Navigating Autonomous Underwater Vehicles

Bingham, Brian; Olin, Franklin W.

doi:10.5772/6695

Cited by 10 publications

(7 citation statements)

References 27 publications

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“…As opposed to the localization of surface vehicles, where the position can obtained using GPS based systems, there are many challenges in underwater localization. On the one hand, the significant attenuation of any electromagnetic signals [1] renders the use of GPS and other RF based techniques infeasible.…”

Section: Underwater Vehicle Localizationmentioning

confidence: 99%

“…Figure 2.2 shows an example of growth in position error of a vehicle traveling along the X axis. The uncertainty in velocity is predominant in the error growth in the movement direction, while the error in the direction perpendicular to movement is mostly affected by heading uncertainty [1].…”

Section: Dead-reckoningmentioning

confidence: 99%

“…The CRLB is commonly used in this area since localization is an estimation problem, where the position and attitude of a vehicle are estimated based on certain measurements. [1].…”

Section: Cramer-rao Lower Boundmentioning

confidence: 99%

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Guidance of an Autonomous Surface Vehicle for Underwater Navigation Aid

Sousa

Ferreira

Cruz

2018

2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV)

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ResumoVeículos Submarinos não Tripulados (UUVs), tais como Veículos Submarinos Autónomos (AUVs) e Veículos de Controlo Remoto (ROVs) são ferramentas versáteis, adequadas a diversas atividades para diferentes áreas, e tem vindo a registar um aumento de uso, fazendo das mesmas uma área de interesse no estudo da robótica.Em termos gerais, a performance de qualquer veículo submarino em qualquer tarefa é profundamente afetada pela precisão do seu sistema de localização. O principal desafio da localização submarina é a atenuação significativa de qualquer sinal submarino de frequência de radio (RF) que impede o uso dos métodos de localização habitualmente usados tais como Sistema de Posicionamento Global (GPS). Muitos métodos foram estudados para a localização de UUVs, incluindo o uso de faróis acústicos. Um destes métodos é o uso de um único farol móvel para obter alcances acústicos, ao contrário de um farol imóvel, que restringe a trajetória dos UUVs, ou múltiplos faróis que envolvem mais hardware, complicando a logística das missões e um aumento dos custos.Nesta dissertação é proposto um algoritmo de navegação com base na Matriz de Informação de Fisher para um veículo de superfície autónomo que tem como função ajudar na navegação de um veiculo subaquático.i ii Abstract Unmanned Underwater Vehicles (UUVs), such as Autonomous Underwater Vehicles (AUVs) and Remote Operated Vehicles (ROVs) are versatile tools, suitable for many activities in different fields, and have seen an increase in usage, making them an area of interest in the study of robotics.Generically speaking, the performance of any underwater vehicle in any given task is deeply affected by the precision of its localization system. The main challenge in underwater localization is the significant attenuation of any Radio Frequency (RF) signal underwater, which prevents the use of many common location methods such as the Global Positioning System (GPS). Many methods have been studied for the localization of UUVs, including the use of acoustic beacons. One of these methods is the use of a single moving beacon to obtain acoustic ranges, as opposed to a stationary single beacon, which restricts the UUV's trajectory or multiple beacons, which involve more hardware, complicating missions' logistics and increasing costs.In this dissertation a guidance algorithm based on the Fisher Information Matrix is proposed for an Autonomous Surface Vehicle to serve as a beacon vehicle and aid in the navigation of a UUV.iii iv Ackowledgements Em primeiro lugar gostaria de agradecer ao professor Nuno Cruz e ao professor Bruno Ferreira por todo o tempo dedicado e disponibilidade que demonstraram ao longo desta dissertação. Em último. mas não menos importante, à minha família, amigos e colegas de curso que decerto compreendem o porquê desta brevidade no agradecimento.

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Section: Underwater Vehicle Localizationmentioning

confidence: 99%

Section: Dead-reckoningmentioning

confidence: 99%

See 1 more Smart Citation

Guidance of an Autonomous Surface Vehicle for Underwater Navigation Aid

Sousa

Ferreira

Cruz

2018

2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV)

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“…If the goal is to follow a path parallel to the feature, as an underwater pipe on the floor or a wall, the window size will be: (4) where corresponds the maximum distance between the sonar and the feature on the orthogonal direction.…”

Section: A Data Segmentation and Extractionmentioning

confidence: 99%

“…Other vehicles such as AUVs (Autonomous Underwater Vehicles) are not able to navigate without the help of methods like absolute location, such as GPS or acoustic beacons. In fact, these vehicles have a certain degree of autonomy, but cannot be considered as truly autonomous [1], [2], [3], [4] and [5].…”

Section: Introductionmentioning

confidence: 99%

Using side scan sonar for relative navigation

Pinto¹,

Ferreira²,

Matos³

et al. 2009

2009 35th Annual Conference of IEEE Industrial Electronics

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Abstract-This paper describes the interaction between the kinematic model of the AUV MARES and the measurement or observation of the environment through images obtained with the Sonar use. Three types of sonar are discussed in this paper, they are forward-look, side scan and multibeam, but the sonar used to develop this work was the side scan sonar. The type of observations and characteristics of the environment provided by the sonar are described here. The method which connects the sensory part of the vehicle with the observations of the sonar, was the Kalman filter (EKF). In this paper, we present two simulations of filters for two different characteristics. Both filters estimate the characteristics of the natural landmarks, creating a environment map, but both of them consider different states of the vehicle. Results of the simulation are obtained. The features that are considered are an underwater pipe on the floor and a wall. It also generated a control for the vehicle that provides the capacity to move along the feature/landmark from a reference distance.

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Robotic tools for deep water archaeology: Surveying an ancient shipwreck with an autonomous underwater vehicle

Bingham

Foley

Singh

et al. 2010

Journal of Field Robotics

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199

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The goals of this field note are twofold. First, we detail the operations and discuss the results of the 2005 Chios ancient shipwreck survey. This survey was conducted by an international team of engineers, archaeologists and natural scientists off the Greek island of Chios in the northeastern Aegean Sea using an autonomous underwater vehicle (AUV) built specifically for high-resolution site inspection and characterization. Second, using the survey operations as context, we identify the specific challenges of adapting AUV technology for deep water archaeology and describe how our team addressed these challenges during the Chios expedition. After identifying the state-of-the-art in robotic tools for deep water archaeology, we discuss opportunities where new developments and research (e.g., AUV platforms, underwater imaging, remote sensing and navigation techniques) will improve rapid assessment of deep water archaeological sites. It is our hope that by reporting on the Chios field expedition we can both describe the opportunities that AUVs bring to fine resolution seafloor site surveys and elucidate future opportunities for collaborations between roboticists and ocean scientists.

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Navigating Autonomous Underwater Vehicles

Cited by 10 publications

References 27 publications

Guidance of an Autonomous Surface Vehicle for Underwater Navigation Aid

Guidance of an Autonomous Surface Vehicle for Underwater Navigation Aid

Using side scan sonar for relative navigation

Robotic tools for deep water archaeology: Surveying an ancient shipwreck with an autonomous underwater vehicle

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