有效性。硬件与软件将全开源，详见 https://do-glove.github.io/。
原文摘要 · Abstract (English)
Dexterous hand teleoperation plays a pivotal role in enabling robots to achieve human-level manipulation dexterity. However, current teleoperation systems often rely on expensive equipment and lack multi-modal sensory feedback, restricting human operators' ability to perceive object properties and perform complex manipulation tasks. To address these limitations, we present DOGlove, a low-cost, precise, and haptic force feedback glove system for teleoperation and manipulation. DoGlove can be assembled in hours at a cost under 600 USD. It features a customized joint structure for 21-DoF motion capture, a compact cable-driven torque transmission mechanism for 5-DoF multidirectional force feedback, and a linear resonate actuator for 5-DoF fingertip haptic feedback. Leveraging action and haptic force retargeting, DOGlove enables precise and immersive teleoperation of dexterous robotic hands, achieving high success rates in complex, contact-rich tasks. We further evaluate DOGlove in scenarios without visual feedback, demonstrating the critical role of haptic force feedback in task performance. In addition, we utilize the collected demonstrations to train imitation learning policies, highlighting the potential and effectiveness of DOGlove. DOGlove's hardware and software system will be fully open-sourced at https://do-glove.github.io/.
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