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首页> 外文会议>2011 IEEE International Conference on Systems, Man, and Cybernetics >Urban localization method for mobile robots based on dead reckoning sensors, GPS, and map matching
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Urban localization method for mobile robots based on dead reckoning sensors, GPS, and map matching

机译：基于航位推算传感器，GPS和地图匹配的移动机器人城市定位方法

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摘要

This paper presents a localization method in urban environments by using dead reckoning sensors, Global Positioning System (GPS), and taking into account the benefits of map matching. Extended Kalman Filter (EKF) is used as the main framework to fuse the information from sensors. However, the result of the EKF greatly depends on how the robot utilizes and judges the position measurement which comes from GPS since the GPS easily gives wrong position measurement due to the phenomenon called multipath effect. Under the assumption that the robot must operate only on the main road, a map matching is used to filter out the wrong GPS measurements which fall outside the main road. An experiment has been conducted in urban environment to validate the proposed method. Experimental results show that our proposed method has superior performance compared to the EKF without map matching
机译：本文通过使用航位推算传感器，全球定位系统（GPS），并考虑了地图匹配的优势，提出了一种城市环境中的定位方法。扩展卡尔曼滤波器（EKF）被用作融合传感器信息的主要框架。但是，EKF的结果很大程度上取决于机器人如何利用和判断来自GPS的位置测量值，因为由于称为多径效应的现象，GPS容易给出错误的位置测量值。在假设机器人只能在主干道上操作的情况下，使用地图匹配来过滤掉落在主干道之外的错误GPS测量值。已经在城市环境中进行了实验，以验证所提出的方法。实验结果表明，与没有地图匹配的EKF相比，我们提出的方法具有更好的性能。

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