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RVIO: An Effective Localization Algorithm for Range-Aided Visual-Inertial Odometry System
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DOI：10.1109/TITS.2023.3317408.png)
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摘要
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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.
Keyword:
Location awareness
Cameras
Optimization
Robot sensing systems
Odometry
Observability
Robot kinematics
Visual-inertial odometry
multi-sensor fusion
UWB
observability
particle filter
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8.4
论文数:
9.7K
被引数:
6.3W
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