I AL-Furati
IR sensors array for robots localization using K means clustering algorithm
AL-Furati, I; Rashid, AT; Al-Ibadi, A
Authors
AT Rashid
A Al-Ibadi
Abstract
The position of multi-robot system in an indoor localization system is successfully estimated using a new algorithm. The localization problem is resolved by using an array of IR receiver sensors distributed uniformly in the environment. The necessary information about the localization development is collected by scanning the IR sensor array in the environment. The scheme of scanning process is done column by column to recognize and mention the position of IR receiver’s sensors, which received signals from the IR transmitter that is fixed on the robot. This principle of scanning helps to minimize the required time for robot localization. The k-means clustering algorithm is used to estimate the multi-robot locations by isolating the labeled IR receivers into clusters. Basically the multi-robot position is estimated to be the middle of each cluster. Simulation results demonstrate the advances algorithm in estimation the multi-robot positions for various dimensional IR receiver’s array.
Citation
AL-Furati, I., Rashid, A., & Al-Ibadi, A. (2019, March). IR sensors array for robots localization using K means clustering algorithm. Presented at UKSim-AMSS 21st International Conference on Modelling & Simulation, Cambridge, UK
Presentation Conference Type | Other |
---|---|
Conference Name | UKSim-AMSS 21st International Conference on Modelling & Simulation |
Conference Location | Cambridge, UK |
Start Date | Mar 27, 2019 |
End Date | Mar 29, 2019 |
Acceptance Date | Feb 1, 2019 |
Publication Date | Mar 27, 2019 |
Deposit Date | Mar 29, 2019 |
Publicly Available Date | Mar 29, 2019 |
DOI | https://doi.org/10.5013/IJSSST.a.20.S1.12 |
Publisher URL | http://www.uksim2019.info/ |
Related Public URLs | http://ijssst.info/ http://www.uksim2019.info/ |
Additional Information | Event Type : Conference |
Files
paper12.pdf
(696 Kb)
PDF
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search