MDIR: 接触を伴う遠隔操作のためのタスク多様体インピーダンス再ターゲティング手法
MDIR: A Task-Manifold Impedance Retargeting Method for Contact-Rich Teleoperation
固定の直交インピーダンス制御による遠隔操作デモを、実行可能な可変インピーダンス指令へ再パラメータ化する手法を提案。デモ軌道近傍でのタスクチャネル応答を維持しつつ、手首力のピークやインパルスなどを低減する。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Liu Jiahao, Kento Kawaharazuka, Tasuku Makabe, Kei Okada
分類: cs.RO
原文アブストラクト
Fixed Cartesian impedance makes contact-rich teleoperation demonstrations practical, but gains that secure progress and contact support also determine impact and force variability. We study single-demonstration controller-to-controller impedance retargeting. Given one fixed Cartesian impedance command sequence {K0, D0, xcmd}, Manifold-Decomposed Impedance Retargeting (MDIR) deterministically reparameterizes the recorded controller into an executable task-channel variable-impedance command. MDIR targets this local retargeting problem by preserving projected task-channel responses near the demonstrated trajectory. It represents the source response in operational work, exertion, and support channels with a passive residual complement under a control-chain metric, computes an executable Cartesian-to-Manifold Retargeting (C2M) baseline, and applies Manifold-Constrained Parameter Optimization (MPO) to select a feasible representative with lower wrist-force peaks, impulse, force variability, and nominal controller power. Across planar wiping, pick-and-place, and pushing on a Franka Panda, the full MDIR controller passes Task Check in all 15 closed-loop executions and reduces all four aggressiveness metrics relative to the fixed-impedance demonstrations.
