Design and Error Analysis of a Vehicular AR System with Auto-Harmonization

Abstract

This paper describes the design, development and testing of an AR system that was developed for aerospace and ground vehicles to meet stringent accuracy and robustness requirements. The system uses an optical see-through HMD, and thus requires extremely low latency, high tracking accuracy and precision alignment and calibration of all subsystems in order to avoid mis-registration and "swim". The paper focuses on the optical/inertial hybrid tracking system and describes novel solutions to the challenges with the optics, algorithms, synchronization, and alignment with the vehicle and HMD systems. Tracker accuracy is presented with simulation results to predict the registration accuracy. A car test is used to create a through-the-eyepiece video demonstrating well-registered augmentations of the road and nearby structures while driving. Finally, a detailed covariance analysis of AR registration error is derived.

Registration errors in beacon-based navigation guidance systems: Influences on path efficiency and user reliance

“…Applications requiring the precise placement of virtual landmark tags are particularly challenging in outdoor environments due to tracking imprecision and resulting registration errors (Carmigniani et al, 2011;Foxlin et al, 2015). Navigation guidance poses a particular problem given its reliance on precise landmark tagging and real-time tracking of user orientations relative to landmark positions, and error accumulates in the system as either or both of these exhibits imprecision.…”

“…Whereas reduced path efficiency among tourists navigating between points of interest may not prove particularly detrimental to the task or user, the same reductions may prove disastrous among military personnel navigating on foot through unfamiliar city areas. Thus, system designers and users will need to cater registration accuracy requirements to contexts and task demands; for instance, systems that continually monitor and assess registration error accumulation (Foxlin et al, 2015;Miura et al, 2015) could establish approximate thresholds for providing users with feedback regarding variable system reliability (Chavaillaz et al, 2016).…”

“…While augmented reality has progressed tremendously over the past several decades, it also faces several technological challenges that limit system accuracy, reduce user performance, and reduce user trust in system reliability (Van Krevelen and Poelman, 2010). Broadly speaking, these limitations include: 1) the complexity of generating accurate 3D models and annotations of complex environments (Bartie et al, 2015;Behzadan and Kamat, 2007;Picard, 2003), 2) tracking a user's movement and orientation relative to the real-world (Azuma, 1997;Foxlin et al, 2015), and 3) registration between the virtual and real worlds, involving the relation between a user's current position and orientation, the 3D world model, and the visual display (Holloway, 1997;Tomioka et al, 2013). The present study focuses on the challenge of accurate registration between the virtual and real worlds.…”