arXiv (OAI Expanded)
open access
PredTac: Learning Contact-Rich Manipulation with Predicted Touch
Contact-rich manipulation benefits from tactile feedback, yet physical tactile sensors introduce hardware, calibration, synchronization, and maintenance costs that complicate policy learning and deployment. We formulate predicted touch as an alternative to measured tactile input and present PredTac,
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