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首页> 外文期刊>International Journal of Advanced Robotic Systems >Application of Matrix Pencil Algorithm to Mobile Robot Localization Using Hybrid DOA/TOA Estimation
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Application of Matrix Pencil Algorithm to Mobile Robot Localization Using Hybrid DOA/TOA Estimation

机译:矩阵铅笔算法在使用混合DOA / TOA估计中的移动机器人定位

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Localization plays an important role in robotics for the tasks of monitoring, tracking and controlling a robot. Much effort has been made to address robot localization problems in recent years. However, despite many proposed solutions and thorough consideration, in terms of developing a low-cost and fast processing method for multiple-source signals, the robot localization problem is still a challenge. In this paper, we propose a solution for robot localization with regards to these concerns. In order to locate the position of a robot, both the coordinate and the orientation of a robot are necessary. We develop a localization method using the Matrix Pencil (MP) algorithm for hybrid detection of direction of arrival (DOA) and time of arrival (TOA). TOA of the signal is estimated for computing the distance between the mobile robot and a base station (BS). Based on the distance and the estimated DOA, we can estimate the mobile robot's position. The characteristics of the algorithm are examined through analysing simulated experiments and the results demonstrate the advantages of our method over previous works in dealing with the above challenges. The method is constructed based on the low-cost infrastructure of radio frequency devices; the DOA/TOA estimation is performed with just single value decomposition for fast processing. Finally, the MP algorithm combined with tracking using a Kalman filter allows our proposed method to locate the positions of multiple source signals.
机译:本地化在机器人中发挥着重要作用,了解监控,跟踪和控制机器人的任务。近年来,已经努力解决机器人本地化问题。然而,尽管许多提出的解决方案和全面考虑,但在开发用于多源信号的低成本和快速加工方法方面,机器人本地化问题仍然是一个挑战。在本文中,我们提出了关于这些问题的机器人本地化的解决方案。为了定位机器人的位置,需要坐标和机器人的方向。我们使用矩阵铅笔(MP)算法开发一个定位方法,用于混合检测到达方向(DOA)和到达时间(TOA)。估计信号的TOA用于计算移动机器人和基站(BS)之间的距离。基于距离和估计的DOA,我们可以估计移动机器人的位置。通过分析模拟实验检查算法的特征,结果证明了我们对以前的作品的方法,以处理上述挑战。该方法基于射频器件的低成本基础设施构建;只需单值分解执行DOA / TOA估计以进行快速处理。最后,使用卡尔曼滤波器的跟踪组合MP算法允许我们所提出的方法定位多个源信号的位置。

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