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Reseach Article

Multi-Robot Localization System using an Array of LEDs and LDR Sensors

by Israa Sabri Abdulameer AL-Forati, Abdulmutallab Rashid
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 10
Year of Publication: 2020
Authors: Israa Sabri Abdulameer AL-Forati, Abdulmutallab Rashid
10.5120/ijca2020920001

Israa Sabri Abdulameer AL-Forati, Abdulmutallab Rashid . Multi-Robot Localization System using an Array of LEDs and LDR Sensors. International Journal of Computer Applications. 176, 10 ( Apr 2020), 9-12. DOI=10.5120/ijca2020920001

@article{ 10.5120/ijca2020920001,
author = { Israa Sabri Abdulameer AL-Forati, Abdulmutallab Rashid },
title = { Multi-Robot Localization System using an Array of LEDs and LDR Sensors },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2020 },
volume = { 176 },
number = { 10 },
month = { Apr },
year = { 2020 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number10/31235-2020920001/ },
doi = { 10.5120/ijca2020920001 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:42:06.600417+05:30
%A Israa Sabri Abdulameer AL-Forati
%A Abdulmutallab Rashid
%T Multi-Robot Localization System using an Array of LEDs and LDR Sensors
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 10
%P 9-12
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

a new positioning system for indoor multi-robot localization is proposed. This system solves the problem of localization by using an array of Light Emitting Diodes (LEDs) distributed uniformly in the environment. The localization is achieved by collecting the information from a group of Light Dependent Resistor (LDR) sensors with which the robot is equipped. The binary search algorithm is used to reduce the time of the localization process by controlling the lights of the LED array. The minimum bounded circle algorithm is used to draw a virtual circle from the information collected by the LDR sensors and the center of this circle represents the robot’s location. This algorithm can be implemented in a multi-robot system when the main control unit can distinguish among the LDR sensors’ information. In the case of unknown information, the K-means Clustering algorithm is used to separate this information into clusters. Each cluster can be used to estimate the location of one robot. The suggested system is simulated and practically implemented in an environment with (32*32) arrays of LEDs. The simulation and experimental results of this system show good performance in the localization process.

References
  1. A.T. Rashid, A. A. Ali, M. Frasca, and L. Fortuna (2013). Path planning with obstacle avoidance based on the visibility binary tree algorithm. Robotics and Autonomous Systems, 61(12), 1440-1449.
  2. Z. Y. Ibrahim, A. T. Rashid and A. F. Marhoon (2016). An algorithm for Path planning with polygon obstacle avoidance based on the virtual circle tangents. Iraq Journal Electrical and Electronic Engineering, 12(2), 221-234.
  3. Z. Y. Ibrahim, A. T. Rashid and A. F. Marhoon (2016). Prediction-Based Path Planning with Obstacle Avoidance in Dynamic Target Environment. Basrah Journal of Engineering Science,16(2), 48-60.
  4. A. T. Rashid, M. Frasca, A, A, Ali, A. Rizzo and L. Fortuna (2015) Multi-robot localization and orientation estimation using robotic cluster matching algorithm. Robotics and Autonomous Systems, 63, 108–121.
  5. Mautz R, Tilch S (2011) Survey of optical indoor positioning systems. In:2011 international conference on indoor positioning and indoor navigation, pp 1–7. https ://doi.org/10.1109/IPIN.2011.60719 25
  6. Nuaimi KA, Kamel H (2011) A survey of indoor positioning systems and algorithms. In: 2011 international conference on innovations in information technology, pp 185–190. https ://doi.org/10.1109/INNOV ATIONS.2011.58938 13
  7. Koyuncu H, Yang SH (2010) A survey of indoor positioning and object locating systems. IJCSNS Int J Comput Sci Netw Secur 10(5):121–128
  8. Liu H, Darabi H, Banerjee P, Liu J (2007) Survey of wireless indoor positioning techniques and systems. IEEE Trans Syst Man Cybern Part C Appl Rev 37(6):1067–1080. https ://doi.org/10.1109/TSMCC .2007.90575 0
  9. Desouza GN, Kak AC (2002) Vision for mobile robot navigation: a survey. IEEE Trans Pattern Anal Mach Intell 24(2):237–267. https ://doi.org/10.1109/34.98290 3
  10. robotshop: Hagisonic StarGazer RS robot localization system. http://www.robot shop.com/en/hagis onic-starg azer-rs-localization -syste m.html
  11. Ul-Haque I, Prassler E (2010) Experimental evaluation of a low-cost mobile robot localization technique for large indoor public environments. In: ISR 2010 (41st international symposium on robotics) and ROBOTIK 2010 (6thGerman conference on robotics), pp 1–7
  12. Oh JH, Kim D, Lee BH (2014) An indoor localization system for mobile robots using an active infrared positioning sensor. J Ind Intell Inf2(1):35–38
  13. Lee S (2009) Use of infrared light reflecting landmarks for localization. Ind Robot Int J 36(2):138–145. https ://doi.org/10.1108/01439 91091 09325 95
  14. Krejsa J, Vechet S (2012) Infrared beacons-based localization of mobile robot. Elektronika ir Elektrotechnika 117(1):17–22
  15. I. S. Alfurati and Abdulmuttalib T. Rashid (2018). Performance Comparison of Three Types of Sensor Matrices for Indoor Multi-Robot Localization. International Journal of Computer Applications (0975 – 8887), 181 (26), 22-29.
  16. I. S. Alfurati and Abdulmuttalib T. Rashid. An Efficient Mathematical Approach for an Indoor Robot Localization System. Iraqi Journal of Electrical and Electronic Engineering, 15 (2), 61-70, 2019.
  17. E. E. Odokuma and O. O. Owolabi (2016). An Indexed Method for Improving the Efficiency of the Binary Search Algorithm. International Journal of Advanced Research in Computer Science and Software Engineering, 6(5).
  18. I. S. Alfurati and Abdulmuttalib T. Rashid (2019),” Design and Implementation an Indoor Robot Localization System Using Minimum Bounded Circle Algorithm”, The 8th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO'2019).
  19. I. S. Alfurati, A. T. Rashid and Alaa Al-Ibadi (2019). IR sensors array for robot's localization using K means clustering algorithm. International Journal of Simulation Systems, Science & Technology, 12.1-12.6.
Index Terms

Computer Science
Information Sciences

Keywords

Localization system Binary search algorithm Minimum bounded circle algorithm.