论文标题
基于模态分析的新型特征对可变形物体的无模型3D形状控制
Model-Free 3D Shape Control of Deformable Objects Using Novel Features Based on Modal Analysis
论文作者
论文摘要
可变形物体的形状控制是一个具有挑战性且重要的机器人问题。本文提出了一个基于模态分析的新型3D全局变形特征的无模型控制器。与大多数使用几何功能的现有控制器不同，我们的控制器通过将3D全局变形分解为低频模式形状，采用基于物理的变形功能。尽管模态分析在计算机视觉和仿真中被广泛采用，但尚未用于机器人变形控制中。我们为机器人操纵下的基于模态的变形控制开发了一个新的无模型框架。模式形状的物理解释使我们能够制定一个分析变形的雅各布矩阵将机器人操纵映射到模态特征的变化上。在Jacobian矩阵中，对象的未知几何形状和物理特性被视为低维模态参数，可用于线性地参数化闭环系统。因此，可以设计具有证实稳定性的自适应控制器，以使对象变形，同时在线估计模态参数。在不同设置下使用线性，平面和实体对象进行仿真和实验。结果不仅证实了我们的控制器的出色性能，而且还证明了其优势在基线方法上。
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.
