יום שלישי, 15 בספטמבר 2026 LIVE
AI־INFO

כתבה arXiv cs.AI ·

TAM: Torque Adaptation Module for Robust Motion Transfer in Manipulation

תקציר מקורי באנגליתarXiv:2606.06218v2 Announce Type: replace-cross Abstract: A policy tuned for one robot often behaves differently on another, whether due to the sim-to-real gap, unknown payloads, or the differing dynamics of two instances of the same robot. In contact-rich, dynamic manipulation, even small motion discrepancies can result in failure to track reference motion, since they disrupt the timing and modes of contact. Common remedies, such as domain randomization or system identification, either produce overly conservative task policies or require data that must be recollected for each robot or payload. We introduce the Torque Adaptation Module (TAM), a learned module that adapts the torque commands sent to the robot to match the behavior of an ideal robot. TAM operates between the low-level contro
קרא במקור המקורי