Indoor navigation systems are increasingly needed for smart cities, robots, and visually impaired people. Although Global Positioning System (GPS) is widely used for navigation in numerous applications, it cannot be used for indoor navigation systems as the signals cannot be absorbed by the walls of buildings. As a result, other methods including Wi-Fi, Bluetooth and sensors must be used for navigation. This paper analyses the various algorithms used to find the location of objects and algorithms to navigate using the shortest path in an indoor environment. The first section introduces indoor navigation systems, the problem statement of this paper, and the background of such systems. Then, a comprehensive literature review is included that reviews previous research studies conducted in this area. After that, a discussion and analysis of the literature review has been done to classify and compare between the algorithms and techniques studied. Finally, the paper provides directions for future work in the field of indoor navigation.

Survey on Algorithms and Techniques for Indoor Navigation Systems.

In this chapter, we focus on presenting some of the artificial intelligence techniques. Among these techniques, we use support vector machine (SVM) method, the adaptive support vector machine (ASVM), k-nearest neighbor (KNN), and naive Bayes (NB).

Machine Learning Techniques for Data Classification

Herein, we propose a novel indoor structure extraction (ISE) method that can reconstruct an indoor planar structure with a feature structure map (FSM) and enable indoor robot navigation using a navigation structure map (NSM). To construct the FSM, we first propose a two-staged region growing algorithm to segment the planar feature and to obtain the original planar point cloud. Subsequently, we simplify the planar feature using quadtree segmentation based on cluster fusion. Finally, we perform simple triangulation in the interior and vertex-assignment triangulation in the boundary to accomplish feature reconstruction for the planar structure. The FSM is organized in the form of a mesh model. To construct the NSM, we first propose a novel ground extraction method based on indoor structure analysis under the Manhattan world assumption. It can accurately capture the ground plane in an indoor scene. Subsequently, we establish a passable area map (PAM) within different heights. Finally, a novel-form NSM is established using the original planar point cloud and the PAM. Experiments are performed using three public datasets and one self-collected dataset. The proposed plane segmentation approach is evaluated on two simulation datasets and achieves a recall of approximately 99%, which is 5% higher than that of the traditional plane segmentation method. Furthermore, the triangulation performance of our method compared with the traditional greedy projection triangulation show that our method performs better in terms of feature representation. The experimental results reveal that our ISE method is robust and effective for extracting indoor structures.

A Novel Indoor Structure Extraction Based on Dense Point Cloud

In this paper, we elicit a cost-effective design of a robot that is used to perform the tasks of the attender, a wheeled mobile robot. The two main challenging aspects of mobile robotics are to achieve localization and navigation. Localization determines the location of the robot with respect to its environment. Navigation is the movement of the robot from one location to the other. Here, the unique design and representation of the QR code helped us to localize and navigate the robot. A raspberry pi mounted with a camera is used to interface with the robot. The triangulation method is used to localize the robot. Dijkstra’s algorithm is used to compute the shortest path from source to destination. The system is monitored tested based on the feedback system established by the Hologram cellular USB modem. Experimental results show that this approach has good feasibility and effectiveness. The robot navigates through the shortest path, performs specified tasks, and returns to its source.

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QR Code based Indoor Navigation system for Attender Robot

Smart indoor navigation and proximity advertising with android application using BLE technology

Real-time user positioning and navigation services are widely used daily by millions of people. The challenge is that common global positioning systems fail in indoor environment or in scenes with a limited sky view. In the paper, the indoor navigation framework based on the Bluetooth beacons is proposed. Such system allows user to obtain the position in GPS denied environment on a real-time basis. Key steps for precise localizing and main components of the developed framework are considered. Initial experimental results are provided.

Real-time system for indoor user localization and navigation using bluetooth beacons

In the paper, we describe technical details of multi-player sports tracker system. We demonstrate that proper in-depth analysis of video frames sequence may provide a lot of useful information required for sports analytics. Object detection and tracking steps are analyzed. Novel ideas for efficient filtering of false detections and irrelevant tracks are proposed. Also, we show an example of how the object tracking information used for the regions of interest location allows streaming sports events without human operators. At last, important practical implementation details, as well as initial experimental results, are discussed.

Light-Weight Tracker for Sports Applications

3D mapping techniques have a large variety of applications from entertainment to military and medical fields. However, there is a big challenge of obtaining well refined 3D model from a set of images without usage of depth sensors. In the paper, we analyze main components of 3D reconstruction pipeline allowing to get detailed models of outdoor objects from drones. In particular, we experiment with algorithms required for structure from motion and point cloud densification. It is demonstrated, that proper local feature extraction, matching and verification directly effect on a final model quality. Analysis of two existing 3D reconstruction frameworks (MVE and COLMAP) is conducted. Initial experimental results are shown.

Outdoor Mapping Framework: from Images to 3D Model

The paper presents basic concepts of augmented reality applications and challenges in building them in the web. We describe the technical and algorithmic stack required to develop, implement and deploy the augmented reality application. Theoretical concepts behind marker detection and tracking are discussed. Two different pipelines are implemented: server-based with algorithms execution in the cloud and completely front-end solution that runs on a user device. We show advantages and disadvantages of each approach and analyze experimental results as well.

Augmented Reality in Web: Results and Challenges

In the paper, a system for real-time positioning is proposed Developed signal processing algorithms for precise user localization and navigation are described It is demonstrated that proper calibration and received signal filtering leads to improvement of positioning accuracy Peculiarities of Bluetooth Low Energy beacons as signal sources are considered Key components of the created software development kit are described Experimental results of testing on mobile platforms are given

Ievgen Gorovyi

Papers

Real-time system for indoor user localization and navigation using bluetooth beacons

Light-Weight Tracker for Sports Applications

Outdoor Mapping Framework: from Images to 3D Model

Augmented Reality in Web: Results and Challenges

Framework for real-time user positioning in GPS denied environments