基于横向距离信息的城市移动机器人EKF定位

Christiand, Yu-Cheol Lee, Wonpil Yu
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引用次数: 4

摘要

针对城市环境下的移动机器人,提出了一种包含横向距离信息的EKF定位方法。假设移动机器人在存在车道标志的普通道路上运行。在EKF更新步骤之前,利用车道标记检测器给出的横向距离信息来补偿全球定位系统(GPS)的测量值。此外,该方法还采用马氏距离法对传感器测量结果进行验证。GPS补偿和马氏距离验证有效地减小了传感器误差,特别是GPS的漂移误差和跳位误差。因此,估计的位置精度优于普通EKF定位。
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EKF localization with lateral distance information for mobile robots in urban environments
This paper proposes the EKF localization with lateral distance information for the mobile robots in urban environments. The mobile robot is assumed to be operated at common roads where the lane marker exists. The lateral distance information given by the lane marker detector is used to compensate the measurement of global positioning system (GPS) before the EKF update step. In addition, the proposed method also uses Mahalanobis distance approach to validate the sensors measurements. The GPS compensation and Mahalanobis distance validation effectively reduce the sensors error, in particular drift error and jumping position of GPS. As a result, the accuracy of the estimated position is better than normal EKF localization.
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