scholarly journals An ARCore-Based Augmented Reality Campus Navigation System

2021 ◽  
Vol 11 (16) ◽  
pp. 7515
Author(s):  
Fangfang Lu ◽  
Hao Zhou ◽  
Lingling Guo ◽  
Jingjing Chen ◽  
Licheng Pei
Keyword(s):  
Augmented Reality ◽  
Navigation System ◽  
Route Planning ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Internet Media ◽  
Real Scene ◽  
3D Information ◽  
Outdoor Localization ◽  
Outdoor Navigation

Currently, the route planning functions in 2D/3D campus navigation systems in the market are unable to process indoor and outdoor localization information simultaneously, and the UI experiences are not optimal because they are limited by the service platforms. An ARCore-based augmented reality campus navigation system is designed in this paper in order to solve the relevant problems. Firstly, the proposed campus navigation system uses ARCore to enhance reality by presenting 3D information in real scenes. Secondly, a visual inertial ranging algorithm is proposed for real-time locating and map generating in mobile devices. Finally, rich Unity3D scripts are designed in order to enhance users’ autonomy and enjoyment during navigation experience. In this paper, indoor navigation and outdoor navigation experiments are carried out at the Lingang campus of Shanghai University of Electric Power. Compared with the AR outdoor navigation system of Gaode, the proposed AR system can achieve increased precise outdoor localization by deploying the visual inertia odometer on the mobile phone and realizes the augmented reality function of 3D information and real scene, thus enriching the user’s interactive experience. Furthermore, four groups of students have been selected for system testing and evaluation. Compared with traditional systems, such as Gaode map or Internet media, experimental results show that our system could facilitate the effectiveness and usability of learning on campus.

scholarly journals "Improved Geometric Network Model" (IGNM): a novel approach for deriving Connectivity Graphs for Indoor Navigation

2014 ◽  
Vol II-4 ◽  
pp. 45-51 ◽  
Author(s):  
F. Mortari ◽  
S. Zlatanova ◽  
L. Liu ◽  
E. Clementini
Keyword(s):  
Route Planning ◽  
Research Area ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Indoor Space ◽  
The Past ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Floor Plans ◽  
Algorithmic Strategy

Over the past few years Personal Navigation Systems have become an established tool for route planning, but they are mainly designed for outdoor environments. Indoor navigation is still a challenging research area for several reasons: positioning is not very accurate, users can freely move between the interior boundaries of buildings, path network construction process may not be easy and straightforward due to complexity of indoor space configurations. Therefore the creation of a good network is essential for deriving overall connectivity of a building and for representing position of objects within the environment. This paper reviews current approaches to automatic derivation of route graphs for indoor navigation and discusses some of their limitations. Then, it introduces a novel algorithmic strategy for extracting a 3D connectivity graph for indoor navigation based on 2D floor plans.

scholarly journals A LiDAR-Aided Indoor Navigation System for UGVs

2014 ◽  
Vol 68 (2) ◽  
pp. 253-273 ◽  
Author(s):  
Shifei Liu ◽  
Mohamed Maher Atia ◽  
Tashfeen B. Karamat ◽  
Aboelmagd Noureldin
Keyword(s):  
Navigation System ◽  
Error Model ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Model Errors ◽  
Integrated Navigation System ◽  
Tightly Coupled ◽  
Indoor Navigation System ◽  
Sensor Errors

Autonomous Unmanned Ground Vehicles (UGVs) require a reliable navigation system that works in all environments. However, indoor navigation remains a challenge because the existing satellite-based navigation systems such as the Global Positioning System (GPS) are mostly unavailable indoors. In this paper, a tightly-coupled integrated navigation system that integrates two dimensional (2D) Light Detection and Ranging (LiDAR), Inertial Navigation System (INS), and odometry is introduced. An efficient LiDAR-based line features detection/tracking algorithm is proposed to estimate the relative changes in orientation and displacement of the vehicle. Furthermore, an error model of INS/odometry system is derived. LiDAR-estimated orientation/position changes are fused by an Extended Kalman Filter (EKF) with those predicted by INS/odometry using the developed error model. Errors estimated by EKF are used to correct the position and orientation of the vehicle and to compensate for sensor errors. The proposed system is verified through simulation and real experiment on an UGV equipped with LiDAR, MEMS-based IMU, and encoder. Both simulation and experimental results showed that sensor errors are accurately estimated and the drifts of INS are significantly reduced leading to navigation performance of sub-metre accuracy.

scholarly journals Selected qualities of mobile maps for indoor navigation

2019 ◽  
Vol 51 (4) ◽  
pp. 155-165
Author(s):  
Dariusz Gotlib
Keyword(s):  
Navigation System ◽  
Data Model ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Stages Of Development ◽  
Positioning Systems ◽  
Presentation Method ◽  
Dynamic Growth ◽  
Definition Of ◽  
Mobile Maps

Abstract The map is the key element in any navigation system. The dynamic growth of indoor navigation systems requires improvements in quality not only of positioning systems but also of maps of building interiors. Most emergent solutions in this field do not use cartographic knowledge. Cartographic methodology for representing building interiors is still in its initial stages of development. Its proper use may, however, be of great importance to the effectiveness of indoor navigation. The author presents important features that indoor mobile maps should possess, for both the data model and the presentation method to be used. In this context, the question of the contemporary definition of a map is also discussed.

scholarly journals On the Right Track: Comfort and Confusion in Indoor Environments

2020 ◽  
Vol 9 (2) ◽  
pp. 132 ◽  
Author(s):  
Nina Vanhaeren ◽  
Laure De Cock ◽  
Lieselot Lapon ◽  
Nico Van de Weghe ◽  
Kristien Ooms ◽  
...  
Keyword(s):  
Focus Group ◽  
Online Survey ◽  
Local Level ◽  
Route Planning ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Navigation Systems ◽  
Online Study ◽  
Planning Algorithm ◽  
The Right

Indoor navigation systems are not well adapted to the needs of their users. The route planning algorithms implemented in these systems are usually limited to shortest path calculations or derivatives, minimalizing Euclidian distance. Guiding people along routes that adhere better to their cognitive processes could ease wayfinding in indoor environments. This paper examines comfort and confusion perception during wayfinding by applying a mixed-method approach. The aforementioned method combined an exploratory focus group and a video-based online survey. From the discussions in the focus group, it could be concluded that indoor wayfinding must be considered at different levels: the local level and the global level. In the online survey, the focus was limited to the local level, i.e., local environmental characteristics. In this online study, the comfort and confusion ratings of multiple indoor navigation situations were analyzed. In general, the results indicate that open spaces and stairs need to be taken into account in the development of a more cognitively-sounding route planning algorithm. Implementing the results in a route planning algorithm could be a valuable improvement of indoor navigation support.

scholarly journals ARBIN: Augmented Reality Based Indoor Navigation System

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5890
Author(s):  
Bo-Chen Huang ◽  
Jiun Hsu ◽  
Edward T.-H. Chu ◽  
Hui-Mei Wu
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Navigation System ◽  
Indoor Navigation ◽  
Ease Of Use ◽  
University Hospital ◽  
Left Turn ◽  
The Real ◽  
Series Of Experiments ◽  
Indoor Navigation System

Due to the popularity of indoor positioning technology, indoor navigation applications have been deployed in large buildings, such as hospitals, airports, and train stations, to guide visitors to their destinations. A commonly-used user interface, shown on smartphones, is a 2D floor map with a route to the destination. The navigation instructions, such as turn left, turn right, and go straight, pop up on the screen when users come to an intersection. However, owing to the restrictions of a 2D navigation map, users may face mental pressure and get confused while they are making a connection between the real environment and the 2D navigation map before moving forward. For this reason, we developed ARBIN, an augmented reality-based navigation system, which posts navigation instructions on the screen of real-world environments for ease of use. Thus, there is no need for users to make a connection between the navigation instructions and the real-world environment. In order to evaluate the applicability of ARBIN, a series of experiments were conducted in the outpatient area of the National Taiwan University Hospital YunLin Branch, which is nearly 1800 m2, with 35 destinations and points of interests, such as a cardiovascular clinic, x-ray examination room, pharmacy, and so on. Four different types of smartphone were adopted for evaluation. Our results show that ARBIN can achieve 3 to 5 m accuracy, and provide users with correct instructions on their way to the destinations. ARBIN proved to be a practical solution for indoor navigation, especially for large buildings.

Evaluation of an Accessible, Real-Time, and Infrastructure-Free Indoor Navigation System by Users Who Are Blind in the Mall of America

2019 ◽  
Vol 113 (2) ◽  
pp. 140-155 ◽  
Author(s):  
Nicholas A. Giudice ◽  
William E. Whalen ◽  
Timothy H. Riehle ◽  
Shane M. Anderson ◽  
Stacy A. Doore
Keyword(s):  
Real Time ◽  
Navigation System ◽  
Memory Load ◽  
The United States ◽  
Indoor Navigation ◽  
Shopping Mall ◽  
Navigation Systems ◽  
Route Guidance ◽  
Indoor Navigation System ◽  
The Impact

Introduction: This article describes an evaluation of MagNav, a speech-based, infrastructure-free indoor navigation system. The research was conducted in the Mall of America, the largest shopping mall in the United States, to empirically investigate the impact of memory load on route-guidance performance. Method: Twelve participants who are blind and 12 age-matched sighted controls participated in the study. Comparisons are made for route-guidance performance between use of updated, real-time route instructions (system-aided condition) and a system-unaided (memory-based condition) where the same instructions were only provided in advance of route travel. The sighted controls (who navigated under typical visual perception but used the system for route guidance) represent a best case comparison benchmark with the blind participants who used the system. Results: Results across all three test measures provide compelling behavioral evidence that blind navigators receiving real-time verbal information from the MagNav system performed route travel faster (navigation time), more accurately (fewer errors in reaching the destination), and more confidently (fewer requests for bystander assistance) compared to conditions where the same route information was only available to them in advance of travel. In addition, no statistically reliable differences were observed for any measure in the system-aided conditions between the blind and sighted participants. Posttest survey results corroborate the empirical findings, further supporting the efficacy of the MagNav system. Discussion: This research provides compelling quantitative and qualitative evidence showing the utility of an infrastructure-free, low-memory demand navigation system for supporting route guidance through complex indoor environments and supports the theory that functionally equivalent navigation performance is possible when access to real-time environmental information is available, irrespective of visual status. Implications for designers and practitioners: Findings provide insight for the importance of developers of accessible navigation systems to employ interfaces that minimize memory demands.

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