计算机科学
里程计
计算机视觉
人工智能
全球导航卫星系统应用
视觉里程计
全球定位系统
移动机器人
机器人
电信
作者
Huei‐Yung Lin,Jia-Rong Zhan
出处
期刊:Measurement
[Elsevier]
日期:2023-01-01
卷期号:206: 112256-112256
被引量:21
标识
DOI:10.1016/j.measurement.2022.112256
摘要
The localization of unmanned aerial vehicles (UAVs) in GPS-denied areas is an essential issue for indoor navigation. This paper presents a technique to improve the accuracy of visual inertial odometry (VIO) by combining the ultra-wideband (UWB) positioning technology. The proposed architecture is divided into two stages. In the initial stage, the constraint on UWB short-term position change is adopted to improve the pose estimation results of the VIO system. It is also used to mitigate the translation error caused by the vibration and lack of features during the flight. In the second stage, a loose coupling approach based on nonlinear optimization is utilized to fuse the local pose estimator of the VIO system with the global constraints from the UWB positioning. At the beginning of each operation, the alignment between the VIO and UWB frames is estimated to avoid the influence of coordinate transformation due to the VIO cumulative error. It is shown that our optimization-based fusion method is able to achieve a smooth localization trajectory under the global coordinate frame. In the experiments, the performance evaluation carried out in the real-world scenes has demonstrated the effectiveness of the proposed technique.
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