Indoor navigation with smartphone-based visual SLAM and Bluetooth-connected wheel-robot

W. Kao, Bui Quang Huy
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引用次数: 23

Abstract

A smartphone-based positioning system suitable for indoor robot application is developed in this research by integrating image and other sensors on a smartphone with wheel odometer feedback from a Bluetooth-connected robot vehicle. WiFi signal, inertial sensors, and CMOS sensor in the smartphone were considered to provide measurements for positioning calculations. The real-time performances of SIFT, SURF, and ORB image feature detection and tracking algorithms are compared in the smartphone and ORB was chosen for implementation. Experimental result of Visual SLAM positioning is presented together with state convergence analysis.
室内导航,基于智能手机的视觉SLAM和蓝牙连接的轮式机器人
本研究通过将智能手机上的图像和其他传感器与蓝牙连接的机器人车辆的车轮里程计反馈相结合,开发了一种适合室内机器人应用的基于智能手机的定位系统。考虑了智能手机中的WiFi信号、惯性传感器和CMOS传感器为定位计算提供测量。比较了SIFT、SURF和ORB三种图像特征检测与跟踪算法在智能手机上的实时性,选择ORB算法进行实现。给出了视觉SLAM定位的实验结果,并进行了状态收敛分析。
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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