论文标题
模棱两可的过滤器是模棱两可的
Equivariant Filters are Equivariant
论文作者
论文摘要
具有谎言组对称系统的系统的观察者是一个积极的研究领域,在许多实用领域,包括航空航天,机器人技术和机电一体化方面都有重大影响。本文建立在最近提出的epoiriant滤波器(EQF)的理论基础上,该理论是均质空间上系统的一般观察者设计,利用对称性获得了显着的性能优势。结果表明,EQF误差动力学对于输入信号的转换和作为参数矢量字段的变换是不变的。主要定理表明,两个EQF具有不同选择的局部坐标和起源,以及等效噪声建模的产生相同的性能。换句话说,EQF是系统方程和对称性的固有的。在模拟2D机器人本地化问题的模拟中对此进行了验证,该问题还显示了选择EQF来源的能力如何通过减轻浮点精度错误来产生实际的性能优势。
Observers for systems with Lie group symmetries are an active area of research that is seeing significant impact in a number of practical domains, including aerospace, robotics, and mechatronics. This paper builds on the theory of the recently proposed Equivariant Filter (EqF), which is a general observer design for systems on homogeneous spaces that takes advantage of symmetries to yield significant performance advantages. It is shown that the EqF error dynamics are invariant to transformation of the input signal and equivariant as a parametrised vector field. The main theorem shows that two EqF's with different choices of local coordinates and origins and with equivalent noise modelling yield identical performance. In other words, the EqF is intrinsic to the system equations and symmetry. This is verified in a simulation of a 2D robot localisation problem, which also shows how the ability to choose an origin for the EqF can yield practical performance advantages by mitigating floating point precision errors.