Surface Craft Research Articles

Trajectory Tracking Nonlinear Model Predictive Control for Autonomous Surface Craft

This paper presents a solution to the problem of trajectory tracking control for autonomous surface craft (ASC) in the presence of ocean currents. The proposed solution is rooted in nonlinear model predictive control (NMPC) techniques and addresses explicitly state and input constraints. Whereas state saturation constraints are added to the underlying optimization cost functional as penalties, input saturation constraints are made intrinsic to the nonlinear model used in the optimization problem, thus reducing the computational burden of the resulting NMPC algorithm. Simulation results, obtained with a nonlinear dynamic model of a prototype ASC, show that the NMPC strategy adopted yields good performance in the presence of constant currents. Experimental results are also provided to validate the real-time implementation of the NMPC techniques for ASCs.

Aspect-dependent acoustic characterization of an underway autonomous underwater vehicle

Acoustic emissions emitted by an underway REMUS-100 autonomous underwater vehicle (AUVs) are analyzed with array beamforming. Characterizing emissions of underway AUVs is challenging due to a variety of factors such as low source levels of some vehicle types, continually varying propagation conditions, and inherent uncertainties in vehicle location. While aspect-dependent spectral and source level emissions are available for a wide range of surface craft types, few articles have analyzed these for underway AUVs. Array beamforming is a known method of increasing gain of a weak signal in the presence of interference and noise, and propagation modeling tools can provide estimates of transmission loss between a source and receiver. These techniques are used to measure the aspect-dependent source level and spectral content from the propulsion system of a REMUS-100 AUV deployed near a fixed array near Honolulu Harbor, Hawaii, by fusing measured acoustic data with multi-sensor navigational records recorded on the vehicle. As AUVs become more widely used, characterizing their acoustic radiation will help predict how these platforms interact with and impact the environments in which they are deployed.

Position and Velocity Filters for ASC/I-AUV Tandems Based on Single Range Measurements

This paper proposes novel cooperative navigation solutions for an Intervention Autonomous Underwater Vehicle (I-AUV) working in tandem with an Autonomous Surface Craft (ASC). The I-AUV is assumed to be moving in the presence of constant unknown ocean currents, and aims to estimate its position relying on measurements of its range to the ASC. Two different scenarios are considered: in the first scenario, the ASC transmits its position and velocity to the I-AUV, and the I-AUV has access to readings of its velocity relative to the water. In the second scenario, the ASC transmits only its position, and the I-AUV has access to measurements of its velocity relative to the ASC. In both cases, it is assumed that an Attitude and Heading Reference System (AHRS) mounted on-board the I-AUV provides measurements of its attitude and angular velocity. A sufficient condition for observability and a method for designing state observers with Globally Asymptotically Stable (GAS) error dynamics are presented for both problems. Finally, simulation results are included and discussed to assess the performance of the proposed solutions in the presence of measurement noise.

Decentralized Extended Information Filter for Single-Beacon Cooperative Acoustic Navigation: Theory and Experiments

We report a decentralized extended information filter (DEIF) algorithm designed for single-beacon cooperative acoustic navigation of one or more client underwater vehicles. In single-beacon cooperative acoustic navigation, ranges and state information from a single reference source (the server) are used to improve localization and navigation of an underwater vehicle (the client). The ranges and state information are obtained using underwater acoustic modems and a synchronous-clock time-of-flight paradigm. Apart from the server's acoustic data broadcasts, the client has no access to the server's position or sensor measurements. We show that at the instance of each range measurement update, the DEIF algorithm yields identical results for the current vehicle state estimate as the corresponding centralized extended information filter (CEIF), which fully tracks the joint probability distribution between the server and client. We compare the state estimation results of the DEIF algorithm with that of a CEIF and three other filters reported in the literature. The evaluation is performed using both simulated data and an experimental dataset comprised of one surface craft and two autonomous underwater vehicles.

Small boat localization using adaptive three-dimensional beamforming on a tetrahedral and vertical line array

Passive acoustic detection and localization of small surface craft has a number of practical applications, such as monitoring and protecting sensitive marine habitats. Moored passive equipment can be cumbersome to deploy and communicate with, so AUV-mounted devices are being investigated as an alternative. The GLASS’12 experiment was designed to assess the feasibility of using a hybrid autonomous underwater vehicle outfitted with a compact volumetric nose array as a data collection platform. The array consisted of five vertical elements and 4 in a tetrahedral arrangement, and the hybrid underwater vehicle had the capability operating in either glider or propeller-driven modes. The rigid design of the array minimized element location mismatch and enabled the use of aggressive adaptive beamforming in 3-D. This facilitated isolation of broadband multipath arrivals originating from the motor of a small rubber boat. Cross-correlation of beams enabled the time-lag between the arrivals to be measured, which, in turn yielded information about the target range. The underlying formulation bears similarity to the passive fathometer [J. Acoust. Soc. Am. 120(3) (2006)], which exploits surface wave noise rather than ship noise. This presentation will focus on the array beamforming and potential applications for localization and environmental sensing.

Semiphysical Modelling of the Nonlinear Dynamics of a Surface Craft with LS-SVM

One of the most important problems in many research fields is the development of reliable mathematical models with good predictive ability to simulate experimental systems accurately. Moreover, in some of these fields, as marine systems, these models play a key role due to the changing environmental conditions and the complexity and high cost of the infrastructure needed to carry out experimental tests. In this paper, a semiphysical modelling technique based on least-squares support vector machines (LS-SVM) is proposed to determine a nonlinear mathematical model of a surface craft. The speed and steering equations of the nonlinear model of Blanke are determined analysing the rudder angle, surge and sway speeds, and yaw rate from real experimental data measured from a zig-zag manoeuvre made by a scale ship. The predictive ability of the model is tested with different manoeuvring experimental tests to show the good performance and prediction ability of the model computed.

Instantaneous Global Navigation Satellite System (GNSS)-Based Attitude Determination for Maritime Applications

Global Navigation Satellite System (GNSS) is a valuable technology for a large number of maritime applications. Other than providing the absolute positioning service, it aids many demanding applications, such as precise docking, formation of surface craft, autonomous vehicles, sinkage monitoring, etc. GNSS carrier-phase-based algorithms provide high-precision positioning solutions, but an integer number of cycles inherent to the observed signal have to be resolved. A newly developed GNSS carrier-phase ambiguity resolution method is tested. The new method solves for the unknown number of integer cycles by exploiting the known placement of the GNSS antennas aboard the vessel. The a priori information on the antennas baseline separation is employed as a hard constraint. A simplified (linearized) version of the method, suitable for large vessels, is also analyzed. The new method was tested against the most challenging scenario when processing GNSS data: single-frequency, single-epoch, unaided ambiguity resolution. Through different tests, the high performance of the new method is demonstrated: high fixing rate, large robustness, and short time-to-fix after initialization, cycle slips, and/or loss of locks. Considerations about the wide spectra of maritime applications are given, and a specific experiment is carried out to demonstrate the capabilities of the method for navigation in shallow waters.

An Underwater Acoustic Localisation System for Assisted Human Diving Operations

In this paper we present a solution to the problem of estimating the position and orientation of a moving underwater object using acoustic range measurements relative to moving surface objects that have access to a global navigation system. We start with the description of a standard GPS Intelligent Buoy system (GIB) that employs an Extended Kalman Filter (EKF); then we adapt this principle for the concrete task of tracking a human diver utilizing moving autonomous surface crafts. To this effect, we will introduce an advanced measurement system that improves significantly the estimation quality especially in the described scenario. The paper concludes with a short description of the first sea trials of the new developed system.

Attitude Filter for Intervention-AUVs working in Tandem with Autonomous Surface Craft

This paper presents the design, analysis, and performance evaluation of an attitude filter for an Intervention-Autonomous Underwater Vehicle (I-AUV) working in tandem with an Autonomous Surface Craft (ASC). In the proposed framework, an ASC aids an I-AUV to determine its attitude by providing an inertial reference direction vector through acoustic modem communications, which is measured in body-fixed coordinates by an Ultra-Short Baseline (USBL) device. The specificity of the intervention mission to be carried out, near structures that distort the Earth magnetic field, renders on-board magnetometers unusable for attitude determination. The solution presented herein includes the estimation of rate gyros biases, yielding globally asymptotically stable error dynamics under some mild restrictions on the vehicle team configurations. The feasibility and performance of the proposed architecture is assessed resorting to numerical simulations with realistic sensor noise.

Attitude Estimation for Intervention-AUVs Working in Tandem with Autonomous Surface Craft

This paper presents the design, analysis, and performance evaluation of an attitude filter for an Intervention- Autonomous Underwater Vehicle (I-AUV) working in tandem with an Autonomous Surface Craft (ASC). In the proposed framework, an ASC aids an I-AUV to determine its attitude by providing an inertial reference direction vector through acoustic modem communications, which is measured in body-fixed coordinates by an Ultra-Short Baseline (USBL) device. The specificity of the intervention mission to be carried out, near structures that distort the Earth magnetic field, renders on-board magnetometers unusable for attitude determination. The solution presented herein includes the estimation of rate gyros biases, yielding globally asymptotically stable error dynamics under some mild restrictions on the vehicle team configurations. The feasibility and performance of the proposed architecture is assessed resorting to numerical Monte-Carlo simulations with realistic sensor noise, and transmission delays and limited bandwidth of the acoustic modems.

An integrated multi-sensor data fusion algorithm and autopilot implementation in an uninhabited surface craft

Unmanned surface vehicles (USVs) are able to accomplish difficult and challenging tasks both in civilian and defence sectors without endangering human lives. Their ability to work round the clock makes them well-suited for matters that demand immediate attention. These issues include but not limited to mines countermeasures, measuring the extent of an oil spill and locating the source of a chemical discharge. A number of USV programmes have emerged in the last decade for a variety of aforementioned purposes. Springer USV is one such research project highlighted in this paper. The intention herein is to report results emanating from data acquired from experiments on the Springer vessel whilst testing its advanced navigation, guidance and control (NGC) subsystems. The algorithms developed for these systems are based on soft-computing methodologies. A novel form of data fusion navigation algorithm has been developed and integrated with a modified optimal controller. Experimental results are presented and analysed for various scenarios including single and multiple waypoints tracking and fixed and time-varying reference bearings. It is demonstrated that the proposed NGC system provides promising results despite the presence of modelling uncertainty and external disturbances.

INS/GPS Aided by Frequency Contents of Vector Observations With Application to Autonomous Surface Crafts

This paper presents a high-accuracy, multirate inertial navigation system (INS) integrating global positioning system (GPS) measurements and advanced vector aiding techniques for precise position and attitude estimation of autonomous surface crafts (ASCs). Designed to be implemented and tested in the DELFIMx catamaran developed at ISR/IST, the navigation system comprises an advanced inertial integration algorithm to account for coning and sculling motions, combined with an extended Kalman filter (EKF) for inertial sensor error compensation. Aiding gravitational observations are optimally exploited in the EKF, by deriving a sensor integration technique that takes into account the vehicle's dynamics bandwidth information to properly trace measurement disturbances and extract the relevant sensor information. The proposed aiding technique and the performance of the navigation system are assessed using experimental data obtained at seatrials with a low-cost hardware architecture installed on-board the DELFIMx platform. It is shown that the low frequency information embodied in pendular measurements improves the compensation of inertial sensor bias and noise, and consequently enhances the performance of position and attitude estimation. The overall improvements obtained with the vector aiding observations are also illustrated for the case of GPS signal outage, emphasizing the extended autonomy of the navigation system with respect to position aiding.

Discrete-Time Complementary Filters for Attitude and Position Estimation: Design, Analysis and Experimental Validation

This paper develops a navigation system based on complementary filtering for position and attitude estimation, with application to autonomous surface crafts. Using strapdown inertial measurements, vector observations, and global positioning system (GPS) aiding, the proposed complementary filters provide attitude estimates in Euler angles representation and position estimates in Earth frame coordinates, while compensating for rate gyro bias. Stability and performance properties of the proposed filters under operating conditions usually found in oceanic applications are derived, and the tuning of the filter parameters in the frequency domain is emphasized. The small computational requirements of the proposed navigation system make it suitable for implementation on low-power hardware and using low-cost sensors, providing a simple yet effective multirate architecture suitable to be used in applications with autonomous vehicles. Experimental results obtained in real time with an implementation of the proposed algorithm running on-board the DELFIMx catamaran, an autonomous surface craft developed at ISR/IST for automatic marine data acquisition, are presented and discussed.

Cooperative AUV Navigation using a Single Maneuvering Surface Craft

In this paper we describe the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft. Maintaining accurate localization of an AUV is difficult because electronic signals, such as GPS, are highly attenuated by water. The usual solution to the problem is to utilize expensive navigation sensors to slow the rate of dead-reckoning divergence. We investigate an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV. This approach uses the Woods Hole Oceanographic Institution (WHOI) acoustic modem to exchange vehicle location estimates while simultaneously estimating inter-vehicle range. A study of the system observability is presented so as to motivate both the choice of filtering approach and surface vehicle path planning. The first contribution of this paper is to the presentation of an experiment in which an extended Kalman filter (EKF) implementation of the concept ran online on-board an OceanServer Iver2 AUV while supported by an autonomous surface vehicle moving adaptively. The second contribution of this paper is to provide a quantitative performance comparison of three estimators: particle filtering (PF), non-linear least-squares optimization (NLS), and the EKF for a mission using three autonomous surface craft (two operating in the AUV role). Our results indicate that the PF and NLS estimators outperform the EKF, with NLS providing the best performance.

Unified command and control for heterogeneous marine sensing networks

AbstractSuccessful command and control (C2) of autonomous vehicles poses challenges that are unique to the marine environment, primarily highly restrictive acoustic communications throughput. To address this, the Unified C2 architecture presented here uses a highly compressed short message encoding scheme (Dynamic Compact Control Language or DCCL) to transfer commands and receive vehicle status. DCCL is readily reconfigurable to provide the flexibility needed to change commands on short notice. Furthermore, operation of multiple types of vehicles requires a C2 architecture that is both scalable and flexible to differences among platform hardware and abilities. The Unified C2 architecture uses the MOOS‐IvP autonomy system to act as a “backseat driver” of the vehicle. This provides a uniform interface to the control system on all the vehicles. Also, a hierarchical configuration system is used to allow single changes in configuration to propagate to all vehicles in operation. Status data from all vehicles are displayed visually using Google Earth, which also allows a rapid meshing of data from other sources (sensors, automatic identification system, radar, satellites) from within, as well as outside of, the MOOS‐IvP architecture. Results are presented throughout from the CCLNET08, SQUINT08, GLINT08, GLINT09, SWAMSI09, and DURIP09 experiments involving robotic marine autonomous surface craft (ASCs) and Bluefin, OceanServer, and NATO Undersea Research Centre (NURC) autonomous underwater vehicles (AUVs). © 2010 Wiley Periodicals, Inc.

TRIDENT: A Framework for Autonomous Underwater Intervention Missions with Dexterous Manipulation Capabilities

TRIDENT is a STREP project recently approved by the European Commission whose proposal was submitted to the ICT call 4 of the 7th Framework Program. The project proposes a new methodology for multipurpose underwater intervention tasks. To that end, a cooperative team formed with an Autonomous Surface Craft and an Intervention Autonomous Underwater Vehicle will be used. The proposed methodology splits the mission in two stages mainly devoted to survey and intervention tasks, respectively. The project brings together research skills specific to the marine environments in navigation and mapping for underwater robotics, multi-sensory perception, intelligent control architectures, vehicle-manipulator systems and dexterous manipulation. TRIDENT is a three years project and its start is planned by first months of 2010.

Cooperative Motion Control of Multiple Autonomous Marine Vehicles: Collision Avoidance in Dynamic Environments

This paper addresses the problem of cooperative motion control (CMC) of multiple autonomous marine vehicles, taking explicitly into account collision avoidance in dynamic environments. A Collision Avoidance System (CAS) for a CMC architecture is proposed that consists of two subsystems: Collision Prediction and Collision Avoidance. Collision Prediction aims at estimating the most probable trajectory of a given obstacle. To this effect, a bank of Kalman filters are run in parallel, with each filter using a different plausible model for obstacle motion. The most probable model is chosen according to a decision algorithm. Each of the vehicle trajectories is then checked for possible collision with the obstacle. Should the possibility of a collision occur, Collision Avoidance is achieved either by controlling the speed of each vehicle along its assigned path or through path re-planing using harmonic potential fields. Because group coordination must be taken into consideration, collision avoidance is implemented using a decentralized system that is suited for multiple heterogeneous vehicles. The paper summarizes the key concepts and the methodology used to implement a Collision Avoidance System for teams of vehicles. The efficacy of the system is assessed in simulation with dynamic models of a group of marine surface craft using NetMarSys, a Cooperative Motion Control Simulator developed at ISR/IST.

Mechanical properties of friction stir welded aluminum alloys 5083 and 5383

The use of high-strength aluminum alloys is increasing in shipbuilding industry, particularly for the design and construction of war ships, littoral surface craft and combat ships, and fast passenger ships. While various welding methods are used today to fabricate aluminum ship structures, namely gas metallic arc welding (GMAW), laser welding and friction stir welding (FSW), FSW technology has been recognized to have many advantages for the construction of aluminum structures, as it is a low-cost welding process. In the present study, mechanical properties of friction stir welded aluminum alloys are examined experimentally. Tensile testing is undertaken on dog-bone type test specimen for aluminum alloys 5083 and 5383. The test specimen includes friction stir welded material between identical alloys and also dissimilar alloys, as well as unwelded (base) alloys. Mechanical properties of fusion welded aluminum alloys are also tested and compared with those of friction stir welded alloys. The insights developed from the present study are documented together with details of the test database. Part of the present study was obtained from the Ship Structure Committee project SR-1454 (Paik, 2009), jointly funded by its member agencies.

Cooperative Localization for Autonomous Underwater Vehicles

This paper describes an algorithm for distributed acoustic navigation for Autonomous Underwater Vehicles (AUVs). Whereas typical AUV navigation systems utilize pre-calibrated arrays of static transponders, our work seeks to create a fully mobile network of AUVs that perform acoustic ranging and data exchange with one another to achieve cooperative positioning for extended duration missions over large areas. The algorithm enumerates possible solutions for the AUV trajectory based on dead-reckoning and range-only measurements provided by acoustic modems that are mounted on each vehicle, and chooses the trajectory via minimization of a cost function based on these constraints. The resulting algorithm is computationally efficient, meets the strict bandwidth requirements of available AUV modems, and has potential to scale well to networks of large numbers of vehicles. The method has undergone extensive experimentation, and results from three different scenarios are reported in this paper, each of which utilizes MIT SCOUT Autonomous Surface Craft (ASC) as convenient platforms for testing. In the first experiment, we utilize three ASCs, each equipped with a Woods Hole acoustic modem, as surrogates for AUVs. In this scenario, two ASCs serve as Communication/Navigation Aids (CNAs) for a third ASC that computes its position based exclusively on GPS positions of the CNAs and acoustic range measurements between platforms. In the second scenario, an undersea glider is used in conjunction with two ASCs serving as CNAs. Finally, in the third experiment, a Bluefin12 AUV serves as the target vehicle. All three experiments demonstrate the successful operation of the technique with real ocean data.

Acoustic signal processing methods for detecting intrusions and threats in the battlespace

The processing of acoustic sensor data enables the detection, classification, localization and tracking of intrusions and threats in the battlespace. Initially, passive acoustic signal processing methods that are used in unattended ground sensor networks and onboard uninhabited aerial vehicles are reviewed. These methods process radiated noise (acoustic signature) data generated by sources of military interest and extract tactical information on air and ground vehicles as well as direct (rifle) and indirect (artillery/mortar) fire weapons. Examples of applying various passive acoustic signal processing methods to real sensor data collected during field experiments are presented. The tactical parameter estimates derived from these acoustic methods are then compared with ground truth data. Next, the application of active sonar signal processing to the automatic detection and tracking of a fast inshore watercraft in a cluttered harbor environment is demonstrated using real data. The air bubbles associated with wakes from high‐speed surface craft are highly reflective of incident high frequency sonar signal transmissions. Finally, various high frequency active sonar methods that use both real and synthetic apertures to image sea mines are reviewed and demonstrated.