IR sensors array for robots localization using K means clustering algorithm

AL-Furati, I, Rashid, AT and Al-Ibadi, A ORCID: 2019, IR sensors array for robots localization using K means clustering algorithm , in: UKSim-AMSS 21st International Conference on Modelling & Simulation, 27-29 March 2019, Cambridge, UK.

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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.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: International Journal of Simulation Systems, Science & Technology
Related URLs:
Depositing User: Dr. Alaa Al-Ibadi
Date Deposited: 29 Mar 2019 14:51
Last Modified: 16 Feb 2022 01:32

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