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

被引:8
作者
Yang, Bohan [1 ]
Lu, Bo [1 ,2 ]
Chen, Wei [1 ]
Zhong, Fangxun [1 ]
Liu, Yun-Hui [1 ]
机构
[1] Chinese Univ Hong Kong, T Stone Robot Inst, Dept Mech & Automation Engn, Hong Kong, Peoples R China
[2] Soochow Univ, Robot & Microsyst Ctr, Sch Mech & Elect Engn, Suzhou 215021, Peoples R China
关键词
Deformation; Jacobian matrices; Robots; Deformable models; Shape; Modal analysis; Computational modeling; Adaptive control; deformable object manipulation; modal analysis; visual servoing; MANIPULATION; INTEGRATION; RECOVERY; TISSUE;
D O I
10.1109/TRO.2023.3269347
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Shape control of deformable objects is a challenging and important robotic problem. This article proposes a model-free controller using novel 3-D global deformation features based on modal analysis. Unlike most existing controllers using geometric features, our controller employs physically based deformation features designed by decoupling global deformation into low-frequency modes. Although modal analysis is widely adopted in computer vision and simulation, its usage in robotic deformation control is still an open topic. We develop a new model-free framework for the modal-based deformation control. Physical interpretation of the modes enables us to formulate an analytical deformation Jacobian matrix mapping the robot manipulation onto changes of the modal features. In the Jacobian matrix, unknown geometric and physical models 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 volumetric objects under different settings. The results not only confirm the superior performance of our controller, but also demonstrate its advantages over the baseline method.
引用
收藏
页码:3134 / 3153
页数:20
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