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

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.


2021 ◽  
Vol 7 ◽  
pp. e704
Author(s):  
Wei Ma ◽  
Shuai Zhang ◽  
Jincai Huang

Unlike traditional visualization methods, augmented reality (AR) inserts virtual objects and information directly into digital representations of the real world, which makes these objects and data more easily understood and interactive. The integration of AR and GIS is a promising way to display spatial information in context. However, most existing AR-GIS applications only provide local spatial information in a fixed location, which is exposed to a set of problems, limited legibility, information clutter and the incomplete spatial relationships. In addition, the indoor space structure is complex and GPS is unavailable, so that indoor AR systems are further impeded by the limited capacity of these systems to detect and display location and semantic information. To address this problem, the localization technique for tracking the camera positions was fused by Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). The multi-sensor fusion-based algorithm employs a particle filter. Based on the direction and position of the phone, the spatial information is automatically registered onto a live camera view. The proposed algorithm extracts and matches a bounding box of the indoor map to a real world scene. Finally, the indoor map and semantic information were rendered into the real world, based on the real-time computed spatial relationship between the indoor map and live camera view. Experimental results demonstrate that the average positioning error of our approach is 1.47 m, and 80% of proposed method error is within approximately 1.8 m. The positioning result can effectively support that AR and indoor map fusion technique links rich indoor spatial information to real world scenes. The method is not only suitable for traditional tasks related to indoor navigation, but it is also promising method for crowdsourcing data collection and indoor map reconstruction.



2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaoji Niu ◽  
Tong Yu ◽  
Jian Tang ◽  
Le Chang

Multisensors (LiDAR/IMU/CAMERA) integrated Simultaneous Location and Mapping (SLAM) technology for navigation and mobile mapping in a GNSS-denied environment, such as indoor areas, dense forests, or urban canyons, becomes a promising solution. An online (real-time) version of such system can extremely extend its applications, especially for indoor mobile mapping. However, the real-time response issue of multisensors is a big challenge for an online SLAM system, due to the different sampling frequencies and processing time of different algorithms. In this paper, an online Extended Kalman Filter (EKF) integrated algorithm of LiDAR scan matching and IMU mechanization for Unmanned Ground Vehicle (UGV) indoor navigation system is introduced. Since LiDAR scan matching is considerably more time consuming than the IMU mechanism, the real-time synchronous issue is solved via a one-step-error-state-transition method in EKF. Stationary and dynamic field tests had been performed using a UGV platform along typical corridor of office building. Compared to the traditional sequential postprocessed EKF algorithm, the proposed method can significantly mitigate the time delay of navigation outputs under the premise of guaranteeing the positioning accuracy, which can be used as an online navigation solution for indoor mobile mapping.





Currently, virtual technology is applied to everyday life. AR (Augmented Reality) has widely become a challenger technology that brings virtual 3D images into the real world through a camera. Augmented Reality is a technology that brings virtual images that is a 3D model simulated into the real world through cameras and processing that brings objects to overlap into one image and AR can help people to understand the content easily. Hence, in increasing the efficiency of services and publicizing various information, this paper presents the smart navigation system using augmented reality based on a smartphone in the case study of Benjakitti Park, Thailand. The application can navigate users to the POI destination and the system based on mobile devices is composed of two parts: the navigation application and the bone collector game. This project produced user satisfaction at a good level and the proposed application was able to support the significant information for navigation in aspects of performance, usability, and effectiveness.



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