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Naval Postgraduate School Report, January 2002, This report was prepared for the Center for Autonomous Underwater Vehicle Research and funded by the Office of Naval Research (ONR) (Dr. Tom Curtin) under project Nº N0001498WR30175.

A Small Autonomous Underwater Vehicle Nnavigation System (SANS) is being developed at the Naval Postgraduate School. The SANS is an integrated Global Positioning System/Inertial Navigation System (GPS/INS) navigation system composed of low-cost and small-size components. It is designed to demonstrate the feasibility of using a low-cost strap-down inertial measurement unit (IMU) to navigate between intermittent GPS fixes. The present hardware consists of a GPS/DGPS receiver, IMU, compass, water speed sensor, water depth sensor, and a data processing computer. The software is based on a 12-state complementary filter that combines measurement data from all sensors to derive a vehicle position/orientation estimate. This paper describes hardware and software design and testing results of the SANS. It is shown that results from tilt table testing and bench testing provide an effective means for tuning filter gains. Ground vehicle testing verifies the overall functioning of the SANS and exhibits an encouraging degree of accuracy.

This paper reports on a previous experimental investigation of the Tritech ST725 high resolution sonar system used onboard the NPS Phoenix and a possible extension of the results to an underwater feature based navigation and correction system. The ST725 sonar was used in progressively complex static environments to clearly image objects. Scanline analysis of the ST72.5 data was conducted and shown to be useful in extracting stationary target information on vertically oriented mine-like objects as well as a small sphere. Raw scanline processing using a “gating and thresholding” method was used to determine range, bearing, and approximate size/orientation. Additionally, by capturing the range of the first return, the sonar was shown to be capable of emulating a “profiling” sonar. Future synthesis of known underwater features with range and bearing information and scanline analysis may provide the underwater vehicle systems designer with an alternate method of navigation. The value of this topic in the advancement of understanding underwater technology is that actual experimental data were used and useful results were obtained .

A small AUV navigation system (SANS) is being developed at the Naval Postgraduate School. The SANS is an integrated GPS/INS navigation system composed of low-cost, small-size components. It is designed to demonstrate the feasibility of using a low-cost inertial measurement unit (IMU) to navigate between intermittent GPS fixes. The paper reports improvements to the SANS hardware, latest testing results after compensating heading-dependent derivations in the TCM-2 compass measurements, and development of an asynchronous Kalman filter for improved position estimation

This paper presents preliminary experimental results on small-sized autonomous underwater vehicle navigation in shallow water environments. The vehicle was chosen to be our second-generation Ocean Voyager II which has been integrated with on-board GPS/INS sensors. These first-cut results reveal practical problems when using raw GP S fixes to perform high-precision real-time navigation. Among these, the most damaging factor is the observed correlated noise (which has a long time constant and large magnitude) embedded in the GPS data. With such disturbance, one cannot distinguish between instantaneous signal and noise over a short time scale (especially with sporadic fixes), and consequently the position estimator will be greatly biased. However, with regular incoming fixes, one can process the error between dead-reckoned and GPS signal in order to minimize the influence of the correlated noise under the assumption that any drift due to sensor bias or currents is relatively time-invariant. This processing thus enables one to estimate the drift and drift rate over time reliability for post-processed vehicle localization. In addition to the results in this paper, a differential GPS and dopper-velocity-log sensor are currently implemented on our Ocean Explorer which is expected to provide much improved navigational performance, and further at-sea results will be presented at the conference. Note that the chosen differential GPS sensor has so far demonstrated successful tracking at 2 feet below water surface, thus reinforcing a potential solution for clandestine operations.

This paper provides an overview of some of the missions and vehicle control functionality being considered for the rapidly developing technology of Autonomous Underwater Vehicles. Spawned from the availability of small embedded processors and the increasing capabilities of underwater communications, these small untethered vehicles are expected to play a role as a force multiplier in expanding our ability to survey ocean areas. Missions expected to become viable in the near future include environmental monitoring, underwater inspection, geological survey as well as the current focus on military missions in mine countermeasures and remediation.

This paper presents the use of the software programming environments PROLOG and CORAL for the implementation of the strategic level of the NPS Phoenix vehicle. Whereas PROLOG provides a rule-based mission control specification language, CORAL builds on a graphical interface to describe mission programs using Petri nets. The paper describes the interfacing of CORAL with the tactical level of the vehicle, and details the programming and execution of a vehicle mission that was run in the NPS test tank

This paper demonstrates a method to navigate an autonomous underwater vehicle in a local area using an acoustic sensor for position information derived from feature detection. A dynamic model of the vehicle response is used for control between location updates. Favorable results have been found using this approach, and precision positioning of the vehicle to centimeters has been accomplished. Another part of the problem is the need to provide a high frequency update of vehicle position in order to close the positioning servo loops. Using sonar image feature extraction is necessarily time consuming and therefore is performed in a tactical level process providing asynchronous data to the tactical navigator. It follows that some form of fast dead reckoning must be performed in the execution level either by INS/Doppler or by water speed and heading data or by a model based predictor. This paper deals with the use of a model based predictor technique where knowledge of the dynamic model of the vehicle provides state information to the vehicle positioning control function. The model uncertainty provides errors of course, but these are corrected through asynchronous updates from the feature extracted positions in the tactical level sonar manager. This concept has been verified by both simulation studies and by experimental validation with the NPS Phoenix vehicle.

Proposes the use of Prolog as a rule-based specification language for coordination of multiple control functions to perform missions with autonomous underwater vehicles. Control of both vehicle motion and mission phase logical sequencing, including specified forms of error recovery, must be accomplished. We define terms used in this type of control system and show that such systems fall into the class of hybrid controllers coupling discrete state/time independent and continuous state/continuous time elements. The software architecture to implement these systems is often composed of three levels for ease of segregation and development of functionality. The article concerns an implementation on the NPS Phoenix vehicle. Embedded in the rule body are functions that interface with the vehicle to gather sensory data and generate signals as required to trigger transitions between control functions, and to initiate commands for control functions. The same code is used for mission specification as for its execution, eliminating the question of correctness. Control of a mission segment using command generation to simultaneously drive the vehicle to a point on space and time is described with experimental results. The development of transitioning signals is discussed alongside error recovery techniques using 'guaranteed phase completion'.

Many possible Autonomous Underwater Vehicle (AUV) missions require a high degree of navigutional accuracy. The Global Positioning System (GPS) is capable of providing this accuracy. However, intermittent reception caused by either wave action or deliberate submergence will cause the loss of GPS position fix information for periods extending from several seconds to minutes. The SANS system is designed to demonstrate the feasibility of using a low-cost strapped-clown Inertial Measurement Unit (IMU) to navigate between GPS fixes. It is anticipated that navigational accuracy comparable to GPS is possible between fixes.

This paper describes recent work with the NPS PHOENIX vehicle in the further development of the intelligent control software incorporating hover control behaviors. Of particular interest is the use of the TRITECH ST1000 and ST725 high frequency sonars to provide data about the environment. Vehicle positioning is proposed to be based in a local relative sense, augmenting global positioning by LBL transponders. Motion behaviors around a target area have been implemented including diving and pitch control under thruster power; heading control at zero speed; lateral and longitudinal positioning, as well as the automatic initiation of filters as needed for target tracking. A tri-level controller architecture is discussed as part of an ongoing evaluation for coordinating the task based control of vehicle robotic behaviors.

The Naval Postgraduate School's "Phoenix" AUV has thus far been operated only in a test pool environment. In preparation for open water testing, currently planned for mid-1996, a series of towfish experiments are being conducted in Monterey Bay to investigate the feasibility of integrated GPS/INS transit mode navigation, in significant sea states, using a GPS antenna mounted only a few inches above the AUV body. In this configuration, either wave action or deliberate submergence will cause loss of GPS position fix information for periods extending from several seconds to a few minutes. The main research question being investigated is, therefore, to determine whether or not a low cost strapped down IMU can be used to navigate accurately between GPS fixes. Our goal is to achieve inertial navigation accuracy comparable to GPS accuracy during periods between successive GPS fixes. Experimental results reported in this paper indicate that this is feasible.

This paper proposes a novel approach to modeling the four quadrant dynamic response of thrusters as used for the motion control of ROV and AUV underwater vehicles. The significance is that these vehicles are small in size and respond quickly to commands. Precision in motion control will require further understanding of thruster performance than is currently available. The model includes a four quadrant mapping of the propeller blades lift and drag forces and is coupled with motor and fluid system dynamics. A series of experiments is described for both long and short period triangular, as well as square wave inputs. The model is compared favorably with experimental data for a variety of differing conditions and predicts that force overshoots are observed under conditions of rapid command changes. Use of the model will improve the control of dynamic thrust on these vehicles.

This paper describes recent work with the NPS AUV H vehicle in the further development of the execution level software to incorporate hover control behavior in the NPS hover tank. Of particular interest is the use of the ST 1000 and ST 725 high frequency sonars to provide data about the environment. Thus positioning can be accomplished without the use of beacons. Motion behaviors may be instituted that include diving and pitch control under thruster power; heading control at zero speed; lateral and longitudinal positioning, as well as the automatic initiation of filters as needed when a new target is found. A simple task level language that will be used to direct tactical level output to a port in communication with the execution level software will be given.

In the last few years, interest has grown in the use of autonomous underwater vehicles for commercial, scientific and military missions. Reliability is critical and autonomous fault detection with programmed recovery procedures have to be built into their control logic. It is important that the mission controller have information concerning the current status of the maneuverability subsystems of the vehicle to perform requested motions. The normal techniques of servo error monitors, limit and trend checks, and Kalman filter state estimators with innovations checks go a long way to providing sensor fault detection. However, the inherent capability of a vehicle to determine the state of health of its steering, diving, and speed subsystems (including fin jams) is not easily discovered by these methods. This paper discusses the use of both batch least squares and Kalman Filters for system parameter identification as a means to detect a change in performance. Applied to the experimental maneuvering responses of the NPS AUV II autonomous underwater vehicle we wish to determine the range of varability of key steering system response parameters that would form the basis of a health monitor. In this application we are not seeking parameter values for the purpose of adaptive control. Instead, we wish to determine if key parameters such as input gain have changed or are out of range.

This article describes the past accomplishments, present status, and future areas of concern for research at NPS in mission planning, mission execution, and post mission data analysis to meet the needs of future Naval Autonomous Underwater Vehicles. These vehicles are unmanned, untethered, free swimming, robotic submarines to be used for Naval missions including search, mapping, surveillance, and intervention activity. This project is joint between the Mechanical Engineering, Computer Science and Electrical and Computer Engineering Departments at the Naval Postgraduate School and is focused on a long range program to develop control technology for these vehicles. The approach taken combines computer simulation, real time robust control theory, computer architecture and code development, vehicle and component design, sonar data analysis and data visualization. Started in 1987, the major thrusts are in the areas of mission planning, both off-line and on-line, mission execution including navigation, collision avoidance, replanning, object recognition, vehicle dynamic response and motion control, real time control software architecture and implementation, and the issues of post mission data analysis.

Currently in use at the Naval Postgraduate School is a fully functional experimental autonomous underwater vehicle (AUV). The vehicle serves as a test bed for research in autonomous control, autonomous obstacle avoidance, automatic fault detection, guidance and control at slow speed. It measures over seven feet (two meters) in length and weights about 430 pounds (215 kg). Maneuvering control is provided by four rudders and dive planes, has twin propulsion motors, and onboard sensors for speed, depth, angular rates and positions and four ultrasonic sensors for range information. All shipboard action is controlled by a 68030 microprocessor running under an OS-9 operating system and a G-96 bus with code written in 'C' language. All systems are powered by a lead acid gell batteries for a test mission duration of about two hours. This paper presents some experimental modeling results upon which computer simulations of the dynamic positioning performance are based. Details are given of the vehicle modeling, the influence of thruster dynamic lags, Sliding Mode control design including integral control for the compensation of ocean current effects, and a Kalman filter design for the estimation of target range and velocity from noisy sonar data. The filter can remove transient fault anomalies which are common in sonar data.

A six degree of freedom model for the maneuvering of an underwater vehicle 15 discussed in which the hydrodynamic force coefficients are scaled from previous studies of a Swimmer Delivery Vehicle, and traditional as well as Sliding Mode controllers are designed for the steering, diving, and speed control functions. In slow speed flight control applications of this kind, difficulties arise because the system to be controlled is highly non-linear, coupled, and there is a good deal of parameter variation with operational conditions. The uncertainty in force coefficients and disturbances make control difficult. This paper presents an outline of the controller design methodology, a description of the testbed vehicle and a discussion of experimental flight control results for way point following, bottom following, and sonar mapping of the surrounding environment. It shows that a multivariable autopilot based on state feedback, designed assuming decoupled modeling, is quite satisfactory for the combined speed, steering and diving response of a slow speed AUV enabling autonomous missions to be planned.

This paper addresses the proposed use of Kalman filters and Artificial Neural Networks to provide the detection, and isolation of impending system failures. Such system health diagnosis is necessary to the overall success of mission controllers for AUVs. Two examples of network designs are given. The first addresses the identification of anomalous changes to the vehicle's acceleration behavior resulting from possible propulsion system changes of loss of propulsion efficiency from fouling. The second example relates to the identification of excessive frictional loads in the propulsion drive train that may cause motor failure. In each case, the training method and the resulting decision surface characterization of the networks so designed are given.