首页> 外文会议>8th Biennial Conference on Engineering Systems Design and Analysis 2006 vol.1 >LOCALIZATION OF A MOBILE ROBOT WITH OMNIDIRECTIONAL WHEELS USING ANGULAR KALMAN FILTERING AND TRIANGULATION
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LOCALIZATION OF A MOBILE ROBOT WITH OMNIDIRECTIONAL WHEELS USING ANGULAR KALMAN FILTERING AND TRIANGULATION

机译:用角卡尔曼滤波和三角剖分定位具有单向轮的移动机器人

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摘要

Localization is one of the fundamental problems in mobile robot navigation. Several approaches to cope with the dynamic positioning problem have been made. Most of them use an extended Kalman filter (EKF) to estimate the robot pose -position and orientation- fusing both the robot odometry and external measurements.rnIn this paper, an EKF is used to estimate the angles, relative to the robot frame, of the straight lines from a rotating laser scanner to a set of landmarks. By using this method angles are predicted, between actual laser measurements, by means of the time integration of its time derivative, which depends upon the robot kinematics. Once these angles are estimated, triangulation can be consistently applied at any time to determine the robot pose. In this work, a mobile robot with three omnidirectional wheels -that consist of two spherical rollers- is considered. Computer simulations showing the accuracy of this method are presented.
机译:本地化是移动机器人导航的基本问题之一。已经提出了几种解决动态定位问题的方法。他们中的大多数人都使用扩展的卡尔曼滤波器(EKF)来结合机器人的里程表和外部测量来估计机器人的姿势和位置。在本文中,EKF用于估计机器人相对于机器人框架的角度。从旋转的激光扫描仪到一组地标的直线。通过使用这种方法,可以根据实际的激光测量结果通过其时间导数的时间积分来预测角度,这取决于机器人的运动学。一旦估计了这些角度,就可以在任何时候一致地应用三角剖分以确定机器人的姿势。在这项工作中,考虑了具有三个由两个球形滚轮组成的全向轮的移动机器人。计算机仿真表明了该方法的准确性。

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