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A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles

机译:基于GNSS / IMU / DMI / LiDAR传感器融合的自主车辆鲁棒车辆定位方法

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摘要

Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.
机译:对于自动驾驶汽车而言,在大型室外环境中进行精确而强大的定位至关重要。为了提高GNSS(全球导航卫星系统)/ IMU(惯性测量单元)/ DMI(距离测量仪器)融合的性能,尽管存在以下问题,仍提出了一种多约束故障检测方法来平滑车辆位置: GNSS跳了起来。此外,本文提出的基于点云的横向定位方法可以补偿横向定位误差。实验结果验证了本文提出的算法,表明本文提出的算法能够提供精确,鲁棒的车辆定位。

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