aiqbench analysis
This research introduces a digital-twin-based AR interface that converts tactile measurements into visual feedback to overcome force and occlusion limitations in bare-hand robot teleoperation. By rendering virtual representations of the robot and task objects, the system enhances the collection of high-quality demonstrations for teaching dexterous manipulation skills without requiring gloves or exoskeletons. The approach directly addresses critical sensory gaps in current robotic control methods, advancing the practicality of human-robot collaboration in complex tasks.
Now You Feel It, Now You See Me: Digital-Twin-based Teleoperation Interface for Dexterous Manipulation
arXiv:2610.05081v1 Announce Type: new Abstract: Teleoperation is becoming increasingly important for collecting high-quality demonstrations to teach robots dexterous manipulation skills. For dexterous manipulation, bare-hand tracking provides a practical way to control robotic hands and demonstrate coordinated finger movements without gloves or exoskeletons. However, this type of teleoperation faces two key feedback limitations: a lack of force feedback and visual feedback of occluded region. The absence of force feedback hinders precise and safe manipulation, as operators must infer contact force visually rather than feel them directly. Occlusion by objects or other robot parts impairs the assessment of hand positions, approach distances, and pre-grasp configurations suited to the object's shape. To address these limitations, we propose a digital-twin-based augmented reality (AR) teleoperation interface that integrates bare-hand tracking, bimanual robotic hands, and virtual representations of the robot and task objects. The interface renders tactile measurements on robot hand meshes as visuo-force feedback. Furthermore, it offers a user-controlled virtual view panel or occlusion-aware transparency rendering to provide occlusion-mitigating visual feedback. We evaluated the interface through user studies involving Task 1 and Task 2, examining how force visualization and visual assistance support demonstration collection in tasks requiring careful force regulation and manipulation under occlusion.
Abstract:Teleoperation is becoming increasingly important for collecting high-quality demonstrations to teach robots dexterous manipulation skills. For dexterous manipulation, bare-hand tracking provides a practical way to control robotic hands and demonstrate coordinated finger movements without gloves or exoskeletons. However, this type of teleoperation faces two key feedback limitations: a lack of force feedback and visual feedback of occluded region. The absence of force feedback hinders precise and safe manipulation, as operators must infer contact force visually rather than feel them directly. Occlusion by objects or other robot parts impairs the assessment of hand positions, approach distances, and pre-grasp configurations suited to the object's shape. To address these limitations, we propose a digital-twin-based augmented reality (AR) teleoperation interface that integrates bare-hand tracking, bimanual robotic hands, and virtual representations of the robot and task objects. The interface renders tactile measurements on robot hand meshes as visuo-force feedback. Furthermore, it offers a user-controlled virtual view panel or occlusion-aware transparency rendering to provide occlusion-mitigating visual feedback. We evaluated the interface through user studies involving Task 1 and Task 2, examining how force visualization and visual assistance support demonstration collection in tasks requiring careful force regulation and manipulation under occlusion.
Robotics (cs.RO)
arXiv:2610.05081 [cs.RO]
(or arXiv:2610.05081v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2610.05081 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 287 words
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