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arXiv 2207.01249cs.RO
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基于模态分析新特征的无模型可变形物体三维形状控制

Model-Free 3D Shape Control of Deformable Objects Using Novel Features Based on Modal Analysis

The Chinese University of Hong Kong(香港中文大学);T Stone Robotics Institute(T Stone机器人研究所);Soochow University(苏州大学)

Bohan Yang, Bo Lu, Wei Chen, Fangxun Zhong, Yun-Hui Liu

AI总结:

本文提出一种基于模态分析的无模型三维形状控制方法,通过低频模态特征构建解析雅可比矩阵并设计自适应控制器,在仿真和实验中验证了其优于基线方法的变形控制性能。

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。本文提出了一种无模型控制器,使用基于模态分析的新型三维全局变形特征。与大多数现有使用几何特征的控制器不同,我们的控制器通过将三维全局变形解耦为低频模态振型,采用了基于物理的变形特征。尽管模态分析在计算机视觉和仿真中被广泛采用,但它尚未被用于机器人变形控制。我们开发了一种新的无模型框架,用于机器人操作下基于模态的变形控制。模态振型的物理解释使我们能够构建一个解析的变形雅可比矩阵,将机器人操作映射到模态特征的变化上。在该雅可比矩阵中,物体的未知几何和物理属性被视为低维模态参数,可用于对闭环系统进行线性参数化。因此,可以设计一种具有已证明稳定性的自适应控制器,在在线估计模态参数的同时使物体变形。使用线性、平面和实体物体在不同设置下进行了仿真和实验。结果不仅证实了我们控制器的优越性能,还展示了其相对于基线方法的优势。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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