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Hierarchical Procedural Framework for Low-latency Robot-Assisted Hand-Object Interaction

arXiv 2405.19531 ↗First posted 29 May 2024cs.RO cs.LGcited by 0

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Abstract (arXiv)

Advances in robotics have been driving the development of human-robot interaction (HRI) technologies. However, accurately perceiving human actions and achieving adaptive control remains a challenge in facilitating seamless coordination between human and robotic movements. In this paper, we propose a hierarchical procedural framework to enable dynamic robot-assisted hand-object interaction (HOI). An open-loop hierarchy leverages the RGB-based 3D reconstruction of the human hand, based on which motion primitives have been designed to translate hand motions into robotic actions. The low-level coordination hierarchy fine-tunes the robot's action by using the continuously updated 3D hand models. Experimental validation demonstrates the effectiveness of the hierarchical control architecture. The adaptive coordination between human and robot behavior has achieved a delay of ≤ 0.3 seconds in the tele-interaction scenario. A case study of ring-wearing tasks indicates the potential application of this work in assistive technologies such as healthcare and manufacturing.

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References · 7

  1. 2021Mesh Graphormercited by 265
  2. 2017Learning to Estimate 3D Hand Pose from Single RGB Imagescited by 234
  3. 2022Embodied Hands: Modeling and Capturing Hands and Bodies Togethercited by 181
  4. 20193D Hand Shape and Pose Estimation from a Single RGB Imagecited by 174
  5. 2022OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interactioncited by 131
  6. 2020CPF: Learning a Contact Potential Field to Model the Hand-Object Interactioncited by 128
  7. 2022Motion Primitives-based Navigation Planning using Deep Collision Predictioncited by 11

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