Location technology of indoor robot based on laser sensor

Yu Zhao, Fenglian Liu, Riwei Wang
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引用次数: 5

Abstract

In order to solve existed accumulative error and SLAM problem for dead reckoning, this paper was proposed a positioning method combining with the known structured environment based on Extended Kalman Filter algorithm (EKF). This method quickly extracts the information of border and corner. According to the feature mapping relationships between world coordinate system and local coordinate system, calculate the robot's position and orientation space in the scene by matching the modeled environmental information. This method that we proposed achieved a better accuracy, timeliness and correctness.
基于激光传感器的室内机器人定位技术
针对航位推算中存在的累积误差和SLAM问题,提出了一种结合已知结构环境的扩展卡尔曼滤波(EKF)定位方法。该方法可以快速提取图像的边角信息。根据世界坐标系与局部坐标系之间的特征映射关系,通过匹配建模的环境信息,计算机器人在场景中的位置和方向空间。该方法具有较好的准确性、及时性和正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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