モーダル解析に基づく新特徴量を用いた柔軟物体のモデルフリー3D形状制御
Model-Free 3D Shape Control of Deformable Objects Using Novel Features Based on Modal Analysis
柔軟物体の3D変形を低周波モード形状に分解する新特徴量を導入し、物体の未知の幾何・物理特性をオンライン推定しながら形状を制御するモデルフリー適応制御器を提案した論文。
著者: Bohan Yang, Bo Lu, Wei Chen, Fangxun Zhong, Yun-Hui Liu
分類: cs.RO
原文アブストラクト
Shape control of deformable objects is a challenging and important robotic problem. This paper proposes a model-free controller using novel 3D global deformation features based on modal analysis. Unlike most existing controllers using geometric features, our controller employs a physically-based deformation feature by decoupling 3D global deformation into low-frequency mode shapes. Although modal analysis is widely adopted in computer vision and simulation, it has not been used in robotic deformation control. We develop a new model-free framework for modal-based deformation control under robot manipulation. Physical interpretation of mode shapes enables us to formulate an analytical deformation Jacobian matrix mapping the robot manipulation onto changes of the modal features. In the Jacobian matrix, unknown geometry and physical properties of the object are treated as low-dimensional modal parameters which can be used to linearly parameterize the closed-loop system. Thus, an adaptive controller with proven stability can be designed to deform the object while online estimating the modal parameters. Simulations and experiments are conducted using linear, planar, and solid objects under different settings. The results not only confirm the superior performance of our controller but also demonstrate its advantages over the baseline method.
