Using side scan sonar to relative navigation

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 a sonar. Three types of sonar are discussed in this paper: 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 from 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 an 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 vertical wall. A control loop for the vehicle that provides the capacity to move along the feature/landmark from a reference distance is also discussed

Towards autonomous localization and mapping of AUVs: a survey

Purpose The main purpose of this paper is to investigate two key elements of localization and mapping of Autonomous Underwater Vehicle (AUV), i.e. to overview various sensors and algorithms used for underwater localization and mapping, and to make suggestions for future research. Design/methodology/approach The authors first review various sensors and algorithms used for AUVs in the terms of basic working principle, characters, their advantages and disadvantages. The statistical analysis is carried out by studying 35 AUV platforms according to the application circumstances of sensors and algorithms. Findings As real-world applications have different requirements and specifications, it is necessary to select the most appropriate one by balancing various factors such as accuracy, cost, size, etc. Although highly accurate localization and mapping in an underwater environment is very difficult, more and more accurate and robust navigation solutions will be achieved with the development of both sensors and algorithms. Research limitations/implications This paper provides an overview of the state of art underwater localisation and mapping algorithms and systems. No experiments are conducted for verification. Practical implications The paper will give readers a clear guideline to find suitable underwater localisation and mapping algorithms and systems for their practical applications in hand. Social implications There is a wide range of audiences who will benefit from reading this comprehensive survey of autonomous localisation and mapping of UAVs. Originality/value The paper will provide useful information and suggestions to research students, engineers and scientists who work in the field of autonomous underwater vehicles

Seabed perception and following for autonomous underwater vehicules

This paper outlines a method of seabed following designed for underwater vehicles navigating in a priori unknown environment. This method aims to fit with the path defined by the seabed shape but it also respects the manoeuvring constraints of the said vehicle. The construction of such trajectories is achieved by using geometrical functions and interpolating polynomials such as “semi-forced cubic splines” or “Hermite polynomials”. Environment modelling is carried out thanks to the bathymetric acquisitions of two embedded sounders situated in the front part of the vehicle. Finally, we present the results obtained by hydrodynamic simulation and those obtained during experimentation in the open sea.Cet article expose une méthode de suivi de fond pour véhicule sous-marin naviguant en environnement a priori inconnu. Elle repose sur l'adaptation de la trajectoire planifiée aux contraintes de manoeuvrabilité du véhicule étudié. Un algorithme basé sur des fonctions géométriques simples et sur les courbes d'interpolation telles que les « splines cubiques semi-forcées » ou les polynômes de Hermite permet de créer un trajet adapté au véhicule. Les données bathymétriques utilisées lors de ce processus proviennent de deux sondeurs placés à l'avant du véhicule. Des simulations hydrodynamiques ont été réalisées pour valider cette méthode. La validation expérimentale en milieu naturel est également présentée

Algorithme de fusion de capteurs à multiples filtres de Kalman

Afin de faire l'inspection des surfaces de béton submergées des barrages hydroélectriques, les chercheurs de l'Unité Robotique de l'Institut de recherche d'Hydro-Québec ont développé un véhicule sous-marin télé-opéré. Le véhicule identifie les défauts sur les surfaces des barrages et les reproduit dans un environnement virtuel. Pour ce faire, la position du véhicule doit toujours être connue avec précision. Ce mémoire décrit un algorithme de fusion de capteurs qui utilise de façon optimale l'information en provenance de divers capteurs afin d'obtenir la meilleure estimation possible de la position du véhicule, tant que celui-ci demeure dans un mouvement plan. L'algorithme utilise un répertoire de filtres de Kalman et offre plusieurs avantages importants par rapport au filtre de Kalman traditionnel. Selon les capteurs présents sur le véhicule, un processus de sélection parmi un répertoire de filtres de Kalman permet l'ajout et le retrait de capteurs sans aucune modification aux modèles des filtres. Les filtres sont aussi conçus de façon à traiter les données de façon asynchrone, ce qui permet de recevoir les données des différents capteurs à différentes fréquences et d'en faire une fusion optimale. De plus, l'algorithme autorise la fusion de capteurs redondants en utilisant un processus de fusion de filtres de Kalman. Finalement, une stratégie simple de filtrage adaptatif donne une plus grande flexibilité au système en permettant l'évaluation du niveau de bruit des capteurs pour lesquels ce niveau est imprécis ou inconnu. Des essais en simulation démontrent les performances des différents éléments de la stratégie de fusion de capteurs développée

Terrain Referenced Navigation Using SIFT Features in LiDAR Range-Based Data

The use of GNSS in aiding navigation has become widespread in aircraft. The long term accuracy of INS are enhanced by frequent updates of the highly precise position estimations GNSS provide. Unfortunately, operational environments exist where constant signal or the requisite number of satellites are unavailable, significantly degraded, or intentionally denied. This thesis describes a novel algorithm that uses scanning LiDAR range data, computer vision features, and a reference database to generate aircraft position estimations to update drifting INS estimates. The algorithm uses a single calibrated scanning LiDAR to sample the range and angle to the ground as an aircraft flies, forming a point cloud. The point cloud is orthorectified into a coordinate system common to a previously recorded reference of the flyover region. The point cloud is then interpolated into a Digital Elevation Model (DEM) of the ground. Range-based SIFT features are then extracted from both the airborne and reference DEMs. Features common to both the collected and reference range images are selected using a SIFT descriptor search. Geometrically inconsistent features are filtered out using RANSAC outlier removal, and surviving features are projected back to their source coordinates in the original point cloud. The point cloud features are used to calculate a least squares correspondence transform that aligns the collected features to the reference features. Applying the correspondence that best aligns the ground features is then applied to the nominal aircraft position, creating a new position estimate. The algorithm was tested on legacy flight data and typically produces position estimates within 10 meters of truth using threshold conditions

Contributions to automated realtime underwater navigation

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2012This dissertation presents three separate–but related–contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field–some have been demonstrated in all three arenas. The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors. The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current–the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework–without altering the filter structure or requiring any ad-hoc adjustments. The end result is a mathematically principled treatment of the delay that leads to more consistent estimates with lower error and uncertainty. Field results from dead reckoning aided by acoustic positioning systems demonstrate the applicability of this approach to real-world problems in underwater navigation.I have been financially supported by: the National Defense Science and Engineering Graduate (NDSEG) Fellowship administered by the American Society for Engineering Education, the Edwin A. Link Foundation Ocean Engineering and Instrumentation Fellowship, and WHOI Academic Programs office

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

Modelo de propagación acústica subacuática y su aplicación en sistemas de posicionamiento

También disponible en CD-ROM e InternetEsta tesis aborda tres importantes aspectos en lo que respecta a los modelos de propagación acústica subacuática y los sistemas de posicionamiento en estos entornos. En primer lugar se presenta un nuevo modelo de propagación acústica para entornos subacuáticos. Este modelo se basa en la técnica de trazado de rayos, que es la más indicada para señales acústicas que presenten cierto ancho de banda y superen los 200-500 Hz de frecuencia. En virtud de las ecuaciones consideradas para representar los distintos fenómenos físicos, el modelo es válido para un amplio rango de frecuencias, desde los 200 Hz hasta 1 MHz, y se puede usar para representar la propagación acústica en entornos diversos, desde aguas poco profundas a aguas profundas, así como aquellos en los que la profundidad depende de la distancia. Adicionalmente, el modelo contempla el efecto dinámico del oleaje generado por el viento como fuente de desvanecimiento y ensanchamiento Doppler en las señales reflejadas en la superficie del mar, siendo la inclusión de este efecto una novedad importante respecto a los modelos existentes. Se abordan también distintos análisis para estudiar el comportamiento de señales acústicas codificadas en entornos subacuáticos. La experiencia previa del grupo de investigación en sistemas de posicionamiento ultrasónico y en la propagación de ultrasonidos en aire ha permitido seleccionar dos esquemas de codificación que pueden ser adecuados en estos entornos. Los estudios realizados utilizando estos esquemas han servido para analizar la influencia de distintos efectos del canal, como el desvanecimiento, multicamino y el efecto del ruido, en una señal codificada. Este estudio ha permitido por tanto seleccionar el mejor esquema de codificación entre los dos estudiados, según su comportamiento en este medio, así como identificar los principales fenómenos que provocan un error en la detección de estas señales codificadas, tanto cualitativa como cuantitativamente. El modelo desarrollado se ha utilizado para el estudio de un sistema de posicionamiento acústico subacuático basado en señales GPS y señales acústicas codificadas para localizar un nodo sumergido, propuesto dentro de esta tesis. Este sistema presenta las ventajas de ser fácilmente desplegable y no necesitar una costosa fase de calibración, así como una mayor tolerancia al ruido y menor error en las detecciones de las señales acústicas que otros sistemas de similares características, gracias al uso de la codificación. Adicionalmente, se ha caracterizado el funcionamiento de dicho sistema para diversos algoritmos de posicionamiento, considerando los efectos de distintas configuraciones y fenomenología presente en el canal sobre la posición estimada del nodo sumergido