Skip to main content

Research Repository

Advanced Search

IR sensors array for robots localization using K means clustering algorithm

AL-Furati, I; Rashid, AT; Al-Ibadi, A

IR sensors array for robots localization using K means clustering algorithm Thumbnail


Authors

I AL-Furati

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






Downloadable Citations