日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
マニピュレーションarXiv:2609.36676

接触の多い巧みな操作デモンストレーションのための運動学的非線形時空間軌道ワーピング

Kinematic Nonlinear Spatio-Temporal Trajectory Warping for Contact-Rich Dexterous Manipulation Demonstrations

シェア:XThreadsFacebookLINEはてブBluesky

手と物体の軌道を入力とし、接触分布を利用して中間ウェイポイントや障害物、時間的ずれ、開始・終了姿勢の変化に対応した高品質な非線形軌道ワープを生成する手法を提案。

著者: Hyojae Park, Arjun S. Lakshmipathy, Nancy S. Pollard

分類: cs.RO

原文アブストラクト

We present a straightforward but effective method for repurposing existing contact-rich dexterous manipulation demonstrations. Starting from inputs of hand and object trajectories, our method outputs high-quality nonlinear trajectory warps that account for intermediate waypoints, environmental barriers, temporal shifts, and varied start/end configurations. Foundational to our method is the utilization of contact distributions, which we show allows us to reliably compute complex and high-dimensional dexterous hand trajectories following a simple object-centric warp specification pipeline. We evaluate our method across 12 variations sourced from 4 demonstrations in a publicly available dataset of human hand motion data, perform baseline comparisons, and demonstrate generalization of our approach to different manipulators. Results and code will be made available on publication.

関連論文

PR本紙発行元 EmplifAI