Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot

iNav Indoor Positioning and Navigation System

Getting a pin-point accurate location is a difficult task and prone to many errors, thus providing a wrong location. Existing GPS Based Location service has proved to be moderately reliable, but it is not the same when considering indoor wise location. Getting an indoor location inside a building is harder than ever since due the signal barriers and narrow range. In this article a system for Indoor Positioning and Navigating with customized maps is presented. This will make the users to get to know the location very quickly and easily. It will be more applicable for the Government Departments where it is difficult to find a proper location. The RSSI of the wireless access points will be used to triangulate the location

Indoor positioning and navigation, part III: navigation systems

In the age of automation the ability to navigate persons and devices in indoor environments has become increasingly important for a rising number of applications. With the emergence of global satellite positioning systems, the performance of outdoor navigation has become excellent, but many mass market applications require seamless navigation capabilities in all environments. Therefore indoor navigation has become a focus of research and development during the past decade. It has by now become apparent that there is no overall solution based on a single technology, such as that provided outdoors by satellite-based navigation

MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum

In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application

AmIE: An Ambient Intelligent Environment for Assisted Living

In the modern world of technology Internet-of-things (IoT) systems strives to provide an extensive interconnected and automated solutions for almost every life aspect. This paper proposes an IoT context-aware system to present an Ambient Intelligence (AmI) environment; such as an apartment, house, or a building; to assist blind, visually-impaired, and elderly people. The proposed system aims at providing an easy-to-utilize voice-controlled system to locate, navigate and assist users indoors. The main purpose of the system is to provide indoor positioning, assisted navigation, outside weather information, room temperature, people availability, phone calls and emergency evacuation when needed. The system enhances the user's awareness of the surrounding environment by feeding them with relevant information through a wearable device to assist them. In addition, the system is voice-controlled in both English and Arabic languages and the information are displayed as audio messages in both languages. The system design, implementation, and evaluation consider the constraints in common types of premises in Kuwait and in challenges, such as the training needed by the users. This paper presents cost-effective implementation options by the adoption of a Raspberry Pi microcomputer, Bluetooth Low Energy devices and an Android smart watch.Comment: 6 pages, 8 figures, 1 tabl

Intelligent Indoor Parking

Nowadays positioning based navigation is an integrated part of our everyday’s routine. Hence, it is hard to succeed without a GPS based navigation system in a bigger city today. However, indoor positioning and navigation are still in their infancy, although these services would be desirable in many areas. One obvious application domain is vehicle navigation in a parking garage. The use of an indoor vehicle navigation system is convenient for the drivers, decreases the unnecessary circling in the garage and reduces air pollution. In this paper, we introduce our iParking indoor positioning and navigation system which has been under development. Our system monitors the occupancy of the parking lots, and with the aid of a Wi-Fi based background wireless infrastructure tracks the position of the vehicle entering the parking garage and navigates the driver to an appropriate free parking lot. Lot selection is handled at the entry point of the garage based on simple preferences, eg., the closest disabled parking space. The navigation interface is the driver’s smartphone. Currently, we have been implementing a prototype of our iParking system in a parking garage of a shopping mall for demonstration purposes

Indoor Positioning and Navigation by Semantic Localization Based on Visual Context

Conventional indoor localization techniques rely on high-precision indoor 3/6 degrees-of-freedom (DOF) positioning of the user device which may be infeasible if the device lacks positioning sensors such as GPS or IMU, if such sensors are turned off, or if the sensors have insufficient accuracy. This disclosure describes techniques the use of language modeling techniques for providing indoor navigation capabilities in the absence of such sensor data based on the local visual context obtained with a camera. Text captions describing frames of the user’s visual context in an indoor space are generated. A collection of captions for the current and recently captured, timestamped frames of the visual context, and a suitable prompt and metadata are input to a large language model to determine the current location of the user within the indoor space. The techniques can be incorporated within any indoor digital mapping and navigation application via any device capable of capturing the visual context via a camera

Modeling and interpolation of the ambient magnetic field by Gaussian processes

Anomalies in the ambient magnetic field can be used as features in indoor positioning and navigation. By using Maxwell's equations, we derive and present a Bayesian non-parametric probabilistic modeling approach for interpolation and extrapolation of the magnetic field. We model the magnetic field components jointly by imposing a Gaussian process (GP) prior on the latent scalar potential of the magnetic field. By rewriting the GP model in terms of a Hilbert space representation, we circumvent the computational pitfalls associated with GP modeling and provide a computationally efficient and physically justified modeling tool for the ambient magnetic field. The model allows for sequential updating of the estimate and time-dependent changes in the magnetic field. The model is shown to work well in practice in different applications: we demonstrate mapping of the magnetic field both with an inexpensive Raspberry Pi powered robot and on foot using a standard smartphone.Comment: 17 pages, 12 figures, to appear in IEEE Transactions on Robotic

UAV-Enabled 3D Indoor Positioning and Navigation Based on VLC

International audienceThe 3D indoor positioning and indoor navigation (IPIN) system is of great significance for promoting and ex- panding indoor intelligent services and applications. The rapid development of unmanned aerial vehicles (UAVs) has provided new opportunities in this field. However, in contrast to their outdoor applications, IPIN for UAVs is more challenging since the Global Positioning System (GPS) is in general inaccessible in indoor environments. In this work, we propose a UAV-enabled 3D IPIN system based on visible light communication (VLC). Firstly, a novel VLC-based indoor positioning scheme is developed using a fusion algorithm based on the dynamic time warping (DTW) method with visible light intensity sequence (VLIS) and inertial measurement unit (IMU) data. To reduce the workload of fingerprint measurements, we propose to modularize a floor site using a standard symmetric structure for VLC positioning. In this manner, the navigation can be achieved by recognizing the edge of each module. Furthermore, since the sampling frequency of IMU is much higher than that of VLIS, discrete Kalman filter (KF) is introduced to correct the location measured by IMU when VLIS is unavailable. A proof-of-concept IPIN prototype is constructed. Field experiments confirm the effectiveness of our proposed IPIN system