A Vision-Based System for Robot Localization in Large Industrial Environments

Boutteau, Rémi; Rossi, Romain; Qin, Lei; Merriaux, Pierre; Savatier, Xavier

doi:10.1007/s10846-019-01114-x

Cited by 17 publications

(4 citation statements)

References 27 publications

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“…However, normal image recognition is considerably affected by the environmental brightness and the printed QR codes stain easily in spraying works. Boutteau et al (2020) used distributed LED lights attached to a robot for localization, which is the opposite of our method. However, they obtained a localization accuracy at 30 mm and 1° on a small robot.…”

Section: Methodsmentioning

confidence: 99%

High-Precision Vision Localization System for Autonomous Guided Vehicles in Dusty Industrial Environments

Liu

Wang

Chen

2022

navi

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Autonomous guided vehicles (AGVs) are widely used in ports and warehouses during the ongoing Fourth Industrial Revolution (Industry 4.0). AGVs can transfer cargoes to their correct destinations or carry industrial robots to work from various directions. In cases like Arthur et al. (2008) andHofacker (1993), engineers put a robot on an AGV to finish aircraft manufacturing instead of a fixed robotic system such as a gantry crane or guide rail on the ground. An AGV can avoid structural transformation and has high adaptability in various applications. However, highly accurate AGV localization is required for safe driving and precise robotic operations.Several studies have investigated high-precision localization methods for AGVs since 1908. A classical method involves setting magnetic or electric cables underground for tracking. AGVs would follow the cable path by electromagnetic induction (Chen et al., 2004) using special sensors. This method is still widely used in modern factories. It can maintain a position accuracy of around 10 mm. However, it damages the original ground and can be easily affected by magnetic and electric fields.Some studies used a monocular camera (Wu et al., 2019) to track colored stripes and quick response (QR) codes. The positioning error in those studies could be

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Section: Methodsmentioning

confidence: 99%

High-Precision Vision Localization System for Autonomous Guided Vehicles in Dusty Industrial Environments

Liu

Wang

Chen

2022

navi

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“…Com o aumento das publicações a partir da década de 90, a ferramenta ROV passou a ser vista não somente em suas áreas de atuação, como também no meio acadêmico e científico. Por se tratar de uma tecnologia em crescente expansão e com aplicabilidade comercial, e não somente para fins científicos e militares, os trabalhos publicados são específicos, com nível de detalhamento e riqueza e em grande maioria, inéditos (Zhang et al, 2013, Lv et al, 2014, Luo et al, 2018, Boutteau et al 2020, Htun et al, 2018, Wahab et al, 2020, Zhou & Zhao, 2020.…”

Section: Rovs Classificação E Nacionalidadeunclassified

Panorama mundial das pesquisas com robôs subaquáticos remotamente operados (ROV)

Carminatto

Ciongoli

Sabundjian

2021

RSD

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Veículos subaquáticos operados remotamente (ROVs) fazem parte de um grupo de tecnologias que vem sendo cada vez mais utilizados como ferramenta em pesquisas científicas. As aplicações para esses veículos são vastas e o trabalho tem por objetivo apresentar análises de âmbito socioeconômico e ambiental trazendo um panorama mundial sobre as pesquisas científicas que incluem os ROVs. Foi criada uma matriz de dados com pesquisa literária sendo incluídos 78 documentos publicados. As principais informações avaliadas foram continentes e países que publicam trabalhos, parcerias realizadas entre os países, se houve ou não financiamento para a realização do projeto, qual a área de estudo e aplicação e quais as características do ROV utilizado, especialmente se ele foi desenvolvido exclusivamente para o projeto ou se houve aquisição de equipamento já existente. Notamos que os países mais desenvolvidos são os que mais investem na tecnologia, tanto em número de publicações quanto em financiamentos, fato esse que pode ser justificado pelo compromisso de as entidades governamentais fazerem aportes constantes na pesquisa científica. Em contrapartida, países em desenvolvimento como Brasil e China vem apresentando ótimos resultados e crescimento na aplicação de recursos em ciência e tecnologia. Os benefícios do investimento nesta tecnologia refletem em toda a sociedade, gerando empregos, contribuindo para a economia nacional e incentivando a pesquisa, o conhecimento e a ciência.

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“…The results demonstrated improved performance compared to the traditional Extended Kalman Filter. Similarly, many more techniques are available in the literature, including rigid body localization using wireless sensor networks [11,12], WiFi-based localization architecture [13,14], vision-based approaches using different types of cameras [15][16][17], and particle filter-based approaches such as Adaptive Monte Carlo Localization (MCL) [18], Self-Adaptive MCL (SA-MCL) [19], and particle flow filtering architecture [20]. It is also possible to improve their performance with suggested arrangements [21].…”

Section: Introductionmentioning

confidence: 99%

A multi-stage localization framework for accurate and precise docking of autonomous mobile robots (AMRs)

Yilmaz,

Temeltas

2024

Robotica

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Autonomous navigation has been a long-standing research topic, and researchers have worked on many challenging problems in indoor and outdoor environments. One application area of navigation solutions is material handling in industrial environments. With Industry 4.0, the simple problem in traditional factories has evolved into the use of autonomous mobile robots within flexible production islands in a self-decision-making structure. Two main stages of such a navigation system are safe transportation of the vehicle from one point to another and reaching destinations at industrial standards. The main concern in the former is roughly determining the vehicle’s pose to follow the route, while the latter aims to reach the target with high accuracy and precision. Often, it may not be possible or require extra effort to satisfy requirements with a single localization method. Therefore, a multi-stage localization approach is proposed in this study. Particle filter-based large-scale localization approaches are utilized during the vehicle’s movement from one point to another, while scan-matching-based methods are used in the docking stage. The localization system enables the appropriate approach based on the vehicle’s status and task through a decision-making mechanism. The decision-making mechanism uses a similarity metric obtained through the correntropy criterion to decide when and how to switch from large-scale localization to precise localization. The feasibility and performance of the developed method are corroborated through field tests. These evaluations demonstrate that the proposed method accomplishes tasks with sub-centimeter and sub-degree accuracy and precision without affecting the operation of the navigation algorithms in real time.

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A Vision-Based System for Robot Localization in Large Industrial Environments

Cited by 17 publications

References 27 publications

High-Precision Vision Localization System for Autonomous Guided Vehicles in Dusty Industrial Environments

High-Precision Vision Localization System for Autonomous Guided Vehicles in Dusty Industrial Environments

Panorama mundial das pesquisas com robôs subaquáticos remotamente operados (ROV)

A multi-stage localization framework for accurate and precise docking of autonomous mobile robots (AMRs)

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