Indoor localisation by using wireless sensor nodes

This study is devoted to investigating and developing WSN based localisation approaches with high position accuracies indoors. The study initially summarises the design and implementation of localisation systems and WSN architecture together with the characteristics of LQI and RSSI values. A fingerprint localisation approach is utilised for indoor positioning applications. A k-nearest neighbourhood algorithm (k-NN) is deployed, using Euclidean distances between the fingerprint database and the object fingerprints, to estimate unknown object positions. Weighted LQI and RSSI values are calculated and the k-NN algorithm with different weights is utilised to improve the position detection accuracy. Different weight functions are investigated with the fingerprint localisation technique. A novel weight function which produced the maximum position accuracy is determined and employed in calculations. The study covered designing and developing the centroid localisation (CL) and weighted centroid localisation (WCL) approaches by using LQI values. A reference node localisation approach is proposed. A star topology of reference nodes are to be utilized and a 3-NN algorithm is employed to determine the nearest reference nodes to the object location. The closest reference nodes are employed to each nearest reference nodes and the object locations are calculated by using the differences between the closest and nearest reference nodes. A neighbourhood weighted localisation approach is proposed between the nearest reference nodes in star topology. Weights between nearest reference nodes are calculated by using Euclidean and physical distances. The physical distances between the object and the nearest reference nodes are calculated and the trigonometric techniques are employed to derive the object coordinates. An environmentally adaptive centroid localisation approach is proposed.Weighted standard deviation (STD) techniques are employed adaptively to estimate the unknown object positions. WSNs with minimum RSSI mean values are considered as reference nodes across the sensing area. The object localisation is carried out in two phases with respect to these reference nodes. Calculated object coordinates are later translated into the universal coordinate system to determine the actual object coordinates. Virtual fingerprint localisation technique is introduced to determine the object locations by using virtual fingerprint database. A physical fingerprint database is organised in the form of virtual database by using LQI distribution functions. Virtual database elements are generated among the physical database elements with linear and exponential distribution functions between the fingerprint points. Localisation procedures are repeated with virtual database and localisation accuracies are improved compared to the basic fingerprint approach. In order to reduce the computation time and effort, segmentation of the sensing area is introduced. Static and dynamic segmentation techniques are deployed. Segments are defined by RSS ranges and the unknown object is localised in one of these segments. Fingerprint techniques are applied only in the relevant segment to find the object location. Finally, graphical user interfaces (GUI) are utilised with application program interfaces (API), in all calculations to visualise unknown object locations indoors

Ubiquitous Positioning: A Taxonomy for Location Determination on Mobile Navigation System

The location determination in obstructed area can be very challenging especially if Global Positioning System are blocked. Users will find it difficult to navigate directly on-site in such condition, especially indoor car park lot or obstructed environment. Sometimes, it needs to combine with other sensors and positioning methods in order to determine the location with more intelligent, reliable and ubiquity. By using ubiquitous positioning in mobile navigation system, it is a promising ubiquitous location technique in a mobile phone since as it is a familiar personal electronic device for many people. However, as research on ubiquitous positioning systems goes beyond basic methods there is an increasing need for better comparison of proposed ubiquitous positioning systems. System developers are also lacking of good frameworks for understanding different options during building ubiquitous positioning systems. This paper proposes taxonomy to address both of these problems. The proposed taxonomy has been constructed from a literature study of papers and articles on positioning estimation that can be used to determine location everywhere on mobile navigation system. For researchers the taxonomy can also be used as an aid for scoping out future research in the area of ubiquitous positioning.Comment: 15 Pages, 3 figure

Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Modeling the Behavior of Multipath Components Pertinent to Indoor Geolocation

Recently, a number of empirical models have been introduced in the literature for the behavior of direct path used in the design of algorithms for RF based indoor geolocation. Frequent absence of direct path has been a major burden on the performance of these algorithms directing researchers to discover algorithms using multipath diversity. However, there is no reliable model for the behavior of multipath components pertinent to precise indoor geolocation. In this dissertation, we first examine the absence of direct path by statistical analysis of empirical data. Then we show how the concept of path persistency can be exploited to obtain accurate ranging using multipath diversity. We analyze the effects of building architecture on the multipath structure by demonstrating the effects of wall length and wall density on the path persistency. Finally, we introduce a comprehensive model for the spatial behavior of multipath components. We use statistical analysis of empirical data obtained by a measurement calibrated ray-tracing tool to model the time-of- arrival, angle-of-arrival and path gains. The relationship between the transmitter-receiver separation and the number of paths are also incorporated in our model. In addition, principles of ray optics are applied to explain the spatial evolution of path gains, time-of-arrival and angle-of-arrival of individual multipath components as a mobile terminal moves inside a typical indoor environment. We also use statistical modeling for the persistency and birth/death rate of the paths

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

THE GLOBAL OPTIMAL PLACEMENT OF BLE BEACON FOR LOCALIZATION BASED ON INDOOR MAP

Anchor Nodes in a localization system obviously play a crucial role in determining the system’s quality. Their placement directly affects the localization accuracy and their number directly impacts the total cost of the system. Nowadays, the deployment of Bluetooth nodes in industry generally relies on the experience knowledge of engineers and the cost of positioning beacon does not considered the global level. In this paper, we put forward a method to extract the number and location of BLE beacon automatically and ensure a high positioning accuracy of the indoor positioning system based the rules of indoor positioning, which use all kinds of space objects and structure characteristics of indoor map. The triangulation method was selected to study the global optimal placement of BLE beacon for localization based on indoor map. The impacts and requirements of BLE beacon placement were systematic analysed from the triangulation positioning method, indoor positioning environment and indoor user distribution characteristics. According to the characteristics of indoor environment structure and user distribution, we built an optimization model of BLE beacon placement method based on genetic algorithm which can generate the number and the location of BLE beacon. At last, the Bluetooth indoor positioning prototype system is developed to compare the experience method deployment scheme and the global optimization deployment scheme in the real indoor positioning environment

Antenas setoriais para sistemas de localização em redes de sensores sem fios

Doutoramento em Engenharia EletrotécnicaThis work investigates low cost localization systems (LS) based on received signal strength (RSS) and integrated with different types of antennas with main emphasis on sectorial antennas. The last few years have witnessed an outstanding growth in wireless sensor networks (WSN). Among its various possible applications, the localization field became a major area of research. The localization techniques based on RSS are characterized by simplicity and low cost of integration. The integration of LS based on RSS and sectorial antennas (SA) was proven to provide an effective solution for reducing the number of required nodes of the networks and allows the combination of several techniques, such as RSS and angle of arrival (AoA). This PhD thesis focuses on studying techniques, antennas and protocols that best meet the needs of each LS with main focus on low cost systems based on RSS and AoA. Firstly there are studied localization techniques and system that best suit the requirements of the user and the antennas that are most appropriate according to the nature of the signal. In this step it is intended to provide a fundamental understanding of the undertaken work. Then the developed antennas are presented according to the following categories: sectorial and microstrip antennas. Two sectorial antennas are presented: a narrowband antenna operating at 2.4 to 2.5 GHz and a broadband antenna operating at 800MHz-2.4GHz. The low cost printed antennas were designed to operate at 5 GHz, which may be used for vehicular communication. After presenting the various antennas, several prototypes of indoor/outdoor LS are implemented and analyzed. Localization protocols are also proposed, one based on simplicity and low power, and the other on interoperability with different types of antennas and system requirements.O presente trabalho investiga sistemas de localização (SL) de baixo custo baseados na intensidade do sinal (RSS) e integrados com diferentes tipos de antenas com principal destaque para antenas sectoriais. Os últimos anos testemunharam um crescimento surpreendente de redes de sensores sem fios (RSSF), onde entre diversas aplicações possíveis, a localização tornou-se uma das principais áreas de pesquisa. Técnicas baseadas na intensidade do sinal caracterizam-se pela simplicidade e baixo custo de integração. A integração de SL baseados na intensidade do sinal recebido e antenas sectoriais (AS) oferecem uma solução eficaz para reduzir o número de nós necessários e para combinar diversas técnicas de localização. Esta tese de doutoramento foca-se no estudado de técnicas, antenas e protocolos de acordo com os requisitos de cada sistema localização com especial atenção para sistemas de baixo custo baseados na intensidade do sinal e no ângulo de chegada. Inicialmente são estudadas técnicas e SL de acordo com as necessidades do utilizador e as antenas que melhor se enquadram de acordo com a natureza do sinal. Esta etapa tem como objectivo proporcionar a compreensão fundamental do trabalho desenvolvido. Em seguida são apresentadas as antenas desenvolvidas divididas em: antenas sectorias e antenas impressas de baixo custo. Duas antenas sectoriais são apresentadas: uma de banda estreita a operar a 2,4-2,5GHz e outro de banda larga 800MHz-2.4GHz. As antenas impressas foram desenvolvidas para operar a 5 GHz, pelo que podem ser utilizadas para comunicação veicular. Após apresentação das diversas antenas vários protótipos de SL interiores/exteriores são implementados e analisados. Protocolos de localização são também propostos, um baseado na simplicidade e baixo consumo, outro na interoperabilidade com diferentes tipos de antenas e requisitos do sistema

Camera Marker Networks for Pose Estimation and Scene Understanding in Construction Automation and Robotics.

The construction industry faces challenges that include high workplace injuries and fatalities, stagnant productivity, and skill shortage. Automation and Robotics in Construction (ARC) has been proposed in the literature as a potential solution that makes machinery easier to collaborate with, facilitates better decision-making, or enables autonomous behavior. However, there are two primary technical challenges in ARC: 1) unstructured and featureless environments; and 2) differences between the as-designed and the as-built. It is therefore impossible to directly replicate conventional automation methods adopted in industries such as manufacturing on construction sites. In particular, two fundamental problems, pose estimation and scene understanding, must be addressed to realize the full potential of ARC. This dissertation proposes a pose estimation and scene understanding framework that addresses the identified research gaps by exploiting cameras, markers, and planar structures to mitigate the identified technical challenges. A fast plane extraction algorithm is developed for efficient modeling and understanding of built environments. A marker registration algorithm is designed for robust, accurate, cost-efficient, and rapidly reconfigurable pose estimation in unstructured and featureless environments. Camera marker networks are then established for unified and systematic design, estimation, and uncertainty analysis in larger scale applications. The proposed algorithms' efficiency has been validated through comprehensive experiments. Specifically, the speed, accuracy and robustness of the fast plane extraction and the marker registration have been demonstrated to be superior to existing state-of-the-art algorithms. These algorithms have also been implemented in two groups of ARC applications to demonstrate the proposed framework's effectiveness, wherein the applications themselves have significant social and economic value. The first group is related to in-situ robotic machinery, including an autonomous manipulator for assembling digital architecture designs on construction sites to help improve productivity and quality; and an intelligent guidance and monitoring system for articulated machinery such as excavators to help improve safety. The second group emphasizes human-machine interaction to make ARC more effective, including a mobile Building Information Modeling and way-finding platform with discrete location recognition to increase indoor facility management efficiency; and a 3D scanning and modeling solution for rapid and cost-efficient dimension checking and concise as-built modeling.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113481/1/cforrest_1.pd

A Novel Approach To Intelligent Navigation Of A Mobile Robot In A Dynamic And Cluttered Indoor Environment

The need and rationale for improved solutions to indoor robot navigation is increasingly driven by the influx of domestic and industrial mobile robots into the market. This research has developed and implemented a novel navigation technique for a mobile robot operating in a cluttered and dynamic indoor environment. It divides the indoor navigation problem into three distinct but interrelated parts, namely, localization, mapping and path planning. The localization part has been addressed using dead-reckoning (odometry). A least squares numerical approach has been used to calibrate the odometer parameters to minimize the effect of systematic errors on the performance, and an intermittent resetting technique, which employs RFID tags placed at known locations in the indoor environment in conjunction with door-markers, has been developed and implemented to mitigate the errors remaining after the calibration. A mapping technique that employs a laser measurement sensor as the main exteroceptive sensor has been developed and implemented for building a binary occupancy grid map of the environment. A-r-Star pathfinder, a new path planning algorithm that is capable of high performance both in cluttered and sparse environments, has been developed and implemented. Its properties, challenges, and solutions to those challenges have also been highlighted in this research. An incremental version of the A-r-Star has been developed to handle dynamic environments. Simulation experiments highlighting properties and performance of the individual components have been developed and executed using MATLAB. A prototype world has been built using the WebotsTM robotic prototyping and 3-D simulation software. An integrated version of the system comprising the localization, mapping and path planning techniques has been executed in this prototype workspace to produce validation results