Mobile Navigation Research Articles

Novel Method of Determining Vehicle Cartesian Location Using Dual Active Optical Beacons and a Rotating Photosensor

A novel system for sensing the location of a vehicle in a region of interest has been implemented; it has applications for mobile ground or aerial vehicle navigation (or positioning) in environments where other types of environmental localization are absent (e.g., lack of radio or GPS signals). The system uses photodetection of encoded laser-beam pulses emitted from a pair of beacons to gather information and perform localization calculations with reasonable accuracy. Testing of the realized system has shown consistent results that are in line with predictions from the previous model simulations. The approach of using dual angle-encoded beacons is shown to be a valid methodology for determining relative location and orientation in a sterile environment. Future optimizations would increase the pulse rates of the lasers, the rotational speed of the beacons, and use mirrors or prisms to replace the rotating detector with a stationary one.

Accessible Mobile Navigation: Convenience to Some Is Independence for Others

Accessible Mobile Navigation: Convenience to Some Is Independence for Others

Mobile Navigation in Emergency Environment Using Wireless Sensor Networks

WSN's are used with the ultimate objective of condition checking and are a trademark choice of the system to enable emergency to course services. Even though The course routes picked by the present technique guarantee productive course and gives perfect most secure route by using the min-max rule close by the quantification approaches ,however fails to identify the gathering .In the present structure we used an estimation called as SEND which does not revolve around the stop up at a particular zone however, in the proposed structure we use a computation called as CAN i.e blockage adaptable navigation, which bases on the congested locale by swarm recognizing and associates the person to move in an elective way where the hazard level is low and the A* figuring for briefest path. The proposed system moreover has the segment to show no less than two ways which improves the prosperity by empowering the customer to pick the most pleasing path .By coordinating customers following the dive edge of the hazard potential field , The CAN count can along these lines gain guaranteed ground of course and give perfect prosperity.

Travelers or locals? Identifying meaningful sub-populations from human movement data in the absence of ground truth

As users of mobile devices make phone calls, browse the web, or use an app, large volumes of data are routinely generated that are a potentially useful source for investigating human behavior in space. However, as such data are usually collected only as a by-product, they often lack stringent experimental design and ground truth, which makes interpretation and derivation of valid behavioral conclusions challenging. Here, we propose an unsupervised, data-driven approach to identify different user types based on high-resolution human movement data collected from a smartphone navigation app, in the absence of ground truth. We capture spatio-temporal footprints of users, characterized by meaningful summary statistics, which are then used in an unsupervised step to identify user types. Based on an extensive dataset of users of the mobile navigation app Sygic in Australia, we show how the proposed methodology allows to identify two distinct groups of users: ‘travelers’, visiting different areas with distinct, salient characteristics, and ‘locals’, covering shorter distances and revisiting many of their locations. We verify our approach by relating user types to space use: we find that travelers and locals prefer to visit distinct, different locations in the Australian cities Sydney and Melbourne, as suggested independently by other studies. Although we use high-resolution GPS data, the proposed methodology is potentially transferable to low-resolution movement data (e.g. Call Detail Records), since we rely only on summary statistics.

The Provision of Mobile Services in US Urban Libraries

To determine the present situation regarding services provided to mobile users in US urban libraries, the authors surveyed 138 Urban Libraries Council members utilizing a combination of mobile visits, content analysis, and librarian interviews. The results show that nearly 95% of these libraries have at least one mobile website, mobile catalog, or mobile app. The libraries actively applied new approaches to meet each local community’s remote-access needs via new technologies, including app download links, mobile reference services, scan ISBN, location navigation, and mobile printing. Mobile services that libraries provide today are timely, convenient, and universally applicable.

Investigation and Development of 3D Printed Biodegradable PLA as Compact Antenna for Broadband Applications

This paper presents the feasibility of biodegradable Polylactic Acid (PLA) for the creation of 3D structure as a radiator. Biodegradable PLA is a special type of polymer having a dielectric constant () of 3.45 with loss tangent (tan δ) of 0.05 which is made from renewable resources instead of non-renewable petroleum-based resources. Three conventional Dielectric Resonator Antennas (DRAs), i.e. Cylindrical DR Antenna (CDRA), Rectangular DR Antenna (RDRA), and Triangular DR Antenna (TDRA) with supporting pillars have been developed and investigated for broadband applications. These three different structures are used to validate the features of PLA for antenna applications. Proposed antennas cover wide impedance bandwidth of 74.54%, 71.36%, and 69.05% (|S11| < −10 dB) for CDRA, RDRA, and TDRA, respectively. Measured results are correlated with simulations. The average peak gain of proposed antennas is more than 4 dBi within operating band. The fabricated antenna possesses compact size with light-weight and cost-effective feature. Thus, proposed antennas can use for a variety of wireless applications such as weather monitoring, air traffic control, scanning & discrimination, mobile service, radio navigation, and many other applications of C-band, X-band, and Ku-band.

An AR mobile navigation system integrating indoor positioning and content recommendation services

Over the past few years, with the prevalence of smart mobile devices, several well-known museums and researchers have developed mobile navigation systems to improve the navigation effect for museum visitors. However, most of these systems lack efficient content recommendation, indoor positioning, and augmented reality (AR) display functions, and this situation causes difficulty for visitors to have a personalized and efficient navigation experience. This paper presents an augmented reality mobile navigation system that supports indoor positioning and content recommendation services, which aims to provide personalized suggestions corresponding to the user’s context through the analysis of the interest and location information of visitors. Moreover, combined with the developed markerless augmented reality display functions, this system could effectively enrich and improve visitor’s navigation experience.

Mobile Navigation Algorithm in Emergency Hazardous Process using WSN

Mobile Navigation Algorithm in Emergency Hazardous Process using WSN

Intelligence Context Aware Mobile Navigation using Augmented Reality Technology

Most of the technologies of today’s world, which are enriched with various powerful features and amazing quality characteristics, enables software developers to come up with best possible software solutions, no matter what the context of the particular issue. Technologies such as Augmented Reality (AR), is utilized almost every kind of fields in today’s society. As computers become more advanced through mobile devices and wearable technology, augmented reality will become a seamless experience that is a part of our everyday lives. In the context of this work, an Intelligence mobile navigation application for the King Abdul Aziz University Rabigh is developed enabling the user to find specific locations on campus and offers the ability to explore the campus environment via AR. Furthermore, the system, Mobile Campus Navigation with Augmented Reality application is capable of giving guidance in outdoor location navigating and retrieving details of campus officials and lecturers. With the proposed system, it is expected to serve as a useful and informative navigate helper for both students of King Abdul Aziz University and for the visitors, at outdoor locations and to use as an application to check officials and lecturer availability and retrieve detail about them when they are not available at the office at any time.

Bio-inspired decentralized autonomous robot mobile navigation control for multi agent systems

Bio-inspired decentralized autonomous robot mobile navigation control for multi agent systems

Localization of mobile using RSS and Hilbert-Huang transform

Mobile navigation has drawn much attention in multitudinous application. However, operational capability of mobile degrades due to buildings and dense foliage. The proposed methods like ‘RSS mobile estimation using wavelets’ are designed for detecting the mobile location for different outdoor environments. This paper presents deciphers the subtleties involved in the application of EMD and Hilbert-Huang Transform approach applied for collected rural and urban data for mobile localization possible even in indoor scenario. By experimental results shown the variations in signal strength due to the distance travelled by the mobile.

Research into Kinect/Inertial Measurement Units Based on Indoor Robots.

As indoor mobile navigation suffers from low positioning accuracy and accumulation error, we carried out research into an integrated location system for a robot based on Kinect and an Inertial Measurement Unit (IMU). In this paper, the close-range stereo images are used to calculate the attitude information and the translation amount of the adjacent positions of the robot by means of the absolute orientation algorithm, for improving the calculation accuracy of the robot’s movement. Relying on the Kinect visual measurement and the strap-down IMU devices, we also use Kalman filtering to obtain the errors of the position and attitude outputs, in order to seek the optimal estimation and correct the errors. Experimental results show that the proposed method is able to improve the positioning accuracy and stability of the indoor mobile robot.

Analysing the impact of travel information for minimising the regret of route choice

In the route choice problem, self-interested drivers aim at choosing routes that minimise travel costs between their origins and destinations. We model this problem as a multiagent reinforcement learning scenario. Here, since agents must adapt to each others’ decisions, the minimisation goal is seen as a moving target. Regret is a well-known performance measure in such settings, and considers how much worse an agent performs compared to the best fixed action in hindsight. In general, regret cannot be computed (and used) by agents because its calculation requires observing the costs of all available routes (including non-taken ones). In contrast to previous works, here we show how agents can compute regret by building upon their experience and via information provided by a mobile (Waze-like) navigation app. Specifically, we compute the regret of each action as a linear combination of local (experience-based) and global (app-based) information. We refer to such a measure as the action regret, which can be used by the agents as reinforcement signal. Under these conditions, agents are able to minimise their external regret even when the cost of routes is not known in advance. Based on experimental evaluation in several abstract road networks, we show that the system converges to approximate User Equilibria.

A Deviate-Based Prioritizing Technique for Regression Testing of Mobile Navigation Service

Mobile navigation service is an important and popular location-based services, which help to recommend routes for mobile users to their destinations. Modern mobile navigation service provides various navigation strategies and considers many complex situations, which make validation and verification of mobile navigation service becomes very difficult. In this paper, we present an approach to prioritize test cases for regression testing of mobile navigation Service. The approach is based on the assumption that there may be a failure if the user's actual route deviates from the navigation recommended route. In this paper, we analyze the mass mobile navigation logs, compare the recommended routes with the user travel routes, identify the deviation of the intersection point, and then priority regression test data by deviation. To evaluate our approach, we conduct a case study on a popular navigation software. By compare proposed prioritizing test approach with random test approach, the approach helps to improve test efficiency.

Static stability design and test method of the autonomous mobile navigation robot

Static stability design and test method of the autonomous mobile navigation robot

Common Platform for Autonomous Low-Speed Mobility System

Development for safety autonomous mobility navigation system that deal with low speed vehicles, such as wheel chair, guidance robot and transportation robot is introduced. Our R&D policy based on Ethical, Legal, Social and Economic issues for the mobility system is also introduced.

Experimental studies of a convolutional neural network for application in the navigation system of a mobile robot

Presently, convolutional neural networks grow rapidly in the field of objects recognition and obstacle detection in the image. Recognition is one of the most important problems for development of modern mobile navigation systems. We propose to link up an artificial neural network as an additional or a backup solution for higher safety of these systems while the obstacles are being detected. The purpose of this work is to conduct experimental studies in order to identify the strengths and weaknesses of an artificial neural network for practical application in navigation systems for mobile robots. The largest possible detection accuracy and training time of the artificial neural network have been measured experimentally with the use of two methods. There has been evaluated the effect of the subset size of the epoch influencing the accuracy of detection. The dataset structure has been analyzed and the direct relationship between the accuracy of detection and the surface value of the recognized object was found. The mobile robot utilization and the frequency of processed frames from the video stream during the operation of the artificial neural network have been measured.

3D Visualization of Urban Area Using Lidar Technology and CityGML

3D models of urban areas have found use in modern world such as navigation, cartography, urban planning visualization, construction, tourism and even in new applications of mobile navigations. With the advancement of technology there are much better solutions for mapping earth’s surface and spatial objects. 3D city model enables exploration, analysis, management tasks and presentation of a city. Urban areas consist of terrain surfaces, buildings, vegetation and other parts of city infrastructure such as city furniture. Nowadays there are a lot of different methods for collecting, processing and publishing 3D models of area of interest. LIDAR technology is one of the most effective methods for collecting data due the large amount data that can be obtained with high density and geometrical accuracy. CityGML is open standard data model for storing alphanumeric and geometry attributes of city. There are 5 levels of display (LoD0, LoD1, LoD2, LoD3, LoD4). In this study, main aim is to represent part of urban area of Novi Sad using LIDAR technology, for data collecting, and different methods for extraction of information’s using CityGML as a standard for 3D representation. By using series of programs, it is possible to process collected data, transform it to CityGML and store it in spatial database. Final product is CityGML 3D model which can display textures and colours in order to give a better insight of the cities. This paper shows results of the first three levels of display. They consist of digital terrain model and buildings with differentiated rooftops and differentiated boundary surfaces. Complete model gives us a realistic view of 3D objects.

AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA

Abstract. LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D building models can be generated successfully using raw LiDAR point cloud data.

Children's Perception of Surroundings in an Unfamiliar Environment

This article presents the results of research on how ten-year-old children in an unfamiliar environment perceive the surroundings of the route during their wayfinding when they focus on the task of successfully orienting themselves with two different sources of cartographic support: a mobile navigator and a paper map. The results show that the children are relatively imprecise with the verbal description of the route, whereas when it comes to perceiving the environment on the basis of recognizing visual features (in photographs), they score better results when using a paper map rather than a mobile navigator.