初始化
精度稀释
里程计
计算机科学
职位(财务)
计算机视觉
弹道
航程(航空)
人工智能
惯性导航系统
视觉里程计
航向(导航)
惯性测量装置
惯性参考系
全球定位系统
工程类
移动机器人
机器人
电信
物理
量子力学
航空航天工程
经济
程序设计语言
全球导航卫星系统应用
财务
天文
作者
Giulio Delama,Farhad Shamsfakhr,Stephan Weiß,Daniele Fontanelli,Alessandro Fomasier
标识
DOI:10.1109/iros55552.2023.10342012
摘要
This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide robust and low-drift localization. In order to include range measurements in state estimation, the position of the UWB anchors must be known. This study proposes a multi-step initialization procedure to map multiple unknown anchors by an Unmanned Aerial Vehicle (UAV), in a fully autonomous fashion. To address the limitations of initializing UWB anchors via a random trajectory, this paper uses the Geometric Dilution of Precision (GDOP) as a measure of optimality in anchor position estimation, to compute a set of optimal waypoints and synthesize a trajectory that minimizes the mapping uncertainty. After the initialization is complete, the range measurements from multiple anchors, including measurement biases, are tightly integrated into the VIO system. While in range of the initialized anchors, the VIO drift in position and heading is eliminated. The effectiveness of UVIO and our initialization procedure has been validated through a series of simulations and real-world experiments.
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