単眼RGB-Dと内力推定による弾塑性材料操作のための力-変形推定
Single-View RGB-D Force--Deformation Estimation for Robotic Manipulation of Elasto-Plastic Materials
単眼ハンドアイRGB-Dカメラとロボットの内力推定を用いて、弾塑性材料の押し込み時の力と変形量の関係を計測し、MLPで力-体積関係をモデル化した研究。
著者: Dezhi Sun, Marijn van Hilten, Kenan Niu
分類: cs.RO
原文アブストラクト
Persistent deformation complicates elasto-plastic manipulation by coupling physical interaction with spatially distributed shape changes. We investigate the force--deformation relationship using a standard robot, a single eye-in-hand RGB-D camera, and intrinsic force estimates. A 7-DoF Franka Emika FR3 performs normal indentations while an Intel RealSense L515 captures pre- and post-contact surfaces. Point-cloud processing localizes deformation and estimates displaced volume. Force--volume characterization includes 27 measurements over nine force levels. A compact multilayer perceptron (MLP), trained on 52 force--volume pairs at four levels, achieves a held-out RMSE of 1.857 N and $R^2=0.440$. A separate comparison shows lower error for a quadratic model at 16 N and for the MLP at 19 and 23.5 N. An eight-step experiment at 4 N per interaction demonstrates cumulative deformation localization from the second indentation onward. These results establish a practical measurement basis for deformation-aware manipulation using intrinsic force estimates and single-view geometry.