Indoor pedestrian navigation systems

Indoor pedestrian navigation systems have become indispensable in modern times, facilitating efficient navigation through complex indoor environments such as malls and airports. Traditional GPS technology falls short in these settings due to signal blockage and reflections, leading to the emergence of indoor positioning systems (IPS). Leveraging technologies like Bluetooth beacons, Wi-Fi triangulation, and ultra-wideband signals, IPS provides precise real-time navigation within buildings. Augmented reality (AR) and virtual reality (VR) further enhance the indoor navigation experience, offering visual cues and pre-navigation simulations. Despite challenges such as precise mapping and signal interference, the adoption of indoor navigation technologies has increased, driven by the demand for better user experiences. This abstract explores the methods, technologies, and challenges associated with indoor pedestrian navigation, providing insights into current trends and future developments.

This paper introduces a new sensor fusion approach for using multiple MEMS sensor-based pedestrian navigation systems (PNSs) to enhance the performance of each individual navigation system. First, we propose a novel single IMU-based PNS which integrates both the inertial navigation system (INS) mechanization and the pedestrian dead reckoning (PDR) mechanization. When two identical PNSs are used by a user at the same time, the output of each PNS is then shared within a Kalman filter (KF) with the state-constrained approach, which, in turn, feeds the state error correction information back to each PNS. Several real experiments are done to assess the proposed methodology for the integration of multiple PNSs. The experimental studies clearly indicate that through applying the proposed state-constrained approach, using motion sensor data from multiple mobile/wearable devices could provide more accurate navigation information for a pedestrian in all indoor and outdoor environments.

With the rapid development of computer technology and communication technology, pedestrian navigation system(PNS) began to enter the real practical stage. PNS is a method of track reckoning based on strapdown inertial navigation system. However, inertial navigation system is prone to error accumulation with time, resulting in low positioning accuracy and practicability. Low cost inertial measurement unit(IMU) device has low accuracy, and the inertial navigation system has accumulated error, and the system is easy to diverge. Apart from those above, civil GPS accuracy is not stable, and poor GPS signal in a multipath environment may lead to errors, and GPS signals can not be used indoors. It is necessary to design a kind of navigation method to adapt low cost IMU. In this paper, it is presented that a foot inertial navigation system which is based on low cost MEMS inertial sensors is presented. According to the characteristics of pedestrian zero-velocity during walking steady state, an inertial navigation method based on Zero Velocity Update (ZUPT) is adopted. This paper uses air pressure, GPS to assist ZUPT method to correcting navigation parameters through Kalman filter. Based on the implementation scheme of pedestrian navigation system proposed in this paper, the steady state of walking were experimentally verified through the actual test data. The experimental results show that the proposed method can provide efficient, reliable and continuous position and navigation services.

With the advanced capabilities of mobile devices and the success of car navigation systems, interest in pedestrian navigation systems is on the rise. A critical component of any navigation system is a map database, which represents a network (e.g., road networks for car navigation) and supports key functionality such as map display, geocoding, and routing. Road networks, mainly due to the popularity of car navigation systems, are well defined and publicly available. However, in pedestrian navigation systems, as well as other applications including urban planning and physical activity studies, road networks do not adequately represent the paths that pedestrians usually travel. Currently, there is a void in literatures discussing the challenges, methods, and best practices for pedestrian network map generation. This coupled with the increased demand for pedestrian networks is the prime motivation for development of new approaches and algorithms to automatically generating pedestrian networks. Three approaches, network buffering, using existing road networks, collaborative mapping, using Global Positioning System (GPS) traces collected by volunteers, and image processing, using high-resolution satellite and laser imageries, were implemented and evaluated with a pedestrian network baseline as a ground truth. The results of the experiments indicate that these three approaches, while differing in complexity and outcome, are viable for automatic pedestrian network map generation. The recommendation of a suitable approach for generating pedestrian networks for a given set of sources and requirements is provided.

In order to reduce the dependence of pedestrian navigation on satellite navigation system and wireless communication, a method is studied to construct pedestrian navigation system based on micro inertial technology and human biological kinematics. In the study, the distributed system structure is arranged on human legs instead of feet, and the key technologies, including conception of virtual inertial sensor, initial alignment and error correction, precise gait-phase detection, effect and inhibition of environmental magnetic field are presented. A detailed analysis of the performance characteristics of the pedestrian navigation system is carried out in the environment with or without electromagnetic interference. Experimental results show that, the prototype of virtual inertial sensors works functionally, and the position error with electromagnetic interference accounts for 2.5% of the walking distance. The key technologies proposed in the study can effectively improve the positioning accuracy of pedestrian navigation system, and independently achieve longer time personal navigation in the GNSS and Wireless communication attenuation or invalid environment.

From the precise location data calculated from satellite signals, Global Positioning System makes itself the effective navigation system in the mobile devices yet the cost of which being the higher energy consumption. Being the energy constrained device, the mobile devices thus need the alternative energy efficient navigation system. The pedometer that counts the foot steps taken by the pedestrian, thereby calculating the average distance covered, when integrated with the device's orientation during locomotion, can pave the way for the pedestrian's navigation system. By increasing the efficiency of pedometer using gait analysis and by taking step vectors rather than simply steps, the effective navigation system for pedestrians can be provided. And, this project aims at such energy efficient less GPS dependent navigation system for pedestrians using the mobile sensors-Accelerometer, Magnetometer and Gyroscope for gait analysis and finding orientation.

This paper describes construction of the M-CubITS pedestrian WYSIWYAS navigation system both in outdoor and indoor areas, toward realization of the M-CubITS pedestrian WYSIWYAS navigation environment. In outdoor navigation, we construct the experimental Saitama University campus outdoor navigation system "CamNavi" using ordinary mobile phone terminals as users' terminals and the i-application platform provided by Japanese NTT DoCoMo. Here, our studies on the outdoor system are mainly based on image processing for outdoor M-CubITS elements and a user interface for the mobile phone terminals. On the other hand, in indoor navigation, we also introduce the route guidance using the Dijkstra method and study databases. Then, we construct an experimental system at the seven-storied buildings in the faculty of engineering, Saitama University, and check the system operation

It is extremely difficult for visually impaired people to walk in strange places, because it is extremely challenging for them to know where they are, the direction in which to move, and the destination. Pedestrian navigation systems such as Google Maps have become popular as a result of the evolution and popularization of smartphones and portable tablet devices. However, it is difficult for visually impaired people to use such systems, because almost all of these are developed for healthy persons. In our research, therefore, we have developed a navigation system for visually impaired people. In order to adapt to dynamic or transient environmental changes, such as temporary obstacles, the system makes use of a small wearable camera to estimate the user's position and construct a 3D environmental map. We applied large-scale direct monocular simultaneous localization and mapping (LSD-SLAM) to develop the system, one of the Visual SLAM techniques, to our system. In this paper, we introduce our approach and system construction, and describe the results of a partial demonstration of its functions.

In recent years, the demand for location based service has promoted the rapid development of pedestrian navigation and positioning technology. Among them, Pedestrian Dead Reckoning (PDR) based on inertial sensor can greatly improve the robustness of indoor and outdoor pedestrian navigation system due to its environment-friendly. This paper designs a robust PDR algorithm based on smart phone. This paper constructs multi-level constraints based on INS algorithm and establishing observation equation needed by EKF using the mutually complementary relationship among sensors, such as gyroscope accelerometer and magnetometer, and human dynamic model. The cumulative error of the system is less than 2% of the traveling distance when using different intelligent terminals, holding on hand both in indoor and outdoor test.

The fast transfer rates via UMTS and their corresponding high-tech devices provide the opportunity to develop easily accessible Location Based Services, which can be utilised to guide pedestrians in unfamiliar environments. With the help of cartographic multimedia data navigation systems can be responsive to the needs of pedestrians by presenting information in the preferred forms. In order to facilitate ongoing tasks, not only the presentation forms themselves are decisive, but also their combination and deliberate design is a crucial factor for usability. Moreover landmarks are an important enhancement for pedestrian navigation systems, yet their immense diversity makes it difficult to effectively include them in guiding instructions. For that reason this paper discusses the use of active and passive landmarks, as well as multimedia presentation forms and general design goals for a combined indoor/outdoor pedestrian navigation service.

Most portable systems like smart-phones are equipped with low cost consumer grade sensors, making them useful as Pedestrian Navigation Systems (PNS). Measurements of these sensors are severely contaminated by errors caused due to instrumentation and environmental issues rendering the unaided navigation solution with these sensors of limited use. The overall navigation error budget associated with pedestrian navigation can be categorized into position/displacement errors and attitude/orientation errors. Most of the research is conducted for tackling and reducing the displacement errors, which either utilize Pedestrian Dead Reckoning (PDR) or special constraints like Zero velocity UPdaTes (ZUPT) and Zero Angular Rate Updates (ZARU). This article targets the orientation/attitude errors encountered in pedestrian navigation and develops a novel sensor fusion technique to utilize the Earth’s magnetic field, even perturbed, for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that Global Navigation Satellite System (GNSS) navigation is denied. As the Earth’s magnetic field undergoes severe degradations in pedestrian navigation environments, a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. The QSF scheme is then used for generating the desired measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator. Results indicate that the QSF measurements are capable of effectively estimating attitude and gyroscope errors, reducing the overall navigation error budget by over 80% in urban canyon environment.

Today, pedestrian navigation systems for mobile phones use 2-dimensional maps as a navigation media in general. But 3-dimensional maps or scenery images are easier to understand for users than 2-dimensional maps. To use 3-dimensional maps or scenery guidance, the measuring accuracy of user position is essential to understand guidance images. In this paper, we will present a pedestrian navigation system using real scenery photographs as a navigation media, and based on experiments we will report the evaluation result of influence of positioning accuracy on the understandability of navigation. It is shown that 3 meters or less error of positioning is tolerable for pedestrian navigation systems using scenery images.

Pedestrian navigation system has been widely used in many fields. In order to offer navigation information intelligible for pedestrian, we provide navigation sentences to users, which can be easily displayed on cellular phones with small display area. In addition, the navigation sentences can be converted into voice, which is useful for users in some special situations or with visually impairment. Navigation sentences can separately help pedestrians to go to the destination, or can be combined with electronic map to provide more intuitive navigation information. Compared with guidance maps, navigation sentences are easy to transmit and manage. The navigation sentences are described by XML (eXtensible Markup Language) and can be created on the server automatically based on the users’ position and destination. This paper will discuss the structure of the pedestrian navigation system using navigation sentences. The structure and generating process of navigation sentences are also described.

This chapter assesses underlying spatial relations for pedestrian wayfinding by examining navigational directions given in both forms of sketch maps and verbal descriptions. An experiment was conducted to investigate characteristics of navigational directions provided by participants in the form of sketch maps and verbal descriptions. The authors were specifically interested in the landmarks and spatial relationships such as route topology, linear order relation, and relative orientation extracted from the navigational directions. A new ontological approach to sketch and verbal interpretations was adopted for spatial analysis. The results pointed to the advantage of including sketch components into pedestrian navigation systems over solely turn-by-turn instructions. In addition, the results showed the differences between visual and verbal directions, which suggest the necessity of having different levels of directions for giving specific types of navigational instructions.

Efficient shortest path algorithms are of key importance for routing and navigation systems. However, these applications are designed focusing on the requirements of motor vehicles, and therefore, finding paths in pedestrian sections of urban areas is not sufficiently supported. In addition, finding the shortest path is often not adequate for urban sidewalk routes, as users of these applications may also be interested in alternative routes that, although slightly longer, possess other desirable features and properties. According to the literature, the search for alternative routes is carried out mainly using the k-shortest paths (KSP) algorithm which represents an ordered list of all available alternatives. Even though various KSP algorithms have been proposed, to the best of our knowledge, there is no research addressing all issues inherent in a pedestrian navigation system. The purpose of this paper is to present a heuristic algorithm for graph datasets that implements a penalty-based method which, by increasing certain edge weights, effectively searches for the most accessible alternative paths in multi-route cases. To demonstrate how the algorithm works, we present experimental results on finding the most accessible paths in pedestrian sections of the historical center of Thessaloniki city.