扩展卡尔曼滤波器
控制理论(社会学)
不变扩展卡尔曼滤波器
不变(物理)
卡尔曼滤波器
机器人学
惯性参考系
数学
杠杆(统计)
观察员(物理)
计算机科学
人工智能
机器人
物理
量子力学
控制(管理)
数学物理
作者
Axel Barrau,Silvère Bonnabel
摘要
We analyze the convergence aspects of the invariant extended Kalman filter (IEKF), when the latter is used as a deterministic non-linear observer on Lie groups, for continuous-time systems with discrete observations. One of the main features of invariant observers for left-invariant systems on Lie groups is that the estimation error is autonomous. In this paper we first generalize this result by characterizing the (much broader) class of systems for which this property holds. Then, we leverage the result to prove for those systems the local stability of the IEKF around any trajectory, under the standard conditions of the linear case. One mobile robotics example and one inertial navigation example illustrate the interest of the approach. Simulations evidence the fact that the EKF is capable of diverging in some challenging situations, where the IEKF with identical tuning keeps converging.
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