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• W4285611982 abstract "Accurate localization is crucial for safe operation of intelligent vehicle (IV). In practice, global positioning system (GPS) signals sometimes may be contaminated or lost, resulting in inaccurate positions of IV. In this article, the distance of IV’s position between previous frame and current frame is derived from Lidar point cloud registration. A novel slide window variational Bayesian (VB) based localization method is proposed for IV with multiple dynamics by fusing GPS and Lidar. In the proposed method, the state of IV, the motion model identity of IV, the measurement loss identity, and the loss probability of measurement are jointly estimated by the VB technique. The effectiveness of the proposed localization method is validated by simulations and field experiments." @default.
• W4285611982 created "2022-07-16" @default.
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• W4285611982 date "2022-12-01" @default.
• W4285611982 modified "2023-10-16" @default.
• W4285611982 title "Variational Bayesian Based Localization for Intelligent Vehicle Using Lidar and GPS Data Fusion: Algorithm and Experiments" @default.
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• W4285611982 doi "https://doi.org/10.1109/tmech.2022.3187975" @default.
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