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ROS-Based Autonomous Navigation Robot Platform with Stepping Motor

Indoor navigation robots, which have been developed using a robot operating system, typically use a direct current motor as a motion actuator. Their control algorithm is generally complex and requires the cooperation of sensors such as wheel encoders to correct errors. For this study, an autonomous...

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Detalles Bibliográficos
Autores principales: Zhao, Shengmin, Hwang, Seung-Hoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098625/
https://www.ncbi.nlm.nih.gov/pubmed/37050707
http://dx.doi.org/10.3390/s23073648
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author Zhao, Shengmin
Hwang, Seung-Hoon
author_facet Zhao, Shengmin
Hwang, Seung-Hoon
author_sort Zhao, Shengmin
collection PubMed
description Indoor navigation robots, which have been developed using a robot operating system, typically use a direct current motor as a motion actuator. Their control algorithm is generally complex and requires the cooperation of sensors such as wheel encoders to correct errors. For this study, an autonomous navigation robot platform named Owlbot was designed, which is equipped with a stepping motor as a mobile actuator. In addition, a stepping motor control algorithm was developed using polynomial equations, which can effectively convert speed instructions to generate control signals for accurately operating the motor. Using 2D LiDAR and an inertial measurement unit as the primary sensors, simultaneous localization, mapping, and autonomous navigation are realised based on the particle filtering mapping algorithm. The experimental results show that Owlbot can effectively map the unknown environment and realise autonomous navigation through the proposed control algorithm, with a maximum movement error being smaller than 0.015 m.
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spelling pubmed-100986252023-04-14 ROS-Based Autonomous Navigation Robot Platform with Stepping Motor Zhao, Shengmin Hwang, Seung-Hoon Sensors (Basel) Article Indoor navigation robots, which have been developed using a robot operating system, typically use a direct current motor as a motion actuator. Their control algorithm is generally complex and requires the cooperation of sensors such as wheel encoders to correct errors. For this study, an autonomous navigation robot platform named Owlbot was designed, which is equipped with a stepping motor as a mobile actuator. In addition, a stepping motor control algorithm was developed using polynomial equations, which can effectively convert speed instructions to generate control signals for accurately operating the motor. Using 2D LiDAR and an inertial measurement unit as the primary sensors, simultaneous localization, mapping, and autonomous navigation are realised based on the particle filtering mapping algorithm. The experimental results show that Owlbot can effectively map the unknown environment and realise autonomous navigation through the proposed control algorithm, with a maximum movement error being smaller than 0.015 m. MDPI 2023-03-31 /pmc/articles/PMC10098625/ /pubmed/37050707 http://dx.doi.org/10.3390/s23073648 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Shengmin
Hwang, Seung-Hoon
ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
title ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
title_full ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
title_fullStr ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
title_full_unstemmed ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
title_short ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
title_sort ros-based autonomous navigation robot platform with stepping motor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098625/
https://www.ncbi.nlm.nih.gov/pubmed/37050707
http://dx.doi.org/10.3390/s23073648
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