TacSpin: Tactile Tracking of In-Gripper Object Rotation on SO(3) via Axis-Magnitude Estimation

Key points

• Tracking object motion within a gripper provides essential feedback for robotic manipulation.1
• However, limited contact coverage and uneven deformation make tactile estimation challenging.1
• Each finger's response is further refined with contact-boundary cues.1
• Qualitative demonstrations on real-world objects, using calibration transferred from a standard sphere, illustrate tracking under different contact geometries.1

Sources (1)

• [1]TacSpin: Tactile Tracking of In-Gripper Object Rotation on SO(3) via Axis-Magnitude Estimation
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 13, 01:54 AM

  In this study, we present TacSpin, a method that tracks in-gripper object rotation on SO(3) using only two vision-based tactile sensors.

  Tracking object motion within a gripper provides essential feedback for robotic manipulation.

Extractive summary: sentences quoted from the sources.