TacHair: Tactile Contact-Distribution Guided Online Correction for Robotic Hair Stroking and Perception

Key points

• Hair stroking is common in daily grooming and personal care, and is also widely used in hair-product evaluation, motivating robots with similar physical interaction capabilities.1
• Existing robotic hair-care and surface-following methods mainly rely on trajectory planning, compliance, force regulation, or tactile-conditioned policies, but deformable hair can remain in contact while gradually drifting across the end-effector, making local interaction difficult to regulate.1
• A visuotactile imitation policy generates the nominal stroking motion, while a separately trained residual module corrects local contact deviations, separating task progression from contact recovery.1
• We evaluate TacHair in 525 real-robot trials across five head geometries and three hair conditions.1

Sources (1)

• [1]TacHair: Tactile Contact-Distribution Guided Online Correction for Robotic Hair Stroking and Perception
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 02:20 PM

  We propose TacHair, a tactile contact-distribution guided online correction framework that represents high-resolution tactile observations as a spatial hair-contact distribution.

  Hair stroking is common in daily grooming and personal care, and is also widely used in hair-product evaluation, motivating robots with similar physical interaction capabilities.

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