Optical Indoor Positioning of Vehicles

Indoor positioning is the backbone of many advanced intra-logistic applications. As opposed to unified outdoor satellite positioning systems, there are many different technical approaches to indoor positioning. Depending on the application, there are different trade-offs between accuracy, range, and costs. In this paper we present a new concept for a 4-degree-of-freedom (4-DOF) positioning system to be used for vehicle tracing in a logistic facility. The system employs optical data transmission between active infrastructure and receiver devices. Compared to existing systems, these optical technologies promise to achieve better accuracy at lower costs. We will introduce the positioning algorithm and an experimental setup of the system.

Vision based indoor positioning in a retail environment

Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

Accurate Indoor Positioning of Firefighters using Dual Foot-mounted Inertial Sensors and Inter-agent Ranging

A real-time cooperative localization system, utilizing dual foot-mounted low-cost inertial sensors and RF-based inter-agent ranging, has been developed. Scenario-based tests have been performed, using fully-equipped firefighters mimicking a search operation in a partly smoke-filled environment, to evaluate the performance of the TOR (Tactical lOcatoR) system. The performed tests included realistic firefighter movements and inter-agent distances, factors that are crucial in order to provide realistic evaluations of the expected performance in real-world operations. The tests indicate that the TOR system may be able to provide a position accuracy of approximately two to three meters during realistic firefighter operations, with only two smoke diving firefighters and one supervising firefighter within range.

In search of reliable centimeter-level indoor positioning: a smartphone-based approach

This thesis describes the design and implementation of a reliable centimeter-level indoor positioning system fully compatible with a conventional smartphone. The proposed system takes advantage of the smartphone audio I/O and processing capabilities to perform acoustic ranging in the audio band using non-invasive audio signals and it has been developed having in mind applications that require high accuracy, such as augmented reality, virtual reality, gaming and audio guides. The system works in a distributed operation mode, i.e. each smartphone is able to obtain its own position using only acoustic signals. To support the positioning system, a Wireless Sensor Network (WSN) of synchronized acoustic beacons is used. To keep the infrastructure in sync we have developed an Automatic Time Synchronization and Syntonization (ATSS) protocol with a standard deviation of the sync offset error below 1.25 μs. Using an improved Time Difference of Arrival (TDoA) estimation approach (which takes advantage of the beacon signals’ periodicity) and by performing Non-Line-of-Sight (NLoS) mitigation, we were able to obtain very stable and accurate position estimates with an absolute mean error of less than 10 cm in 95% of the cases and a mean standard deviation of 2.2 cm for a position refresh period of 350 ms.

A Review of antenas for indoor positioning systems

This paper provides a review of antennas applied for indoor positioning or localization systems. The desired requirements of those antennas when integrated in anchor nodes (reference nodes) are discussed, according to different localization techniques and their performance. The described antennas will be subdivided into the following sections according to the nature of measurements: received signal strength (RSS), time of flight (ToF), and direction of arrival (DoA). This paper intends to provide a useful guide for antenna designers who are interested in developing suitable antennas for indoor localization systems.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

Indoor positioning using Android Platform

In recent years, there has been a great increase in the development of wireless technologies and location services. For this reason, numerous projects in the location field, have arisen. In addition, with the appearance of the open Android operating system, wireless technologies are being developed faster than ever. This Project approaches the design and development of a system that combines the technologies of wireless, location and Android with the implementation of an indoor positioning system. As a result, an Android application has been obtained, which detects the position of a phone in a simple and useful way. The application is based on the WIFI manager API of Android. It combines the data stored in a SQL database with the wifi data received at any given time. Afterwards the position of the user is determined with the algorithm that has been implemented. This application is able to obtain the position of any person who is inside a building with Wi-Fi coverage, and display it on the screen of any device with the Android operating system. Besides the estimation of the position, this system displays a map that helps you see in which quadrant of the room are positioned in real time. This system has been designed with a simple interface to allow people without technology knowledge. Finally, several tests and simulations of the system have been carried out to see its operation and accuracy. The performance of the system has been verified in two different places and changes have been made in the Java code to improve its precision and effectiveness. As a result of the several tests, it has been noticed that the placement of the access point (AP) and the configuration of the Wireless network is an important point that should be taken into account to avoid interferences and errors as much as possible, in the estimation of the position. RESUMEN. En los últimos años, se ha producido un incremento en el desarrollo de tecnologías inalámbricas y en servicios de localización y posicionamiento. Por esta razón, han surgido numerosos proyectos relacionados con estas tecnologías. Por otra parte, un punto importante en el desarrollo de estas tecnologías ha sido la aparición del lenguaje Android que ha hecho que estas nuevas tecnologías se implementaran con una mayor rapidez. Este proyecto, se acerca al diseño y desarrollo de un sistema que combina tecnologías inalámbricas, de ubicación y uso de lenguaje Android para el desarrollo de una aplicación de un sistema de posicionamiento en interiores. Como consecuencia de esto se ha obtenido una aplicación Android que detecta la posición de un dispositivo móvil de una manera sencilla e intuititva. La aplicación se basa en la API WIFI de Android, que combina los datos almacenados en una base de datos SQL con los datos recibidos vía Wi-Fi en cualquier momento. A continuación, la posición del usuario se determina con el algoritmo que se ha implementado a lo largo de todo el proyecto utilizando código Android. Esta aplicación es capaz de obtener la posición de cualquier persona que se encuentra dentro de un edificio con cobertura Wi-Fi, mostrando por pantalla la ubicación del usuario en cualquier dispositivo que disponga de sistema operativo Android. Además de la estimación de la posición, este sistema muestra un mapa que le ayuda a ver en qué cuadrante de la sala está situado el usuario. Este sistema ha sido diseñado con una interfaz sencilla para permitir que usuarios sin conocimiento tecnológico o no acostumbrados al uso de los nuevos dispositivos de hoy en día puedan usarlo de una manera sencilla y de forma intuitiva. Por último, se han llevado a cabo varias pruebas y simulaciones del sistema para verificar su funcionamiento y precisión. El rendimiento del sistema se ha comprobado en dos puntos diferentes de la sala (lugar donde se han hecho todas las pruebas y desarrollado la aplicación) realizando cambios en el código Java para mejorar aún más la precisión y eficacia del posicionamiento. Como resultado de todo esto, se ha comprobado que la ubicación del punto de acceso (AP) y la configuración de la red inalámbrica es importante, y por ello se debe de tener en cuenta para evitar interferencias y tantos errores como sea posible en la estimación de la posición.

Indoor positioning system for mobile devices using radio frequency and perfect sequences

Recent advancements in the area of nanotechnology have brought us into a new age of pervasive computing devices. These computing devices grow ever smaller and are being used in ways which were unimaginable before. Recent interest in developing a precise indoor positioning system, as opposed to existing outdoor systems, has given way to much research heading into the area. The use of these small computing devices offers many conveniences for usage in indoor positioning systems. This thesis will deal with using small computing devices Raspberry Pi’s to enable and improve position estimation of mobile devices within closed spaces. The newly patented Orthogonal Perfect DFT Golay coding sequences will be used inside this scenario, and their positioning properties will be tested. After that, testing and comparisons with other coding sequences will be done.

A Beacon based Localization System for Autonomous Mobile Robots and its Applications in Traffic and Transport Control

ACCURATE sensing of vehicle position and attitude is still a very challenging problem in many mobile robot applications. The mobile robot vehicle applications must have some means of estimating where they are and in which direction they are heading. Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines-of-sight or do not provide absolute, driftfree measurements.The research work presented in this dissertation provides a new approach to position and attitude sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building, hospital, industrial or warehouse. This is accomplished by an innovative assembly of infrared LED source that restricts the spreading of the light intensity distribution confined to a sheet of light and is encoded with localization and traffic information. This Digital Infrared Sheet of Light Beacon (DISLiB) developed for mobile robot is a high resolution absolute localization system which is simple, fast, accurate and robust, without much of computational burden or significant processing. Most of the available beacon's performance in corridors and narrow passages are not satisfactory, whereas the performance of DISLiB is very encouraging in such situations. This research overcomes most of the inherent limitations of existing systems.The work further examines the odometric localization errors caused by over count readings of an optical encoder based odometric system in a mobile robot due to wheel-slippage and terrain irregularities. A simple and efficient method is investigated and realized using an FPGA for reducing the errors. The detection and correction is based on redundant encoder measurements. The method suggested relies on the fact that the wheel slippage or terrain irregularities cause more count readings from the encoder than what corresponds to the actual distance travelled by the vehicle.The application of encoded Digital Infrared Sheet of Light Beacon (DISLiB) system can be extended to intelligent control of the public transportation system. The system is capable of receiving traffic status input through a GSM (Global System Mobile) modem. The vehicles have infrared receivers and processors capable of decoding the information, and generating the audio and video messages to assist the driver. The thesis further examines the usefulness of the technique to assist the movement of differently-able (blind) persons in indoor or outdoor premises of his residence.The work addressed in this thesis suggests a new way forward in the development of autonomous robotics and guidance systems. However, this work can be easily extended to many other challenging domains, as well.

Experimental Comparison of Bluetooth and WiFi Signal Propagation for Indoor Localisation

Systems for indoor positioning using radio technologies are largely studied due to their convenience and the market opportunities they offer. The positioning algorithms typically derive geographic coordinates from observed radio signals and hence good understanding of the indoor radio channel is required. In this paper we investigate several factors that affect signal propagation indoors for both Bluetooth and WiFi. Our goal is to investigate which factors can be disregarded and which should be considered in the development of a positioning algorithm. Our results show that technical factors such as device characteristics have smaller impact on the signal than multipath propagation. Moreover, we show that propagation conditions differ in each direction. We also noticed that WiFi and Bluetooth, despite operating in the same radio band, do not at all times exhibit the same behaviour.

SDR-based Passive Indoor Localization System for GSM

This study deals with indoor positioning using GSM radio, which has the distinct advantage of wide coverage over other wireless technologies. In particular, we focus on passive localization systems that are able to achieve high localization accuracy without any prior knowledge of the indoor environment or the tracking device radio settings. In order to overcome these challenges, newly proposed localization algorithms based on the exploitation of the received signal strength (RSS) are proposed. We explore the effects of non-line-of-sight communication links, opening and closing of doors, and human mobility on RSS measurements and localization accuracy. We have implemented the proposed algorithms on top of software defined radio systems and carried out detailed empirical indoor experiments. The performance results show that the proposed solutions are accurate with average localization errors between 2.4 and 3.2 meters.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Utilizzo di sensori a basso costo per la localizzazione indoor

I sistemi di localizzazione, negli ultimi anni, sono stati oggetto di numerose ricerche a livello internazionale.Gli sviluppi più importanti hanno avuto inizio nell’ambito stradale con sistemi di navigazione e localizzazione, possibili grazie alle forti capacità del GPS.Infatti il GPS indica l’intero apparato che permette il funzionamento della maggior parte dei navigatori disponibili in commercio, che, però, non sono utilizzabili in ambito indoor, in quanto la ricezione del segnale proveniente dai satelliti GPS diventa scarsa o pressoché nulla. In questo senso, la localizzazione risulta rilevante nel caso di indoor positioning, ossia quando utenti hanno bisogno di conoscere la propria posizione e quella degli altri membri della squadra di soccorso all’interno di un edificio come, ad esempio, i vigili del fuoco durante un’operazione di salvataggio. Sono questi fattori che portano all’idea della creazione di un sistema di localizzazione indoor basato su smartphone o una qualsiasi altra piattaforma disponibile. Tra le diverse tecnologie e architetture legate al posizionamento indoor/outdoor e inerziale, con questa tesi, si vuole esporre la foot-mounted inertial navigation, un sistema che permette di conoscere la propria posizione, sia all’interno di edifici,sia in campi aperti, tramite l’utilizzo di una rete wireless o GPS e l’aiuto di sensori a basso costo.Tuttavia per conoscere la stima ottimale della posizione, della velocità e dell’orientamento corrente di un utente dotato di sensori sarà necessaria l’integrazione di diversi algoritmi, che permettono di modellare e stimare errori o di conoscere e predire la posizione futura dello stesso. Gli scopi principali di questo lavoro sono: 1)Tracciare i movimenti di un utente usando diversi sensori per ottenere una stima ottimale della posizione dello stesso; 2)Localizzare l’utente in 3 dimensioni con precisione; 3)Ottenere una transizione senza interruzioni per un posizionamento continuo tra aree indoor e outdoor;

Real-time locating systems applications in construction

Real-time locating systems (RTLSs) are considered an effective way to identify and track the location of an object in both indoor and outdoor environments. Various RTLSs have been developed and made commercially available in recent years. Research into RTLSs in the construction sector is ubiquitous and results have been published in many construction-related academic journals over the past decade. A succinct and systematic review of current applications would help academics, researchers and industry practitioners in identifying existing research deficiencies and therefore future research directions. However, such a review is lacking to date. This paper provides a framework for understanding RTLS research and development in the construction literature over the last decade. The research opportunities and directions of construction RTLS are highlighted. Background information relating to construction RTLS trends, accuracy, deployment, cost, purposes, advantages and limitations is provided. Four major research gaps are identified and research opportunities and directions are highlighted.