膜によるマニピュレーション：高解像度で高変形可能な触覚センシングと制御
Manipulation via Membranes: High-Resolution and Highly Deformable Tactile Sensing and Control
柔らかい触覚センサ膜の変形ダイナミクスを学習し、把持物体の姿勢を推定することで、マーカー描画や把持内回転などの接触の多いタスクを高精度に実現する手法を提案した。
著者: Miquel Oller, Mireia Planas, Dmitry Berenson, Nima Fazeli
分類: cs.RO
原文アブストラクト
Collocated tactile sensing is a fundamental enabling technology for dexterous manipulation. However, deformable sensors introduce complex dynamics between the robot, grasped object, and environment that must be considered for fine manipulation. Here, we propose a method to learn soft tactile sensor membrane dynamics that accounts for sensor deformations caused by the physical interaction between the grasped object and environment. Our method combines the perceived 3D geometry of the membrane with proprioceptive reaction wrenches to predict future deformations conditioned on robot action. Grasped object poses are recovered from membrane geometry and reaction wrenches, decoupling interaction dynamics from the tactile observation model. We benchmark our approach on two real-world contact-rich tasks: drawing with a grasped marker and in-hand pivoting. Our results suggest that explicitly modeling membrane dynamics achieves better task performance and generalization to unseen objects than baselines.
