Indoor navigation with vision, INS and reality-based 3D maps

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Embargoed until 2023-06-23
Copyright: Chen, Kai
Navigation is a technique for the determination of position and attitude of a moving platform with respect to a known reference. Global Navigation Satellite System (GNSS) has become a dominating navigation technology. However, GNSS signals are degraded or denied in indoor environments. It is necessary to develop alternative positioning techniques for indoor navigation to realize seamless navigation. Inertial Navigation System (INS) and Vision are both regarded to be highly promising because of their ubiquitous and self-contained nature. A new indoor navigation system with vision, INS and reality-based 3D maps are proposed. The main contributions of this thesis are summarized as follows: 1. A new strategy for the integration of vision with a low-cost INS has been developed based on a smartphone. This new approach solves the difficulty of precise calibration of INS errors in such a scenario and enables MEMS INS to generate stable position and attitude solutions. 2. Results show that improved accuracy and reliability of the geo-referenced solution can be achieved. Vision-based navigation with reality-based 3D maps (Vision)/INS integration improves the accuracy and robustness of a navigation solution compared with an INS only solution. 3. Aiding Optical Flow (OF) and Visual Odometry (VO) navigation solution to Vision/INS integrated system improved geo-referenced results during Vision outages. The results confirmed the effectiveness of integration for high accuracy positioning applications. 4. A novel geo-referenced system based on Vision/OF/VO/INS integration has been developed and tested for indoor navigation. Real experiments are conducted to evaluate the influence of different integrated configurations on the performance of the navigation system. 5. Integrated indoor navigation requires a robust outlier detection mechanism to ensure good performance. Outlier detection and identification are explored and researched on the integrated indoor navigation system. Besides, a multi-level outlier detection scheme for the navigation system has been proposed. 6. Analyzing the factors that influence the correlation coefficients between fault test statistics in Vision/INS measurements and the dynamic model is another essential contribution of this thesis. Reliability and separability analysis of outlier detection theory was extended by providing a more reliable estimation of MDB and MSB. 
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Chen, Kai
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PhD Doctorate
UNSW Faculty