國立虎尾科技大學 |

Navigation System for Robots in Harsh Environments = Sistema de Navegação para Robôs em Ambientes Agrestes /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Navigation System for Robots in Harsh Environments/ Sandra Leonor Craveiro Rodrigues.
其他題名:	Sistema de Navegação para Robôs em Ambientes Agrestes /
作者:	Rodrigues, Sandra Leonor Craveiro,
面頁冊數:	1 electronic resource (118 pages)
附註:	Source: Masters Abstracts International, Volume: 87-01.
Contained By:	Masters Abstracts International87-01.
標題:	Robotics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32161915
ISBN:	9798290695945

Navigation System for Robots in Harsh Environments = Sistema de Navegação para Robôs em Ambientes Agrestes /
Rodrigues, Sandra Leonor Craveiro,

Navigation System for Robots in Harsh EnvironmentsSistema de Navegação para Robôs em Ambientes Agrestes / [electronic resource] =Sandra Leonor Craveiro Rodrigues. - 1 electronic resource (118 pages)

Source: Masters Abstracts International, Volume: 87-01.

Localization in dusty environments is challenging due to sensor interference, environmental noise, and poor visibility, as dust sticks to the sensors, increasing the uncertainty of their measurements. This dissertation focuses on developing a robust and precise localization system that uses sensor fusion to integrate Visual Simultaneous Localization and Mapping (VSLAM), odometry, and Ultra-Wideband (UWB) positioning sensors to enhance localization accuracy. The suggested system is intended for industrial applications, particularly where traditional localization systems are inadequate due to dust and low visibility. Robot Operating System (ROS) was employed to create a localization system using multiple sensors to compensate for individual irregularities.To validate the system, a simulation world was used in Gazebo using TurtleBot3 and simulated anchors of UWB, where a plug-in was created to employ UWB technology in Gazebo. The results indicate that combining the ORB-SLAM3 data with the odometer data and the UWB data improves localization, particularly in environments with low visual quality. This dissertation contributes to the advancement of autonomous robotics by offering a scalable and adaptable approach to localization in dusty and noisy environments.This dissertation carried out a practical component, which consists of using ArUco markers to evaluate the distance accuracy of the UWB system and the OptiTrack system to assess its accuracy and precision by comparing the positions collected by both systems.

English

ISBN: 9798290695945Subjects--Topical Terms:

561941
Robotics.

Navigation System for Robots in Harsh Environments = Sistema de Navegação para Robôs em Ambientes Agrestes /
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520 # $a Localization in dusty environments is challenging due to sensor interference, environmental noise, and poor visibility, as dust sticks to the sensors, increasing the uncertainty of their measurements. This dissertation focuses on developing a robust and precise localization system that uses sensor fusion to integrate Visual Simultaneous Localization and Mapping (VSLAM), odometry, and Ultra-Wideband (UWB) positioning sensors to enhance localization accuracy. The suggested system is intended for industrial applications, particularly where traditional localization systems are inadequate due to dust and low visibility. Robot Operating System (ROS) was employed to create a localization system using multiple sensors to compensate for individual irregularities.To validate the system, a simulation world was used in Gazebo using TurtleBot3 and simulated anchors of UWB, where a plug-in was created to employ UWB technology in Gazebo. The results indicate that combining the ORB-SLAM3 data with the odometer data and the UWB data improves localization, particularly in environments with low visual quality. This dissertation contributes to the advancement of autonomous robotics by offering a scalable and adaptable approach to localization in dusty and noisy environments.This dissertation carried out a practical component, which consists of using ArUco markers to evaluate the distance accuracy of the UWB system and the OptiTrack system to assess its accuracy and precision by comparing the positions collected by both systems.
520 3 $a Atualmente, a localização em ambientes poeirentos e ruidosos é um desafio, devido à interferência dos sensores, ao ruido ambiental e à fraca visibilidade. Esta dissertação centra-se no desenvolvimento de um sistema de localização robusto e preciso que utiliza a fusão de sensores com VSLAM, odometria e posicionamento UWB para melhorar a precisão da localização. O sistema destina-se a aplicações industriais, particularmente em ambientes onde os sistemas de localização tradicionais são inadequados devido a poeiras e baixa visibilidade. O ROS2 foi utilizado para criar um sistema de localização que usa múltiplos sensores para compensar as irregularidades individuais dos mesmos. Para validar o sistema, foi realizado uma simulação do mundo no Gazebo com o TurtleBot3 e simulações de âncoras UWB, onde foi criado um plugin para conectar a tecnologia UWB no Gazebo. Os resultados evidênciam que a fusão dos dados do ORB-SLAM3 com os dados dos odometros e os dados do UWB melhora a localização, principalmente em ambientes com baixa qualidade visual. Esta dissertação contribui para o avanço da robótica autónoma, oferecendo uma abordagem escalável e adaptável à localização em ambientes poeirentos e ruidosos. Nesta dissertação foi realizada uma parte prática que consiste na utilização de marcadores de ArUco para avaliar a precisão de distancia do sistema de UWB, bem como o uso do sistema OptiTrack para avaliar a acurácia e precisão do sistema de UWB, comparando as posições que ambos os sistemas recolhiam.
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