703 research outputs found
Particle Filter for Fault Diagnosis and Robust Navigation of Underwater Robot
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. © IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.A particle filter (PF)-based robust navigation with
fault diagnosis (FD) is designed for an underwater robot, where
10 failure modes of sensors and thrusters are considered. The
nominal underwater robot and its anomaly are described by a
switching-mode hidden Markov model. By extensively running
a PF on the model, the FD and robust navigation are achieved.
Closed-loop full-scale experimental results show that the proposed
method is robust, can diagnose faults effectively, and can
provide good state estimation even in cases where multiple faults
occur. Comparing with other methods, the proposed method can
diagnose all faults within a single structure, it can diagnose
simultaneous faults, and it is easily implemented
Underwater Cave Mapping and Reconstruction Using Stereo Vision
This work presents a systematic approach for 3-D mapping and reconstruction of underwater caves. Exploration of underwater caves is very important for furthering our understanding of hydrogeology, managing efficiently water resources, and advancing our knowledge in marine archaeology. Underwater cave exploration by human divers however, is a tedious, labor intensive, extremely dangerous operation, and requires highly skilled people. As such, it is an excellent fit for robotic technology. The proposed solution employs a stereo camera and a video-light. The approach utilizes the intersection of the cone of video-light with the cave boundaries resulting in the construction of a wire frame outline of the cave. Successive frames produce a scalable accurate point cloud which, through the use of adapted 3-D geometry reconstruction techniques, creates a fully replicated model of the cave system
Robust GNSS Carrier Phase-based Position and Attitude Estimation Theory and Applications
Mención Internacional en el título de doctorNavigation information is an essential element for the functioning of robotic platforms and
intelligent transportation systems. Among the existing technologies, Global Navigation Satellite
Systems (GNSS) have established as the cornerstone for outdoor navigation, allowing for
all-weather, all-time positioning and timing at a worldwide scale. GNSS is the generic term
for referring to a constellation of satellites which transmit radio signals used primarily for
ranging information. Therefore, the successful operation and deployment of prospective
autonomous systems is subject to our capabilities to support GNSS in the provision of
robust and precise navigational estimates.
GNSS signals enable two types of ranging observations: –code pseudorange, which is a
measure of the time difference between the signal’s emission and reception at the satellite
and receiver, respectively, scaled by the speed of light; –carrier phase pseudorange, which
measures the beat of the carrier signal and the number of accumulated full carrier cycles.
While code pseudoranges provides an unambiguous measure of the distance between satellites
and receiver, with a dm-level precision when disregarding atmospheric delays and clock offsets,
carrier phase measurements present a much higher precision, at the cost of being ambiguous by
an unknown number of integer cycles, commonly denoted as ambiguities. Thus, the maximum
potential of GNSS, in terms of navigational precision, can be reach by the use of carrier phase
observations which, in turn, lead to complicated estimation problems.
This thesis deals with the estimation theory behind the provision of carrier phase-based
precise navigation for vehicles traversing scenarios with harsh signal propagation conditions.
Contributions to such a broad topic are made in three directions. First, the ultimate positioning
performance is addressed, by proposing lower bounds on the signal processing realized at the
receiver level and for the mixed real- and integer-valued problem related to carrier phase-based
positioning. Second, multi-antenna configurations are considered for the computation of a
vehicle’s orientation, introducing a new model for the joint position and attitude estimation
problems and proposing new deterministic and recursive estimators based on Lie Theory.
Finally, the framework of robust statistics is explored to propose new solutions to code- and
carrier phase-based navigation, able to deal with outlying impulsive noises.La información de navegación es un elemental fundamental para el funcionamiento de sistemas
de transporte inteligentes y plataformas robóticas. Entre las tecnologías existentes, los
Sistemas Globales de Navegación por Satélite (GNSS) se han consolidado como la piedra
angular para la navegación en exteriores, dando acceso a localización y sincronización temporal
a una escala global, irrespectivamente de la condición meteorológica. GNSS es el término
genérico que define una constelación de satélites que transmiten señales de radio, usadas
primordinalmente para proporcionar información de distancia. Por lo tanto, la operatibilidad y
funcionamiento de los futuros sistemas autónomos pende de nuestra capacidad para explotar
GNSS y estimar soluciones de navegación robustas y precisas.
Las señales GNSS permiten dos tipos de observaciones de alcance: –pseudorangos de
código, que miden el tiempo transcurrido entre la emisión de las señales en los satélites y su
acquisición en la tierra por parte de un receptor; –pseudorangos de fase de portadora, que
miden la fase de la onda sinusoide que portan dichas señales y el número acumulado de ciclos
completos. Los pseudorangos de código proporcionan una medida inequívoca de la distancia
entre los satélites y el receptor, con una precisión de decímetros cuando no se tienen en
cuenta los retrasos atmosféricos y los desfases del reloj. En contraposición, las observaciones
de la portadora son super precisas, alcanzando el milímetro de exactidud, a expensas de ser
ambiguas por un número entero y desconocido de ciclos. Por ende, el alcanzar la máxima
precisión con GNSS queda condicionado al uso de las medidas de fase de la portadora, lo
cual implica unos problemas de estimación de elevada complejidad.
Esta tesis versa sobre la teoría de estimación relacionada con la provisión de navegación
precisa basada en la fase de la portadora, especialmente para vehículos que transitan escenarios
donde las señales no se propagan fácilmente, como es el caso de las ciudades. Para ello,
primero se aborda la máxima efectividad del problema de localización, proponiendo cotas
inferiores para el procesamiento de la señal en el receptor y para el problema de estimación
mixto (es decir, cuando las incógnitas pertenecen al espacio de números reales y enteros). En
segundo lugar, se consideran las configuraciones multiantena para el cálculo de la orientación de un vehículo, presentando un nuevo modelo para la estimación conjunta de posición y
rumbo, y proponiendo estimadores deterministas y recursivos basados en la teoría de Lie. Por
último, se explora el marco de la estadística robusta para proporcionar nuevas soluciones de
navegación precisa, capaces de hacer frente a los ruidos atípicos.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José Manuel Molina López.- Secretario: Giorgi Gabriele.- Vocal: Fabio Dovi
Improving Self-Consistency in Underwater Mapping Through Laser-Based Loop Closure (Extended)
Accurate, self-consistent bathymetric maps are needed to monitor changes in
subsea environments and infrastructure. These maps are increasingly collected
by underwater vehicles, and mapping requires an accurate vehicle navigation
solution. Commercial off-the-shelf (COTS) navigation solutions for underwater
vehicles often rely on external acoustic sensors for localization, however
survey-grade acoustic sensors are expensive to deploy and limit the range of
the vehicle. Techniques from the field of simultaneous localization and
mapping, particularly loop closures, can improve the quality of the navigation
solution over dead-reckoning, but are difficult to integrate into COTS
navigation systems. This work presents a method to improve the self-consistency
of bathymetric maps by smoothly integrating loop-closure measurements into the
state estimate produced by a commercial subsea navigation system. Integration
is done using a white-noise-on-acceleration motion prior, without access to raw
sensor measurements or proprietary models. Improvements in map self-consistency
are shown for both simulated and experimental datasets, including a 3D scan of
an underwater shipwreck in Wiarton, Ontario, Canada.Comment: 26 pages, 18 figures. V2 correct Table III x2 parameter values, Table
VIII 'INS' values, and equation A.2
Identification of multi-faults in GNSS signals using RSIVIA under dual constellation
This publication presents the development of integrity monitoring and fault detection and exclusion (FDE) of pseudorange measurements, which are used to aid a tightly-coupled navigation filter. This filter is based on an inertial measurement unit (IMU) and is aided by signals of the global navigation satellite system (GNSS). Particularly, the GNSS signals include global positioning system (GPS) and Galileo. By using GNSS signals, navigation systems suffer from signal interferences resulting in large pseudorange errors. Further, a higher number of satellites with dual-constellation increases the possibility that satellite observations contain multiple faults. In order to ensure integrity and accuracy of the filter solution, it is crucial to provide sufficient fault-free GNSS measurements for the navigation filter. For this purpose, a new hybrid strategy is applied, combining conventional receiver autonomous integrity monitoring (RAIM) and innovative robust set inversion via interval analysis (RSIVIA). To further improve the performance, as well as the computational efficiency of the algorithm, the estimated velocity and its variance from the navigation filter is used to reduce the size of the RSIVIA initial box. The designed approach is evaluated with recorded data from an extensive real-world measurement campaign, which has been carried out in GATE Berchtesgaden, Germany. In GATE, up to six Galileo satellites in orbit can be simulated. Further, the signals of simulated Galileo satellites can be manipulated to provide faulty GNSS measurements, such that the fault detection and identification (FDI) capability can be validated. The results show that the designed approach is able to identify the generated faulty GNSS observables correctly and improve the accuracy of the navigation solution. Compared with traditional RSIVIA, the designed new approach provides a more timely fault identification and is computationally more efficient
Simultaneous Trajectory Estimation and Mapping for Autonomous Underwater Proximity Operations
Due to the challenges regarding the limits of their endurance and autonomous
capabilities, underwater docking for autonomous underwater vehicles (AUVs) has
become a topic of interest for many academic and commercial applications.
Herein, we take on the problem of state estimation during an autonomous
underwater docking mission. Docking operations typically involve only two
actors, a chaser and a target. We leverage the similarities to proximity
operations (prox-ops) from spacecraft robotic missions to frame the diverse
docking scenarios with a set of phases the chaser undergoes on the way to its
target. We use factor graphs to generalize the underlying estimation problem
for arbitrary underwater prox-ops. To showcase our framework, we use this
factor graph approach to model an underwater homing scenario with an active
target as a Simultaneous Localization and Mapping problem. Using basic AUV
navigation sensors, relative Ultra-short Baseline measurements, and the
assumption of constant dynamics for the target, we derive factors that
constrain the chaser's state and the position and trajectory of the target. We
detail our front- and back-end software implementation using open-source
software and libraries, and verify its performance with both simulated and
field experiments. Obtained results show an overall increase in performance
against the unprocessed measurements, regardless of the presence of an
adversarial target whose dynamics void the modeled assumptions. However,
challenges with unmodeled noise parameters and stringent target motion
assumptions shed light on limitations that must be addressed to enhance the
accuracy and consistency of the proposed approach.Comment: 19 pages, 14 figures, submitted to the IEEE Journal of Oceanic
Engineerin
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