Full State Estimation of Continuum Robots From Tip Velocities: A Cosserat-Theoretic Boundary Observer

IF 7 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Automatic Control Pub Date : 2024-10-23 DOI:10.1109/TAC.2024.3485404
Tongjia Zheng;Qing Han;Hai Lin
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Abstract

State estimation of robotic systems is essential to implementing feedback controllers, which usually provide better robustness to modeling uncertainties than open-loop controllers. However, state estimation of soft robots is very challenging because soft robots have theoretically infinite degrees of freedom while existing sensors only provide a limited number of discrete measurements. This work focuses on soft robotic manipulators, also known as continuum robots. We design an observer algorithm based on the well-known Cosserat rod theory, which models continuum robots by nonlinear partial differential equations (PDEs) evolving in geometric Lie groups. The observer can estimate all infinite-dimensional continuum robot states, including poses, strains, and velocities, by only sensing the tip velocity of the continuum robot, and hence it is called a “boundary” observer. More importantly, the estimation error dynamics is formally proven to be locally input-to-state stable. The key idea is to inject sequential tip velocity measurements into the observer in a way that dissipates the energy of the estimation errors through the boundary. The distinct advantage of this PDE-based design is that it can be implemented using any existing numerical implementation for Cosserat rod models. All theoretical convergence guarantees will be preserved, regardless of the discretization method. We call this property “one design for any discretization.” Extensive numerical studies are included and suggest that the domain of attraction is large and the observer is robust to uncertainties of tip velocity measurements and model parameters.
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从尖端速度估算连续机器人的完整状态:科塞拉特理论边界观测器
机器人系统的状态估计是实现反馈控制器的关键,反馈控制器通常比开环控制器对建模不确定性具有更好的鲁棒性。然而,由于软机器人理论上具有无限的自由度,而现有的传感器只能提供有限数量的离散测量,因此软机器人的状态估计非常具有挑战性。这项工作的重点是软机器人操纵器,也被称为连续体机器人。基于著名的Cosserat棒理论设计了一种观测器算法,该算法通过几何李群中的非线性偏微分方程(PDEs)来建模连续体机器人。观察者可以通过感知连续体机器人的尖端速度来估计机器人的所有无限维连续体状态,包括姿态、应变和速度,因此被称为“边界”观察者。更重要的是,正式证明了估计误差动力学是局部输入到状态稳定的。关键思想是将连续的尖端速度测量值注入观测器,以一种通过边界消散估计误差能量的方式。这种基于pde的设计的明显优势在于,它可以使用任何现有的Cosserat杆模型的数值实现来实现。所有的理论收敛保证将被保留,不管离散方法。我们称这一特性为“任意离散化的一种设计”。广泛的数值研究表明,引力范围很大,观测器对叶尖速度测量和模型参数的不确定性具有鲁棒性。
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来源期刊
IEEE Transactions on Automatic Control
IEEE Transactions on Automatic Control 工程技术-工程:电子与电气
CiteScore
11.30
自引率
5.90%
发文量
824
审稿时长
9 months
期刊介绍: In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering. Two types of contributions are regularly considered: 1) Papers: Presentation of significant research, development, or application of control concepts. 2) Technical Notes and Correspondence: Brief technical notes, comments on published areas or established control topics, corrections to papers and notes published in the Transactions. In addition, special papers (tutorials, surveys, and perspectives on the theory and applications of control systems topics) are solicited.
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