TacSE3: 低テクスチャ視触覚画像からの等変SE(3)運動推定による把持内追跡と補償
TacSE3: Equivariant SE(3) Motion Estimation from Low-Texture Visuotactile Images for In-Gripper Tracking and Compensation
低テクスチャの視触覚画像からSE(3)上の剛体運動を推定するパイプラインを提案し、把持内の物体追跡と外乱補償に応用した。
詳しい要約
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著者: Zhongyuan Liao, Junzhe Wang, Qingyang Liu, Zhenmin Huang, Jun Ma, Yi Cai, Fei Meng, Haobo Liang, Michael Yu Wang
分類: cs.RO
原文アブストラクト
Robotic in-hand manipulation requires reliable object-motion tracking under frequent visual occlusion, yet low-texture visuotactile images provide few stable correspondences for conventional image- or geometry-matching methods. This paper presents TacSE3, a tactile motion-estimation pipeline that converts low-texture visuotactile observations into a decoupled three-dimensional force field and estimates incremental rigid-body motion on SE(3). The method derives planar translation from contact-centroid motion and estimates rotation primarily from shear-related tactile responses, yielding a physically interpretable signal for in-gripper tracking and compensation. Experiments with paired DM-Tac fingertip sensors show that dual-sensor sensing reduces translation-rotation ambiguity, supports rotation tracking across axes and object geometries, and provides a lightweight compensation signal that improves disturbance tolerance in downstream manipulation tasks without retraining the base policy.
