SE(3)-Constrained Extended Kalman Filtering for Rigid Body Pose Estimation
SE(3)-Constrained Extended Kalman Filtering for Rigid Body Pose Estimation
复制标题
用于刚体姿态估计的 SE(3) 约束扩展卡尔曼滤波
DOI：
10.1109/taes.2021.3139291
复制
发表时间：
2022
影响因子：
4.4
通讯作者：
E. Butcher
中科院分区：
文献类型：
--
作者：
S. Mathavaraj;E. Butcher
在本文中，在连续时间以及更实用的连续离散框架中提出了 <inline-formula><tex-math notation="LaTeX">$SE(3)$</tex-math></inline-formula> 约束的扩展卡尔曼滤波器。该滤波器允许对 6-DOF 刚体运动进行状态估计，同时考虑测量误差统计并使用旋转矩阵而不是四元数或其他姿态参数化。所提出的过滤器与最近提出的 <inline-formula><tex-math notation="LaTeX">$SO(3)$</tex-math></inline-formula> 约束态度过滤器不同，因为当前过滤器中仅约束配置状态的子集。它的有效性在数值示例中得到了证明，其中将其性能与文献中现有的 <inline-formula><tex-math notation="LaTeX">$SE(3)$</tex-math></inline-formula> 估计器的性能进行了比较，并进行了蒙特卡洛模拟，以确保所提出的滤波器的准确性。
In this article, an <inline-formula><tex-math notation="LaTeX">$SE(3)$</tex-math></inline-formula>-constrained extended Kalman filter is proposed in continuous time as well as in a more practical continuous-discrete framework. The filter allows for the state estimation of the 6-DOF rigid body motion while accounting for measurement error statistics and using the rotation matrix instead of quaternions or other attitude parameterizations. The proposed filter differs from the recently proposed <inline-formula><tex-math notation="LaTeX">$SO(3)$</tex-math></inline-formula>-constrained attitude filter in that only a subset of the configuration states are constrained in the present filter. Its effectiveness is demonstrated in a numerical example in which its performance is compared with that of an existing <inline-formula><tex-math notation="LaTeX">$SE(3)$</tex-math></inline-formula> estimator from the literature and a Monte Carlo simulation is carried out to provide credence to the accuracy of the proposed filter.