提出离散几何建模与状态估计方法，提升连续体机器人的精度和效率。
Discrete Geometric Modeling and Extended State Estimation of Continuum Robots
- 基于最小应变形式的几何精确梁模型，结合李群变分积分框架。
- 实验验证模型与观测器在真实系统中实现高精度状态估计。
- 适合需要高精度控制的柔性机器人研究者参考。
本文提出一种完全离散的方法，用于连续体机器人的精确且数值高效的动力学建模与状态估计。该模型基于几何精确梁的最小应变形式，在李群变分积分框架下推导，能够保持重要的几何特性，从而实现高精度与数值高效性。随后，我们提出一种基于扩展卡尔曼滤波的扰动观测器，可可靠估计系统状态、模型不确定性及外部干扰。在真实系统上的实验验证了所提模型与观测器的准确性与效率。
原文摘要 · Abstract (English)
In this paper, we present a fully discrete approach for the accurate and numerically efficient dynamical modeling and state estimation of continuum robots. The model is based on geometrically exact beams in a minimal, strain-based formulation and derived in the framework of Lie group variational integrators, allowing to preserve important geometric properties that we exploit to achieve high accuracy and numerical efficiency. We then propose a disturbance observer based on an extended Kalman filter formulation that reliably estimates system states as well as model uncertainties and external disturbances. Experiments on a real system validate the accuracy and efficiency of the proposed model and observer.
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