DOGlove: Dexterous Manipulation with a Low-Cost Open-Source Haptic Force Feedback Glove
Han Zhang, Songbo Hu, Zhecheng Yuan, Huazhe Xu

TL;DR
DOGlove is an affordable, open-source haptic glove enabling precise teleoperation of robotic hands with multi-modal feedback, improving manipulation success rates and supporting imitation learning in complex tasks.
Contribution
We introduce DOGlove, a low-cost, open-source haptic glove with multi-DoF feedback and a novel design for dexterous teleoperation, advancing accessible robotic manipulation technology.
Findings
High success rates in complex tasks with DOGlove
Effective haptic feedback improves task performance without visual cues
Demonstrated potential for training imitation learning policies
Abstract
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,…
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Taxonomy
TopicsTeleoperation and Haptic Systems
