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Fusion of visual odometry and inertial navigation system on a smartphone

机译:视觉里程表和惯性导航系统在智能手机上的融合

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The paper presents the monocular visual odometry, inertial navigation system and the fusion of both these localization approaches. The visual odometry algorithm consists of four other algorithms, namely the camera calibration algorithm, KLT algorithm, algorithm for the estimation of rigid transformation and RANSAC algorithm. The inertial navigation system is based on a pedometer and digital compass. Both visual odometry and the inertial navigation system can determine the incremental movements and the positions of a robot or a pedestrian according to the world coordinate system. In order to get an even more robust and accurate localization system, the advantages of each mentioned localization approaches were combined by using the Extended Kalman Filter. The algorithms were fully implemented on a smartphone, where they were divided into several threads that could be performed simultaneously on multiple processor cores. The proposed system, which fuses information from the camera and inertial sensors, can convert the smartphone into a powerful mobile sensor unit or the so-called virtual sensor that returns relative position in relation to the starting point. This virtual sensor can be used as an advanced sensor unit on mobile robots or as part of a smartphone application which requires personal navigation system. The operation of the localization system is proved by experimental results which were obtained by attaching a smartphone on a pedestrian who walked along the reference trajectory drawn on the floor. In the experiments the described system showed big potential in many aspects since very good results were obtained. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文介绍了单眼视觉里程表,惯性导航系统以及这两种定位方法的融合。视觉里程计算法由其他四个算法组成,分别是相机校准算法,KLT算法,用于估计刚性变换的算法和RANSAC算法。惯性导航系统基于计步器和数字罗盘。视觉里程表和惯性导航系统都可以根据世界坐标系确定机器人或行人的增量运动和位置。为了获得更加鲁棒和准确的定位系统,通过使用扩展卡尔曼滤波器将每种提到的定位方法的优点结合在一起。该算法在智能手机上完全实现,在智能手机中,算法被划分为多个线程,可以在多个处理器内核上同时执行。所提出的系统融合了来自摄像头和惯性传感器的信息,可以将智能手机转换为功能强大的移动传感器单元或所谓的虚拟传感器,该传感器返回相对于起点的相对位置。该虚拟传感器可以用作移动机器人上的高级传感器单元,也可以用作需要个人导航系统的智能手机应用程序的一部分。通过将智能手机安装在沿着地板上绘制的参考轨迹行走的行人上的实验结果证明了定位系统的运行。在实验中,由于获得了很好的结果,所描述的系统在许多方面都显示出巨大的潜力。 (C)2015 Elsevier B.V.保留所有权利。

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