西格玛点滤波器:综合导航和视觉辅助控制的应用概述

E. Wan
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引用次数: 37

摘要

在本次演讲中,我们首先概述了Sigma-Point滤波方法,包括Unscented卡尔曼滤波(UKF),中心差分卡尔曼滤波(CDKF),以及对顺序蒙特卡罗滤波(例如粒子滤波)进行混合扩展的几种变体。在第二部分中,我们将重点介绍组合导航系统(INS)的最新应用,该系统通过结合GPS和惯性测量来提供状态估计。此外,我们提出了使用视频数据提取等效状态信息(即取代INS)用于无人机(UAV)闭环控制的新工作。
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Sigma-Point Filters: An Overview with Applications to Integrated Navigation and Vision Assisted Control
In this presentation, we first provide an overview of Sigma-Point filtering methods, which include the Unscented Kalman Filter (UKF), Central Difference Kalman Filter (CDKF), and several variants with hybrid extensions to sequential Monte Carlo filtering (e.g., particle filtering). In the second half, we focus on recent applications to integrated navigation systems (INS), which provide state-estimation by combining GPS and inertial measurements. In addition, we present new work on using video data to extract the equivalent state-information (i.e., replacing the INS) for use in closed-loop control of an Unmanned Aerial Vehicle (UAV).
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