Tactile In-Hand Object Rotation: A Comparative Study of Hand Morphology in Simulation and Hardware

Key points

• We investigate these relationships through rotational progress, finger participation, and fingertip loading on two versions of the low-cost LEAP Hand with anthropomorphic and symmetric finger arrangements.1
• Both hands are integrated with TacTip vision-based tactile sensors and use a shared reinforcement learning framework.1
• Simulation evaluates full tactile, binary touch, and proprioception-only observations on 12 unseen objects; hardware experiments evaluate full tactile policies on ten objects under multiple hand orientations.1
• In simulation, full tactile observations increase mean normalized rotation per episode over proprioception alone by 94.8% for the anthropomorphic hand and 66.9% for the symmetric hand, with longer mean episode durations and lower mean total fingertip loads.1

Sources (1)

• [1]Tactile In-Hand Object Rotation: A Comparative Study of Hand Morphology in Simulation and Hardware
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 05:18 PM

  Continuous in-hand rotation requires coordinated contact maintenance and renewal, linking manipulation performance to both hand geometry and tactile feedback.

  We investigate these relationships through rotational progress, finger participation, and fingertip loading on two versions of the low-cost LEAP Hand with anthropomorphic and symmetric finger arrangements.

Extractive summary: sentences quoted from the sources.