research-article

Omnidirectional Robot Indoor Localisation using Two Pixy Cameras and Artificial Colour Code Signature Beacons

Authors:

MOHANAD NIHAD NOAMAN,

Zeyad Yousif Abdoon Al-Shibaany,

SABA AL-WAISAuthors Info & Claims

CIIS '20: Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems

Pages 110 - 118

https://doi.org/10.1145/3440840.3440849

Published: 15 February 2021 Publication History

Abstract

Location estimation of Autonomous mobile robots is an essential and challenging task, especially for indoor applications. Despite the many solutions and algorithms that have been suggested in the literature to provide a precise localisation technique for mobile robots, it continues to be an open research problem and worth further study. In this paper, a predefined map with artificial colour code signature (CCs) beacons are used to build an effective algorithm to achieve an indoor localisation and position prediction of an omnidirectional mobile robot. This algorithm is primarily based on calculating the distance between the robot and the beacon using Pixy cameras, as vision sensors; then, estimating the position of the robot using a trilateration method. By comparing the results obtained in this paper with the mathematically obtained results, it is clearly shown that the robot effectively follows the localisation algorithm to estimate its pose (position and orientation), improving its localisation abilities in addition to obtaining its initial position. Furthermore, the limitations associated with using Pixy cameras are discussed in this paper as well.

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Cited By

Silva CWimalaratne P(2021)Indoor Localization using Color Code Identification2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET52533.2021.9698731(1-4)Online publication date: 9-Dec-2021
https://doi.org/10.1109/ICECET52533.2021.9698731

Index Terms

Omnidirectional Robot Indoor Localisation using Two Pixy Cameras and Artificial Colour Code Signature Beacons
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Robotics
    2. Sensors and actuators
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding

Index terms have been assigned to the content through auto-classification.

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cover image ACM Other conferences

CIIS '20: Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems

November 2020

135 pages

ISBN:9781450388085

DOI:10.1145/3440840

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 February 2021

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CIIS 2020

CIIS 2020: 2020 The 3rd International Conference on Computational Intelligence and Intelligent Systems

November 13 - 15, 2020

Tokyo, Japan

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Cited By

Silva CWimalaratne P(2021)Indoor Localization using Color Code Identification2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET52533.2021.9698731(1-4)Online publication date: 9-Dec-2021
https://doi.org/10.1109/ICECET52533.2021.9698731

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