scholarly journals SLAM-based Indoor Navigation in University Buildings

2021 ◽  
Author(s):  
Ekaterina Sukhareva ◽  
Tatiana Tomchinskaya ◽  
Ilya Serov
Keyword(s):  
Augmented Reality ◽  
Indoor Navigation ◽  
Positioning System ◽  
Navigation Systems ◽  
Mobile Platforms ◽  
Localization And Mapping ◽  
Mapping Technology ◽  
Augmented Reality Technology ◽  
University Buildings ◽  
Indoor Positioning System

The article discusses the use of SLAM (simultaneous localization and mapping) technology, with the help of which it is possible to build Indoor navigation systems using augmented reality technology, including on mobile platforms. The article also provides an overview of the positive and negative aspects of the SLAM technology its principle of operation for positioning a navigator using augmented reality in a university building within the framework of a student project are reviewed. The already implemented projects on similar topics, but using other technologies are considered their features are described. An example of the implementation of an indoor positioning system in a university using SLAM is given.

scholarly journals A Robust Artificial Intelligence: Smart Indoor Positioning System

2019 ◽  
Vol 8 (10) ◽  
pp. 1393-1398 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Human Life ◽  
Indoor Navigation ◽  
Cloud Services ◽  
Raspberry Pi ◽  
Positioning System ◽  
Navigation Systems ◽  
Computing Power ◽  
The Voice ◽  
Indoor Positioning System

Over the previous few centuries, technology has converted massively from being a desktop personal computer to handheld mobile phones, with lower energy consumption of raw computing power. This computability is now incorporated with other systems as well as isolated to a single device. This paradigm was first noted in cyber-physical systems with the introduction of cloud services. The evolution of Artificial Intelligence(AI) with cloud computing and the importance of this field in human life, induce us to make simple and efficient talkative assistant robot for indoor navigation. The navigation system in outdoor typically rely upon Global Positioning System (GPS) but the indoor navigation systems have to rely on different technologies, as GPS signals cannot be received indoors. Thus, several technologies have been proposed and implemented over the past decade to improve navigation in indoors. But they were costly and less effective. Therefore, we have proposed a system that assists humans to find their location in a conversational manner. The suggested system was constructed by introducing the advantages of a personal assistant device, Amazon Alexa, the cloud services of Amazon and its voice services for indoor navigation. A Raspberry Pi 3 Model B is used as the element of the hardware to provide our system with intelligent characteristics. You can trigger the speech service using the "Alexa" keyword. Using the voice command, the skill / application we created can be initiated. It operates a script on the cloud once Alexa is enabled, which runs a subroutine on the Raspberry Pi 3 in-turn to provide a path for that specific place. Once the Raspberry Pi calculation is finished, it sends the message back to Alexa. Alexa transforms the text into a voice and informs the user path.

scholarly journals INDOOR NAVIGATION AND MAPPING: PERFORMANCE ANALYSIS OF UWB-BASED PLATFORM POSITIONING

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 549-555
Author(s):  
A. Masiero ◽  
H. Perakis ◽  
J. Gabela ◽  
C. Toth ◽  
V. Gikas ◽  
...  
Keyword(s):  
Wide Band ◽  
Indoor Navigation ◽  
Operating Conditions ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Localization And Mapping ◽  
Wide Range ◽  
Increasing Demand ◽  
Slam Algorithm ◽  
Tof Camera

Abstract. The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.

On-Board car diagnostics

2021 ◽  
pp. 09-16
Author(s):  
Keyword(s):  
Augmented Reality ◽  
Control Systems ◽  
Global Positioning System ◽  
Technical Condition ◽  
Positioning System ◽  
Global Positioning Systems ◽  
Positioning Systems ◽  
Global Positioning ◽  
History Of ◽  
Augmented Reality Technology

The article deals with the history of the development of automotive on-Board control systems since the late 60s of the last century to the present time, the assessment of their effectiveness. The perspective directions of development of onboard systems of control of a technical condition with use of global positioning systems GLONASS and GPS, the technology of "augmented reality" are described. Keywords diagnostics, OBD, KAN Protocol, global positioning system GLONASS and GPS, "augmented reality" technology

scholarly journals Unsupervised Indoor Positioning System Based on Environmental Signatures

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 327
Author(s):  
Pan Feng ◽  
Danyang Qin ◽  
Min Zhao ◽  
Ruolin Guo ◽  
Teklu Berhane
Keyword(s):  
Dead Reckoning ◽  
Indoor Positioning ◽  
Convergence Time ◽  
Positioning System ◽  
Indoor Environments ◽  
Test Results ◽  
Positioning Errors ◽  
Localization And Mapping ◽  
Indoor Positioning System ◽  
Unconventional Method

Mobile sensors are widely used in indoor positioning in recent years, but most methods require cumbersome calibration for precise positioning results, thus the paper proposes a new unsupervised indoor positioning (UIP) without cumbersome calibration. UIP takes advantage of environment features in indoor environments, as some indoor locations have their signatures. UIP considers these signatures as the landmarks, and combines dead reckoning with them in a simultaneous localization and mapping (SLAM) frame to reduce positioning errors and convergence time. The test results prove that the system can achieve accurate indoor positioning, which highlights its prospect as an unconventional method of indoor positioning.

scholarly journals An Indoor Navigation Methodology for Mobile Devices by Integrating Augmented Reality and Semantic Web

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5435
Author(s):  
Jesus Ivan Rubio-Sandoval ◽  
Jose L. Martinez-Rodriguez ◽  
Ivan Lopez-Arevalo ◽  
Ana B. Rios-Alvarado ◽  
Adolfo Josue Rodriguez-Rodriguez ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Semantic Web ◽  
Tracking System ◽  
Contextual Information ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Semantic Web Technologies ◽  
Academic Environments ◽  
Web Technologies ◽  
Time Position

Indoor navigation systems incorporating augmented reality allow users to locate places within buildings and acquire more knowledge about their environment. However, although diverse works have been introduced with varied technologies, infrastructure, and functionalities, a standardization of the procedures for elaborating these systems has not been reached. Moreover, while systems usually handle contextual information of places in proprietary formats, a platform-independent model is desirable, which would encourage its access, updating, and management. This paper proposes a methodology for developing indoor navigation systems based on the integration of Augmented Reality and Semantic Web technologies to present navigation instructions and contextual information about the environment. It comprises four modules to define a spatial model, data management (supported by an ontology), positioning and navigation, and content visualization. A mobile application system was developed for testing the proposal in academic environments, modeling the structure, routes, and places of two buildings from independent institutions. The experiments cover distinct navigation tasks by participants in both scenarios, recording data such as navigation time, position tracking, system functionality, feedback (answering a survey), and a navigation comparison when the system is not used. The results demonstrate the system’s feasibility, where the participants show a positive interest in its functionalities.

scholarly journals An RSSI-Based Localization, Path Planning and Computer Vision-Based Decision Making Robotic System

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1326
Author(s):  
Jatin Upadhyay ◽  
Abhishek Rawat ◽  
Dipankar Deb ◽  
Vlad Muresan ◽  
Mihaela-Ligia Unguresan
Keyword(s):  
Signal Strength ◽  
Indoor Navigation ◽  
Small Scale ◽  
Area Network ◽  
Navigation Systems ◽  
Localization And Mapping ◽  
Mapping System ◽  
Vision Based Localization ◽  
Human Faces ◽  
Robot Position

A robotic navigation system operates flawlessly under an adequate GPS signal range, whereas indoor navigation systems use the simultaneous localization and mapping system or other vision-based localization systems. The sensor used in indoor navigation systems is not suitable for low power and small scale robotic systems. The wireless area network transmitting devices have fixed transmission power, and the receivers get the different values of signal strength based on their surrounding environments. In the proposed method, the received signal strength index (RSSI) values of three fixed transmitter units are measured every 1.6 m in mesh format and analyzed by the classifiers, and robot position can be mapped in the indoor area. After navigation, the robot analyzes objects and detects and recognize human faces with the help of object recognition and facial recognition-based classification methods respectively. This robot detects the intruder with the current position in an indoor environment.

scholarly journals A Hybrid Marker-Based Indoor Positioning System for Pedestrian Tracking in Subway Stations

2020 ◽  
Vol 10 (21) ◽  
pp. 7421
Author(s):  
Gunwoo Lee ◽  
Hyun Kim
Keyword(s):  
Error Correction ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Signal Interference ◽  
Measurement Unit ◽  
Subway Station ◽  
Positioning System ◽  
Correction Technique ◽  
Subway Stations ◽  
Indoor Positioning System

The use of smartphones for accurate navigation in underground spaces, such as subway stations, poses several challenges. This is because it is difficult to obtain a sure estimate of user location due to the radio signal interference caused by the entry and exit of trains, the infrastructure of the subway station installation, and changes in the internal facility environment. This study uses quick response markers and augmented reality to solve these difficulties using an error correction method. Specifically, a hybrid marker-based indoor positioning system (HMIPS) which provides accurate and efficient user-tracking results is proposed. The HMIPS performs hybrid localization by using marker images as well as inertial measurement unit data from smartphones. It utilizes the Viterbi tracking algorithm to solve the problem of tracking accuracy degradation that may occur when inertial sensors are used by adopting a sensor error correction technique. In addition, as an integrated system, the HMIPS provides a tool to easily carry out all the steps necessary for positioning. The results of experiments conducted in a subway station environment confirm that the HMIPS provides accurate and practical navigation services. The proposed system is expected to be useful for indoor navigation, even in poor indoor positioning environments.

Indoor Navigation Using Augmented Reality

2021 ◽  
pp. 588-592
Author(s):  
Satya Kiranmai Tadepalli ◽  
Preethivardhan Anusri Ega ◽  
Pavan Kalyan Inugurthi
Keyword(s):  
Augmented Reality ◽  
Shortest Path ◽  
Indoor Navigation ◽  
Qr Code ◽  
Qr Codes ◽  
A Algorithm ◽  
Live Feed ◽  
Front End ◽  
Localization And Mapping ◽  
Starting Point

This system advice directions to the destination in the user’s camera screen. QR codes shall be installed at all possible destinations in the building assuming any destination can be the starting point of the user. Users must scan a QR code to select a destination. Google AR Core takes live feed from the user's camera and does simultaneous localization and mapping to update the user’s location. Shortest path to the chosen destination is found using A * algorithm and the directions to the destination are shown in the user's camera screen using Augmented Reality. The application is developed in Unity from scratch using some essential plugins like Google ARCore. We aim at developing the front end in the simplest way possible so that the users can easily reach their destination by just opening the camera where the directions are shown as animations in their surroundings.

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