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- W2068396425 abstract "This paper proposes a 3D point cloud registration method based on light detection and ranging (LiDAR) system. The proposed method consists of three steps: Gaussian-Process based ground segmentation, a novel k-neighbors based dynamic point feature and Iterative Closest Point (ICP) fine registration. The first two steps are the preparation of ICP fine registration. The odometry information from a GPS/IMU system is used to compensate the vehicle's ego-motion. The Gaussian-Process based ground segmentation is adopted to remove ground points. A novel Initial Localization based Dynamic Feature (ILDF) is proposed to detect and remove dynamic points. It is applicable in sequential frames and a proper initial localization without a large dislocation. In experiment results, a large number of dynamic points will be detected and removed by ILDF. The removal of dynamic points improves both accuracy and efficiency of registration algorithm." @default.
- W2068396425 created "2016-06-24" @default.
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- W2068396425 date "2014-10-01" @default.
- W2068396425 modified "2023-09-26" @default.
- W2068396425 title "A 3D Sequential LiDAR Data Registration Method for Unmanned Ground Vehicle" @default.
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- W2068396425 doi "https://doi.org/10.4028/www.scientific.net/amm.664.365" @default.
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