Abstract

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

Highlights

  • The objective of a moving platform is to provide accurate information for moving platforms, e.g., a land vehicle, an airplane, or aircraft in space, when a global positioning system (GPS) or an inertial measurement unit (IMU) is not working effectively under poor environmental conditions [1,2].Imaging sensors have been widely studied and applied to determine position and orientation via a technology called vision navigation

  • The framework of geo-referenced image database (GRID)-aided vision navigation is established with sequence images derived from land-based, multiple sensor-integrated mobile mapping systems

  • We proposed a vision navigation approach based on this database to facilitate continuous and robust navigation for GPS and IMU

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Summary

Introduction

Imaging sensors have been widely studied and applied to determine position and orientation via a technology called vision navigation. This approach may be effective for such applications because it can be utilized in a GPS/IMU-deprived environment (such as indoors, in urban canyons, and in far space) [3,4,5]. Sensors 2016, 16, 166 this approach does not depend on any signal or radiant sources [1,6]. This environmental condition becomes problematic when real-time and high-precision performance is required

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