scholarly journals An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Md. Shahjalal ◽  
Md. Tanvir Hossan ◽  
Moh. Khalid Hasan ◽  
Mostafa Zaman Chowdhury ◽  
Nam Tuan Le ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Indoor Localization ◽  
Smart Phone ◽  
Image Sensor ◽  
Indoor Navigation ◽  
Mobile Robot Navigation ◽  
Light Emitting ◽  
And Performance ◽  
White Light Emitting Diodes ◽  
Combined Algorithm

Optical camera communication (OCC) exhibits considerable importance nowadays in various indoor camera based services such as smart home and robot-based automation. An android smart phone camera that is mounted on a mobile robot (MR) offers a uniform communication distance when the camera remains at the same level that can reduce the communication error rate. Indoor mobile robot navigation (MRN) is considered to be a promising OCC application in which the white light emitting diodes (LEDs) and an MR camera are used as transmitters and receiver, respectively. Positioning is a key issue in MRN systems in terms of accuracy, data rate, and distance. We propose an indoor navigation and positioning combined algorithm and further evaluate its performance. An android application is developed to support data acquisition from multiple simultaneous transmitter links. Experimentally, we received data from four links which are required to ensure a higher positioning accuracy.

scholarly journals Error Analysis on Indoor Localization with Visible Light Communication

2019 ◽  
Vol 11 (4) ◽  
pp. 427
Author(s):  
Jun Yan ◽  
Bingcheng Zhu ◽  
Liang Chen ◽  
Jin Wang ◽  
Jingbin Liu
Keyword(s):  
Visible Light ◽  
Indoor Localization ◽  
Smart Phone ◽  
Visible Light Communication ◽  
Indoor Positioning ◽  
Light Signal ◽  
Indoor Navigation ◽  
Angle Of Arrival ◽  
Light Emitting ◽  
Indoor Scenarios

Affected by the complexity of the indoor environment, accurate indoor positioning is challenging in many localization based services (LBS). Recently, it has been recognized that, visible light communication (VLC) is promising for indoor navigation and positioning, due to the low implementation cost with marginal modification to the existing infrastructure and the possibility to achieve high accurate positioning results. Provided that the positions of the light emitting diodes (LEDs) are known to the receiver, the angle of arrival (AOA) of the light signal is able to be estimated by a camera embedded in a smart phone, and thus the position of the smart phone can be derived based on the triangulation. In this paper, the performance of the positioning accuracy is analyzed based on indoor positioning with VLC, and the analytical upper bound of location error is derived. Extensive simulation results have verified the theoretical analysis on the VLC-based localization approach in different indoor scenarios. In order to obtain better location performance, the principles of choosing reference LED and localization LED are also given.

Beacon selection and calibration for the efficient localization of a mobile robot

Robotica ◽  
2013 ◽  
Vol 32 (1) ◽  
pp. 115-131 ◽  
Author(s):  
Jaehyun Park ◽  
Jangmyung Lee
Keyword(s):  
Mobile Robot ◽  
Indoor Localization ◽  
Setup Time ◽  
Ultrasonic Waves ◽  
Mobile Robot Navigation ◽  
Indoor Environments ◽  
Ultrasonic Sensors ◽  
Indoor Space ◽  
Localization Scheme ◽  
Set Up

SUMMARYThis paper proposes a localization scheme using ultrasonic beacons in an unstructured multi-block workspace. Indoor localization schemes using ultrasonic sensors have widely been studied due to their low costs and high accuracies. However, ultrasonic sensors are susceptible to environmental noise due to the propagation characteristics of ultrasonic waves. In addition, the decay of ultrasonic signals over long distances implies that ultrasonic sensors are unsuitable for use in large indoor environments. To overcome these shortcomings of ultrasonic sensors, while retaining their advantages, a multi-block approach was devised by dividing an indoor space into several blocks with multiple beacons in each block. However, it is difficult to divide an indoor space into several blocks when beacons cannot be installed in a regular manner or when some new beacons are installed. To resolve this difficulty, a dynamic algorithm is needed to divide an indoor space into multiple blocks and to select suitable beacons. Therefore, this paper proposes a real-time localization scheme to estimate the position of a mobile robot independent of beacon locations and to estimate the position of a new beacon installed at an unknown position. A beacon selection algorithm was developed to select optimal beacons according to robot position and to set up sets of beacons for mobile robot navigation. By using the new beacon searching and calibration algorithm, a mobile robot is able to navigate in an unknown space without requiring the additional setup time needed to install new beacons. The performance of the proposed localization system was verified using real experiments.

scholarly journals THE ALGORITHM OF SIMULTANEOUS NAVIGATION AND MAPPING FOR MOBILE ROBOT BASED ON THE ITERATIVE ALGORITHM OF THE NEAREST PIXELS AND DESCRIPTOR CALCULATED IN A CIRCULAR MOVING WINDOW

2018 ◽  
Vol 14 (3) ◽  
pp. 49-56
Author(s):  
A V Vokhmintcev ◽  
S A Pachganov
Keyword(s):  
Mobile Robot ◽  
Real Data ◽  
Point Clouds ◽  
Mobile Robot Navigation ◽  
Depth Information ◽  
3D Point Clouds ◽  
Surrounding Space ◽  
Remote Observation ◽  
Slam Algorithm ◽  
Combined Algorithm

New combined algorithm for simultaneous navigation and map construction is developed using visual characteristics and depth information to compare images, register 3D-point clouds, and build global sequential 3D-maps of the surrounding space. The performance and computational complexity of the proposed RGB-D SLAM algorithm are presented and discussed with reference and real data. The results can be applied in real-time tracking of objects, in non-cooperative remote observation, and semantic mapping of mobile robot navigation problems.

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