The Geometry of Navigation Problems

被引:8
|
作者
Barrau, Axel [1 ]
Bonnabel, Silvere [2 ,3 ]
机构
[1] SAFRAN TECH, Grp Safran, Paris 78772, France
[2] PSL Res Univ, Ctr Robot, MINES ParisTech, Paris 75006, France
[3] Univ Nouvelle Caledonie, Inst Sci Exactes & Appl, Noumea 98851, France
关键词
Observers; Simultaneous localization and mapping; Kalman filters; Vehicle dynamics; Inertial navigation; Convergence; Manipulators; Aircraft navigation; autonomous vehicles; geometry; nonlinear filters; observers; state estimation; EXTENDED KALMAN FILTER; SYSTEMS; DESIGN;
D O I
10.1109/TAC.2022.3144328
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
While many works exploiting an existing Lie group structure have been proposed for state estimation, in particular the invariant extended Kalman filter (IEKF), few papers address the construction of a group structure that allows casting a given system into the framework of invariant filtering. In this article, we introduce a large class of systems encompassing most problems involving a navigating vehicle encountered in practice. For those systems we introduce a novel methodology that systematically provides a group structure for the state space, including vectors of the body frame such as biases. We use it to derive observers having properties akin to those of linear observers or filters. The proposed unifying and versatile framework encompasses all systems, where IEKF has proved successful, improves state-of-the art "imperfect" IEKF for inertial navigation with sensor biases, and allows addressing novel examples, like GNSS antenna lever arm estimation.
引用
收藏
页码:689 / 704
页数:16
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