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

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

NASA Thesaurus Supplement: A three part cumulative supplement to the 1982 edition of the NASA Thesaurus (supplement 2)

The three part cumulative NASA Thesaurus Supplement to the 1982 edition of the NASA Thesaurus includes: part 1, hierarchical listing; part 2, access vocabulary, and part 3, deletions. The semiannual supplement gives complete hierarchies for new terms and includes new term indications for terms new to this supplement

Multisensor navigation systems: a remedy for GNSS vulnerabilities?

Space-based positioning, navigation, and timing (PNT) technologies, such as the global navigation satellite systems (GNSS) provide position, velocity, and timing information to an unlimited number of users around the world. In recent years, PNT information has become increasingly critical to the security, safety, and prosperity of the World's population, and is now widely recognized as an essential element of the global information infrastructure. Due to its vulnerabilities and line-of-sight requirements, GNSS alone is unable to provide PNT with the required levels of integrity, accuracy, continuity, and reliability. A multisensor navigation approach offers an effective augmentation in GNSS-challenged environments that holds a promise of delivering robust and resilient PNT. Traditionally, sensors such as inertial measurement units (IMUs), barometers, magnetometers, odometers, and digital compasses, have been used. However, recent trends have largely focused on image-based, terrain-based and collaborative navigation to recover the user location. This paper offers a review of the technological advances that have taken place in PNT over the last two decades, and discusses various hybridizations of multisensory systems, building upon the fundamental GNSS/IMU integration. The most important conclusion of this study is that in order to meet the challenging goals of delivering continuous, accurate and robust PNT to the ever-growing numbers of users, the hybridization of a suite of different PNT solutions is required

Indoor location based services challenges, requirements and usability of current solutions

Indoor Location Based Services (LBS), such as indoor navigation and tracking, still have to deal with both technical and non-technical challenges. For this reason, they have not yet found a prominent position in people’s everyday lives. Reliability and availability of indoor positioning technologies, the availability of up-to-date indoor maps, and privacy concerns associated with location data are some of the biggest challenges to their development. If these challenges were solved, or at least minimized, there would be more penetration into the user market. This paper studies the requirements of LBS applications, through a survey conducted by the authors, identifies the current challenges of indoor LBS, and reviews the available solutions that address the most important challenge, that of providing seamless indoor/outdoor positioning. The paper also looks at the potential of emerging solutions and the technologies that may help to handle this challenge

NASA Thesaurus Supplement: A three part cumulative supplement to the 1982 edition of the NASA Thesaurus (supplement 3)

The three part cumulative NASA Thesaurus Supplement to the 1982 edition of the NASA Thesaurus includes Part 1, Hierarchical Listing, Part 2, Access Vocabulary, and Part 3, Deletions. The semiannual supplement gives complete hierarchies for new terms and includes new term indications for entries new to this supplement

Information-Aware Guidance for Magnetic Anomaly based Navigation

In the absence of an absolute positioning system, such as GPS, autonomous vehicles are subject to accumulation of positional error which can interfere with reliable performance. Improved navigational accuracy without GPS enables vehicles to achieve a higher degree of autonomy and reliability, both in terms of decision making and safety. This paper details the use of two navigation systems for autonomous agents using magnetic field anomalies to localize themselves within a map; both techniques use the information content in the environment in distinct ways and are aimed at reducing the localization uncertainty. The first method is based on a nonlinear observability metric of the vehicle model, while the second is an information theory based technique which minimizes the expected entropy of the system. These conditions are used to design guidance laws that minimize the localization uncertainty and are verified both in simulation and hardware experiments are presented for the observability approach.Comment: 2022 International Conference on Intelligent Robots and Systems October 23 to 27, 2022 Kyoto, Japa

Dynamic spatial segmentation strategy based magnetic field indoor positioning system

In this day and age, it is imperative for anyone who relies on a mobile device to track and navigate themselves using the Global Positioning System (GPS). Such satellite-based positioning works as intended when in the outdoors, or when the device is able to have unobstructed communication with GPS satellites. Nevertheless, at the same time, GPS signal fades away in indoor environments due to the effects of multi-path components and obstructed line-of-sight to the satellite. Therefore, numerous indoor localisation applications have emerged in the market, geared towards finding a practical solution to satisfy the need for accuracy and efficiency. The case of Indoor Positioning System (IPS) is promoted by recent smart devices, which have evolved into a multimedia device with various sensors and optimised connectivity. By sensing the device’s surroundings and inferring its context, current IPS technology has proven its ability to provide stable and reliable indoor localisation information. However, such a system is usually dependent on a high-density of infrastructure that requires expensive installations (e.g. Wi-Fi-based IPS). To make a trade-off between accuracy and cost, considerable attention from many researchers has been paid to the range of infrastructure-free technologies, particularly exploiting the earth’s magnetic field (EMF). EMF is a promising signal type that features ubiquitous availability, location specificity and long-term stability. When considering the practicality of this typical signal in IPS, such a system only consists of mobile device and the EMF signal. To fully comprehend the conventional EMF-based IPS reported in the literature, a preliminary experimental study on indoor EMF characteristics was carried out at the beginning of this research. The results revealed that the positioning performance decreased when the presence of magnetic disturbance sources was lowered to a minimum. In response to this finding, a new concept of spatial segmentation is devised in this research based on magnetic anomaly (MA). Therefore, this study focuses on developing innovative techniques based on spatial segmentation strategy and machine learning algorithms for effective indoor localisation using EMF. In this thesis, four closely correlated components in the proposed system are included: (i) Kriging interpolation-based fingerprinting map; (ii) magnetic intensity-based spatial segmentation; (iii) weighted Naïve Bayes classification (WNBC); (iv) fused features-based k-Nearest-Neighbours (kNN) algorithm. Kriging interpolation-based fingerprinting map reconstructs the original observed EMF positioning database in the calibration phase by interpolating predicted points. The magnetic intensity-based spatial segmentation component then investigates the variation tendency of ambient EMF signals in the new database to analyse the distribution of magnetic disturbance sources, and accordingly, segmenting the test site. Then, WNBC blends the exclusive characteristics of indoor EMF into original Naïve Bayes Classification (NBC) to enable a more accurate and efficient segmentation approach. It is well known that the best IPS implementation often exerts the use of multiple positing sources in order to maximise accuracy. The fused features-based kNN component used in the positioning phase finally learns the various parameters collected in the calibration phase, continuously improving the positioning accuracy of the system. The proposed system was evaluated on multiple indoor sites with diverse layouts. The results show that it outperforms state-of-the-art approaches and demonstrate an average accuracy between 1-2 meters achieved in typical sites by the best methods proposed in this thesis across most of the experimental environments. It can be believed that such an accurate approach will enable the future of infrastructure–free IPS technologies