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Seamless Positioning and Navigation by Using Geo-Referenced Images and Multi-Sensor Data

机译:使用地理参考图像和多传感器数据进行无缝定位和导航

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Ubiquitous positioning is considered to be a highly demanding application for today's Location-Based Services (LBS). While satellite-based navigation has achieved great advances in the past few decades, positioning and navigation in indoor scenarios and deep urban areas has remained a challenging topic of substantial research interest. Various strategies have been adopted to fill this gap, within which vision-based methods have attracted growing attention due to the widespread use of cameras on mobile devices. However, current vision-based methods using image processing have yet to revealed their full potential for navigation applications and are insufficient in many aspects. Therefore in this paper, we present a hybrid image-based positioning system that is intended to provide seamless position solution in six degrees of freedom (6DoF) for location-based services in both outdoor and indoor environments. It mainly uses visual sensor input to match with geo-referenced images for image-based positioning resolution, and also takes advantage of multiple onboard sensors, including the built-in GPS receiver and digital compass to assist visual methods. Experiments demonstrate that such a system can greatly improve the position accuracy for areas where the GPS signal is negatively affected (such as in urban canyons), and it also provides excellent position accuracy for indoor environments.
机译:无处不在的定位被认为是当今基于位置的服务(LBS)的一项非常苛刻的应用。尽管基于卫星的导航在过去的几十年中取得了长足的进步,但是在室内场景和城市深处的定位和导航仍然是一个具有重大研究兴趣的挑战性课题。为了填补这一空白,已经采取了各种策略,其中,由于摄像头在移动设备上的广泛使用,基于视觉的方法引起了越来越多的关注。但是,当前使用图像处理的基于视觉的方法尚未显示出其在导航应用中的全部潜力,并且在许多方面还不够。因此,在本文中,我们提出了一种基于图像的混合定位系统,旨在为室外和室内环境中的基于位置的服务提供六个自由度(6DoF)的无缝位置解决方案。它主要使用视觉传感器输入与地理参考图像进行匹配,以实现基于图像的定位分辨率,还利用了多个内置传感器的优势,包括内置GPS接收器和数字罗盘以辅助视觉方法。实验表明,这种系统可以极大地提高GPS信号受到不利影响的区域(例如,城市峡谷中)的位置精度,并且还可以为室内环境提供出色的位置精度。

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