scholarly journals Selected qualities of mobile maps for indoor navigation

2019 ◽  
Vol 51 (4) ◽  
pp. 155-165
Author(s):  
Dariusz Gotlib

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.

Author(s):  
Denis Gingras

In this chapter, the authors will review the problem of estimating in real-time the position of a vehicle for use in land navigation systems. After describing the application context and giving a definition of the problem, they will look at the mathematical framework and technologies involved to design positioning systems. The authors will compare the performance of some of the most popular data fusion approaches and provide some insights on their limitations and capabilities. They will then look at the case of robustness of the positioning system when one or some of the sensors are faulty and will describe how the positioning system can be made more robust and adaptive in order to take into account the occurrence of faulty or degraded sensors. Finally, they will go one step further and explore possible architectures for collaborative positioning systems, whereas many vehicles are interacting and exchanging data to improve their own position estimate. The chapter is concluded with some remarks on the future evolution of the field.


2003 ◽  
Vol 56 (3) ◽  
pp. 385-398 ◽  
Author(s):  
Ahmad Mirabadi ◽  
Felix Schmid ◽  
Neil Mort

Onboard train positioning (navigation) plays a vital and safety critical role in advanced Automatic Train Control (ATC) and Automatic Train Protection (ATP) systems. Such onboard systems are also essential for moving block signalling and control systems for railways. The application of multi-sensor fusion algorithms to the vehicle navigation field has made it possible to create inexpensive and accurate positioning systems, which will satisfy the railways' requirements. The state estimation methods involved in Kalman filtering have proved to be some of the most effective techniques in multi-sensor data fusion. A multi-sensor navigation system is introduced in this paper to address the shortcomings of the existing train positioning systems. The proposed system utilizes the Global Positioning System (GPS), Doppler radar, gyroscopes, tachometers, digital maps and balises. In order to provide fault detection and isolation capabilities, a hierarchical structure is proposed for the multi-sensor integration system in which different combinations of navigation systems would function. Several data integration nodes, including DR/GPS, DR/Balise, and DR/GPS/Balise, are studied in more detail and their performances are evaluated.


Author(s):  
A. Masiero ◽  
H. Perakis ◽  
J. Gabela ◽  
C. Toth ◽  
V. Gikas ◽  
...  

Abstract. The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.


Author(s):  
APURVA MEHTA ◽  
D. D. PUKALE ◽  
RADHIKA BHAGAT ◽  
RUJAL SHAH

In the past few years, a number of ideas have been proposed for indoor navigation systems. These ideas were not as widely implemented as outdoor positioning systems like GPS(Global Positioning Systems). We propose an indoor navigation assistance system using Bluetooth which is low cost and feasible to use in daily life. Our system enables users with handheld mobile devices to steer with ease through the indoor premises using the short range radio frequencies of Bluetooth. It also establishes user’s current location and the various paths leading to the destination. Dijkstra’s algorithm is used to determine the shortest path from the source to the required destination.


Author(s):  
Guenther Retscher ◽  
Allison Kealy

With the increasing ubiquity of smartphones and tablets, users are now routinely carrying a variety of sensors with them wherever they go. These devices are enabling technologies for ubiquitous computing, facilitating continuous updates of a user's context. They have built-in MEMS-based accelerometers for ubiquitous activity monitoring and there is a growing interest in how to use these together with gyroscopes and magnetometers to build dead reckoning (DR) systems for location tracking. Navigation in complex environments is needed mainly by consumer users, private vehicles, and pedestrians. Therefore, the navigation system has to be small, easy to use, and have reasonably low levels of power consumption and price. The technologies and techniques discussed here include the fusion of inertial navigation (IN) and other sensors, positioning based on signals from wireless networks (such as Wi-Fi), image-based methods, cooperative positioning systems, and map matching (MM). The state-of-the-art of MEMS-based location sensors and their integration into modern navigation systems are also presented.


2014 ◽  
Vol 68 (2) ◽  
pp. 253-273 ◽  
Author(s):  
Shifei Liu ◽  
Mohamed Maher Atia ◽  
Tashfeen B. Karamat ◽  
Aboelmagd Noureldin

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.


2013 ◽  
Vol 95 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Dariusz Gotlib ◽  
Miłosz Gnat

Abstract For many years, cartographers are involved in designing GIS and navigation systems. Most GIS applications use the outdoor data. Increasingly, similar applications are used inside buildings. Therefore it is important to find the proper model of indoor spatial database. The development of indoor navigation systems should utilize advanced teleinformation, geoinformatics, geodetic and cartographical knowledge. The authors present the fundamental requirements for the indoor data model for navigation purposes. Presenting some of the solutions adopted in the world they emphasize that navigation applications require specific data to present the navigation routes in the right way. There is presented original solution for indoor data model created by authors on the basis of BISDM model. Its purpose is to expand the opportunities for use in indoor navigation.


2019 ◽  
Vol 113 (2) ◽  
pp. 140-155 ◽  
Author(s):  
Nicholas A. Giudice ◽  
William E. Whalen ◽  
Timothy H. Riehle ◽  
Shane M. Anderson ◽  
Stacy A. Doore

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.


2019 ◽  
Vol 1 ◽  
pp. 1-2 ◽  
Author(s):  
Wangshu Wang ◽  
Haosheng Huang ◽  
Hao Lyu ◽  
Georg Gartner

<p><strong>Abstract.</strong> Recent years have witnessed the rapid development of navigation systems. They gradually become the default way of navigating in our daily life. Despite benefiting from their convenience, we may be negatively influenced by them (Parush et al. 2007). Current navigation systems usually draw too much of users' attention to the mobile devices, which leads to users’ lacking interaction with the environment. It is often the case that people easily forget travelled route and get lost without navigation systems (Reilly et al. 2008). Empirical study shows that by dividing attention, navigation systems impair users’ spatial memory, and thus impact their navigation skills (Gardony et al. 2013). Since a higher engagement with the environment can improve users’ spatial knowledge acquisition without decreasing efficiency (Brügger et al. 2017), navigation systems should incorporate important environmental features.</p><p>As objects of visual, cognitive or structural importance (Sorrows &amp; Hirtle 1999), landmarks have been extensively studied, and considered as an important environmental feature to be incorporated into navigation systems (Nuhn &amp; Timpf 2018, Richter 2017, Duckham et al. 2010, Raubal &amp; Winter 2002). They serve as references to provide users with more natural and pleasant navigating experience (Richter &amp; Winter 2014). However, most of landmark-related studies are in outdoor environment. Although researchers have attempted to classify and assess indoor landmarks (Ohm 2014, Viaene 2014), it is still very difficult to determine suitable ones. As a subset of semantic indoor landmarks, existing navigational aids (e.g. signs and floor plans) are designed to assist navigation. Among them, signs are most preferred by users (Wang et al. 2017). Being the signs that give necessary information to route users to possible destinations, directional signs contribute most to wayfinding (Gibson 2009). With route information explicitly presented by them, they are relevant environmental features to be incorporated into indoor navigation systems.</p><p>In this study, we therefore propose to incorporate directional signs into indoor navigation systems, in order to guide users’ attention back to the environment, to facilitate their spatial learning and improve their spatial knowledge acquisition.</p><p>We incorporated directional signs into a proof-of-concept indoor navigation system. First, we integrated directional signs and their semantics into a graph-based model. A directional sign was modelled as a node. Each destination on the sign was linked with the sign by an edge. In order to differentiate it from the normal edge, it was marked as semantic edge. Thus, the semantics of the sign was modelled directly into the graph, instead of being stored as attributes in a previous version of our study (Wang &amp; Gartner 2018). Then, a top-K shortest path algorithm was employed to find candidate routes (Yen 1971). In the end, the route with the largest coverage of semantic edges was suggested to the user. The users would then be explicitly guided to follow the directional signs in the environment.</p><p>In the next step, we will evaluate the efficiency and effectiveness of the proposed navigation system by an empirical study with human subjects. Within the experiment, we will also investigate on whether this kind of guidance can succeed in drawing users’ attention back to the environment and support their spatial knowledge acquisition.</p>


Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2412 ◽  
Author(s):  
Zbigniew Siejka

For the last two decades, the American GPS and Russian GLONASS were the basic systems used in global positioning and navigation. In recent years, there has been significant progress in the development of positioning systems. New regional systems have been created, i.e., the Japanese Quasi-Zenith Satellite System (QZSS) and Indian Regional Navigational Satellite System (IRNSS). A plan to build its own regional navigation system named Korean Positioning System (KPS) was announced South Korea on 5 February 2018. Currently, two new global navigation systems are under development: the European Galileo and the Chinese BeiDou. The full operability of both systems by 2020 is planned. The paper deals with a possibility of determination of the user’s position from individual and independent global navigation satellite system (GNSS). The article is a broader concept aimed at independent determination of precise position from individual GPS, GLONASS, BeiDou and Galileo systems. It presents real time positioning results (Real Time Kinematic-RTK) using signals from Galileo satellites only. During the test, 14 Galileo satellites were used and the number of simultaneously observed Galileo satellites varied from five to seven. Real-time measurements were only possible in certain 24-h observation windows. However, their number was completed within 6 days at the end of 2017 and beginning of 2018, so there was possible to infer about the current availability, continuity, convergence time and accuracy of the RTK measurements. In addition, the systematic errors were demonstrated for the Galileo system.


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