Cited By
View all- Zhang LZhou XLi DYang Z(2024)HCCNet: Hybrid Coupled Cooperative Network for Robust Indoor LocalizationACM Transactions on Sensor Networks10.1145/366564520:4(1-22)Online publication date: 8-Jul-2024
RVIO: An Effective Localization Algorithm for Range-Aided Visual-Inertial Odometry System
Authors: 
Jun Wang, Pengfei Gu, Lei Wang, Ziyang MengAuthors Info & Claims
Jun Wang, Pengfei Gu, Lei Wang, Ziyang MengAuthors Info & ClaimsPages 1476 - 1490
Abstract
This paper presents an efficient and accurate range-aided visual-inertial odometry (RVIO) system for the global positioning system denied environment. In particular, the ultra-wideband (UWB) measurements are integrated to reduce the long-term drift of the visual-inertial odometry (VIO) system. Our approach starts with a filter-based scheme to localize the unknown UWB anchor in the local world frame. In particular, a novel surface-based particle filter is proposed to localize the UWB anchors efficiently. When the initialization is complete, the UWB location information is utilized to support the subsequent long-term robot positioning. An observability-constrained optimization approach is developed to combine the visual, inertial, and UWB range measurements. Such a framework takes advantage of both VIO and UWB measurements and is feasible even when the number of observed UWB anchors is below four. Experiments on both simulated and real-world scenes demonstrate the validity and superiority of the proposed system.
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Index Terms
- RVIO: An Effective Localization Algorithm for Range-Aided Visual-Inertial Odometry System
Index terms have been assigned to the content through auto-classification.
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Published: 02 October 2023
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View all- Zhang LZhou XLi DYang Z(2024)HCCNet: Hybrid Coupled Cooperative Network for Robust Indoor LocalizationACM Transactions on Sensor Networks10.1145/366564520:4(1-22)Online publication date: 8-Jul-2024
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