Optimal path shape for range-only underwater target localization using a Wave Glider

Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system’s costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.Peer ReviewedPostprint (author's final draft

Underwater acoustic localisation and referencing: an enhanced subsurface positioning method for archaeological data collection of submerged cultural resources

Traditional and modern optical methods of maritime archaeological site documentation typically lack absolute spatial information as part of submerged cultural heritage surveys in locations where shore-based satellite positioning technologies are not applicable for use. This is due to the inability to use satellite positioning receivers beneath the water surface as a result of the high attenuation rate of electromagnetic waves in a marine environment. The defence and offshore energy industries solved this problem through the incorporation of acoustic ranging systems used in conjunction with satellite positioning receivers. Underwater acoustic ranging equipment, such as ultra-short baseline (USBL) and long baseline (LBL) systems, are commonly used in geophysical surveys and marine construction projects to provide subsurface positioning information of underwater instrumentation such as towed sonar arrays, remotely-operated vehicles (ROVs), and divers. Satellite positioning and underwater acoustic ranging configurations have been in continuous use for more than three decades, and such equipment systems are readily available throughout the world for commercial and scientific applications. Despite the proven effectiveness and accessibility of these systems, maritime archaeology fieldwork practices have not successfully integrated these systems into established underwater data collection techniques. This thesis was established to determine if traditional and modern optical maritime archaeological data collection techniques are capable of being supplemented by a tandem satellite positioning system and USBL acoustic ranging configuration to provide underwater positioning information in accordance with universally-accepted geophysical surveying spatial and equipment standards, such as those published by the International Hydrographic Organization (IHO), Bureau of Ocean Energy Management (BOEM), Historic England, and others. In the absence of recognised spatial standards within the maritime archaeology community, this thesis relied on geophysical surveying spatial and equipment standards as the research parameters upon which the Underwater Acoustic Localisation and Referencing (UALR) methodology was developed. The UALR methodology presented in this thesis successfully incorporated a GPS/USBL configuration for providing subsurface latitude and longitude coordinates for ground control point positions for traditional and modern optical archaeological data collection techniques. The collected datasets were georeferenced using underwater spatial information gathered by the UALR methodology process, and demonstrated that these methods are capable of achieving spatial accuracy and measurement precision in accordance with geophysical surveying specifications. By adhering to these standards, the UALR methodology is applicable for use by archaeologists in support of geophysical surveying operations throughout the world

Jointly Optimizing Placement and Inference for Beacon-based Localization

The ability of robots to estimate their location is crucial for a wide variety of autonomous operations. In settings where GPS is unavailable, measurements of transmissions from fixed beacons provide an effective means of estimating a robot's location as it navigates. The accuracy of such a beacon-based localization system depends both on how beacons are distributed in the environment, and how the robot's location is inferred based on noisy and potentially ambiguous measurements. We propose an approach for making these design decisions automatically and without expert supervision, by explicitly searching for the placement and inference strategies that, together, are optimal for a given environment. Since this search is computationally expensive, our approach encodes beacon placement as a differential neural layer that interfaces with a neural network for inference. This formulation allows us to employ standard techniques for training neural networks to carry out the joint optimization. We evaluate this approach on a variety of environments and settings, and find that it is able to discover designs that enable high localization accuracy.Comment: Appeared at 2017 International Conference on Intelligent Robots and Systems (IROS

Acoustic underwater target tracking methods using autonomous vehicles

Marine ecological research related to the increasing importance which the fisheries sector has reached so far, new methods and tools to study the biological components of our oceans are needed. The capacity to measure different population and environmental parameters of marine species allows a greater knowledge of the human impact, improving exploitation strategies of these resources. For example, the displacement capacity and mobility patterns are crucial to obtain the required knowledge for a sustainable management of fisheries. However, underwater localisation is one of the main problems which must be addressed in subsea exploration, where no Global Positioning System (GPS) is available. In addition to the traditional underwater localisation systems, such as Long BaseLine (LBL) or Ultra-Short BaseLine (USBL), new methods have been developed to increase navigation performance, flexibility, and to reduce deployment costs. For example, the Range-Only and Single-Beacon (ROSB) is based on an autonomous vehicle which localises and tracks different underwater targets using slant range measurements conducted by acoustic modems. In a moving target tracking scenario, the ROSB target tracking method can be seen as a Hidden Markov Model (HMM) problem. Using Bayes' rule, the probability distribution function of the HMM states can be solved by using different filtering methods. Accordingly, this thesis presents different strategies to improve the ROSB localisation and tracking methods for static and moving targets. Determining the optimal parameters to minimize acoustic energy use and search time, and to maximize the localisation accuracy and precision, is therefore one of the discussed aspects of ROSB. Thus, we present and compare different methods under different scenarios, both evaluated in simulations and field tests. The main mathematical notation and performance of each algorithm are presented, where the best practice has been derived. From a methodology point of view, this work advances the understanding of accuracy that can be achieved by using ROSB target tracking methods with autonomous vehicles. Moreover, whereas most of the work conducted during the last years has been focused on target tracking using acoustic modems, here we also present a novel method called the Area-Only Target Tracking (AOTT). This method works with commercially available acoustic tags, thereby reducing the costs and complexity over other tracking systems. These tags do not have bidirectional communication capabilities, and therefore, the ROSB techniques are not applicable. However, this method can be used to track small targets such as jellyfish due to the reduced tag's size. The methodology behind the area-only technique is shown, and results from the first field tests conducted in Monterey Bay area, California, are also presented.La biologia marina junt amb la importància que ha adquirit el sector pesquer, fa que es requereixin noves eines per a l’estudi dels nostres oceans. La capacitat de mesurar diferents poblacions i paràmetres ambientals d’espècies marines permet millorar el coneixement de l’impacte que l’ésser humà té sobre elles, millorant-ne els mètodes d’explotació. Per exemple, la capacitat de desplaçament i els patrons de moviment són crucials per obtenir el coneixement necessari per a una explotació sostenible de les pescaries involucrades. No obstant, la localització submarina és un dels principals problemes que s’ha de resoldre en l’explotació dels recursos submarins, on el sistema de posició global (GPS) no es pot utilitzar. A part dels mètodes tradicionals de posicionament submarí, com per exemple el Long Base-Line (LBL) o el Ultra-Short Base-Line (USBL), nous mètodes han estat desenvolupats per tal de millorar la navegació, la flexibilitat, i per reduir els costos de desplegament. Per exemple, el Range-Only and Single-Beacon (ROSB) utilitza un vehicle autònom per a localitzar i seguir diferents objectius submarins mitjançant mesures de rang realitzades a partir de mòdems acústics. En un escenari on l’objectiu a seguir és mòbil, el mètode ROSB de seguiment pot ser vist com a un problema de Hidden Markov Model (HMM). Aleshores, utilitzant la regla de Bayes, la funció de distribució de probabilitat dels estats del HMM pot ser solucionat utilitzant diferents mètodes de filtratge. Per tant, s’estudien diferents estratègies per millorar el sistema de localització i seguiment basat en ROSB, tant per objectius estàtics com mòbils. En aquesta tesis, presentem i comparem diferents mètodes utilitzant diferents escenaris, els quals s’han avaluat tant en simulacions com en proves de camp reals. A més, es presenten les principals notacions matemàtiques de cada algoritme i les millors pràctiques a utilitzar. Per tant, des d’un punt de vista metodològic, aquest treball fa un pas endavant en el coneixement de l’exactitud que es pot assolir utilitzant els mètodes de localització i seguiment d’espècies mitjançant algoritmes ROSB i vehicles autònoms. A més a més, mentre molts dels treballs realitzant durant els últims anys es centren en l’ús de mòdems acústics per al seguiment d’objectius submarins, en aquesta tesis es presenta un innovador mètode anomenat Area-Only Target Tracking (AOTT). Aquest sistema utilitza petites etiquetes acústiques comercials (tag), la qual cosa, redueix el cost i la complexitat en comparació amb els altres mètodes. Addicionalment, gràcies a l’ús d’aquests tags de dimensions reduïdes, aquest sistema permet seguir espècies marines com les meduses. La metodologia utilitzada per el mètode AOTT es mostra en aquesta tesis, on també es presenten els primers experiments realitzats a la badia de Monterey a Califòrnia

Cluster Control of a Multi-Robot Tracking Network and Tracking Geometry Optimization

The position of a moving object can be tracked in numerous ways, the simplest of which is to use a single static sensor. However, the information from a single sensor cannot be verified and may not be reliable without performing multiple measurements of the same object. When multiple static sensors are used, each sensor need only take a single measurement which can be combined with other sensor measurements to produce a more accurate position estimate. Work has been done to develop sensors that move with the tracked object, such as relative positioning, but this research takes this concept one step further; this dissertation presents a novel, highly capable strategy for utilizing a multi-robot network to track a moving target. The method optimizes the configuration of mobile tracking stations in order to produce the position estimate for a target object that yields the smallest estimation error, even when the sensor performance varies. The simulations and experiments presented here verify that the optimization process works in the real world, even under changing conditions and noisy sensor data. This demonstrates a simple, robust system that can accurately follow a moving object, as illustrated by results from both simulations and physical experiments. Further, the optimization led to a 6% improvement in the target location estimate over the non-optimized worst-case scenario tested with identical sensors at the nominal fixed radius distance of 2.83 m and even more significant improvements of over 90% at larger radial distances. This method can be applied to a wider variety of conditions than current methods since it does not require a Kalman filter and is able to find an optimal solution for the fixed radius case. To make this optimization method even more useful, it is proposed to extend the mathematical framework to n robots and extend the mathematical framework to three dimensions. It is also proposed to combine the effect of position uncertainty in the tracking system with position uncertainty of the tracking stations themselves in the analysis in order to better account for real-world conditions. Additionally, testing should be extended to different platforms with different sensors to further explore the applicability of this optimization method. Finally, it is proposed to modify the optimization method to compensate for the dynamics of the system so that sensor systems could move into an intercept course that would result in the optimal configuration about the tracked object at the desired time step. These proposals would result in a more applicable and robust system than is currently available

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Underwater Robots Part II: Existing Solutions and Open Issues

National audienceThis paper constitutes the second part of a general overview of underwater robotics. The first part is titled: Underwater Robots Part I: current systems and problem pose. The works referenced as (Name*, year) have been already cited on the first part of the paper, and the details of these references can be found in the section 7 of the paper titled Underwater Robots Part I: current systems and problem pose. The mathematical notation used in this paper is defined in section 4 of the paper Underwater Robots Part I: current systems and problem pose

Wireless Sensor Networks for Underwater Localization: A Survey

Autonomous Underwater Vehicles (AUVs) have widely deployed in marine investigation and ocean exploration in recent years. As the fundamental information, their position information is not only for data validity but also for many real-world applications. Therefore, it is critical for the AUV to have the underwater localization capability. This report is mainly devoted to outline the recent advance- ment of Wireless Sensor Networks (WSN) based underwater localization. Several classic architectures designed for Underwater Acoustic Sensor Network (UASN) are brie y introduced. Acoustic propa- gation and channel models are described and several ranging techniques are then explained. Many state-of-the-art underwater localization algorithms are introduced, followed by the outline of some existing underwater localization systems