Abstract
Smartphones have become indispensable in our daily lives. Their various embedded sensors have inspired innovations in mobile applications—especially for indoor navigation. However, the accuracy, reliability and generalizability of navigation all continue to struggle in environments lacking a Global Navigation Satellite System (GNSS). Pedestrian Dead Reckoning (PDR) is a popular method for indoor pedestrian navigation. Unfortunately, due to its fundamental principles, even a small navigation error will amplify itself, step by step, generally leading to the need for supplementary resources to maintain navigation accuracy. Virtually all mobile devices and most robots contain a basic camera sensor, which has led to the popularity of image-based localization, and vice versa. However, all of the image-based localization requires continuous images for uninterrupted positioning. Furthermore, the solutions provided by either image-based localization or a PDR are usually in a relative coordinate system. Therefore, this research proposes a system, which uses space resection-aided PDR with geo-referenced images of a previously mapped environment to enable seamless navigation and solve the shortcomings of PDR and image-based localization, and evaluates the performance of space resection with different assumptions using a smartphone. The indoor mobile mapping system (IMMS) is used for the effective production of geo-referenced images. The preliminary results indicate that the proposed algorithm is suitable for universal pedestrian indoor navigation, achieving the accuracy required for commercial applications.
Highlights
A variety of indoor navigation technologies based on different principles and hardware have been developed over the last two decades [1]
The proposed space resection-aided Pedestrian Dead Reckoning (PDR) is implemented in the underground parking lot, which is mapped by indoor mobile mapping system (IMMS)
By using the proposed algorithm, the user only needs a smartphone with an embedded inertial sensor and camera to estimate location
Summary
A variety of indoor navigation technologies based on different principles and hardware have been developed over the last two decades [1]. Li et al propose a hybrid image-based localization for seamless navigation based upon GNSS, a compass, calibrated camera and space resection with geo-referenced images [30] They believe such technologies have the potential for indoor and outdoor navigation using a smartphone. This research proposes novel usage of space resection to aid PDR with geo-referenced images in a previously mapped environment. The position error of space resection caused by the use of an un-calibrated smartphone camera is improved after applying the proposed adaptive weight method. TThhee ccoorree mmeetthhooddss uusseedd iinn tthhiiss rreesseeaarrcchh ccaann bbee ddiivviiddeedd iinnttoo tthhrreeee mmaajjoorr ppaarrttss:: iinnddoooorr mmaappppiinngg,, ssppaaccee rreesseeccttiioonn,, aanndd PPDDRR,, eeaacchh ddeessccrriibbeedd iinn oonnee ooff tthhee ffoolllloowwiinngg sseeccttiioonnss. TThhee ddeevveellooppeedd IIMMMMSS:: ((aa)) TThhee eexxtteerriioorr ooff IIMMMMSS aanndd tthhee ssppeecciiffiiccaattiioonnss ooff tthhee uusseedd hhiigghh--ggrraaddee IIMMUU aanndd 336600--ddeeggrreeeesspphheerriiccaallccaammeerraassyysstetemm; ;(b(b))TThheeddeveveleoloppededsosfotfwtwaraerefofrodr idreircetcgtegoe-ore-rfeefreernecnincign.g
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