Navigation and Motion Control Systems of the Autonomous Underwater Vehicle (original) (raw)
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The Institute of Ocean and Systems Engineering at Florida Atlantic University is currently developing a new generation of autonomous underwater vehicle (AUV), the MiniAUV. One major objective in its development is to provide a higher degree of navigation accuracy than the former generation of vehicle, the Ocean Explorer could achieve. To this end an embedded, real-time inertial navigation system has been developed for the past two years. It integrates high-precision navigation sensors while performing high frequency filtering and extensive data fusion methods, including a standard and an extended Kalman filter. This paper presents both the hardware and software architectures of the navigation system. Although the system is not fully operational yet, preliminary results were produced and are presented to illustrate the different features of the system
An inertial navigation system for small autonomous underwater vehicles
Advanced Robotics, 2001
A Small A U V Navigation System (S A N S) is being developed at the Naval Postgraduate School. The SANS is an integrated GPS/INS navigation system composed of low-cost, small-size components. I t is designed to demonstrate the feasibility of using a low-cost Inertial Measurement Unit (IMU) to navigate between intermittent G P S fixes. This paper reports recent 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.
Enhancement of the inertial navigation system for the Morpheus autonomous underwater vehicles
IEEE Journal of Oceanic Engineering, 2001
This paper presents the design and development of an enhanced inertial navigation system that is to be integrated into the Morpheus autonomous underwater vehicle at Florida Atlantic University. The inertial measurement unit is based on the off-the-shelf Honeywell HG1700-AG25 3-axis ring-laser gyros and three-axis accelerometers and is aided with ground speed measurements obtained using an RDI Doppler-velocity-log sonar. An extended Kalman filter has been developed, which fuses together asynchronously the inertial and Doppler data, as well as the differential global positioning system positional fixes whenever they are available. A complementary filter was implemented to provide a much smoother and stable attitude estimate. Thus far, preliminary study has been made on characterizing the inertial navigation system-based navigation system performance, and the corresponding results and analyzes are provided in this paper.
IEEE Journal of Oceanic Engineering, 2007
This paper presents an integrated navigation system for underwater vehicles to improve the performance of a conventional inertial acoustic navigation system by introducing range measurement. The integrated navigation system is based on a strapdown inertial navigation system (SDINS) accompanying range sensor, Doppler velocity log (DVL), magnetic compass, and depth sensor. Two measurement models of the range sensor are derived and augmented to the inertial acoustic navigation system, respectively. A multirate extended Kalman filter (EKF) is adopted to propagate the error covariance with the inertial sensors, where the filter updates the measurement errors and the error covariance and corrects the system states when the external measurements are available. This paper demonstrates the improvement on the robustness and convergence of the integrated navigation system with range aiding (RA). This paper used experimental data obtained from a rotating arm test with a fish model to simulate the navigational performance. Strong points of the navigation system are the elimination of initial position errors and the robustness on the dropout of acoustic signals. The convergence speed and conditions of the initial error removal are examined with Monte Carlo simulation. In addition, numerical simulations are conducted with the six-degrees-of-freedom (6-DOF) equations of motion of an autonomous underwater vehicle (AUV) in a boustrophedon survey mode to illustrate the effectiveness of the integrated navigation system.
Inertial Sensor Self-Calibration Module for Autonomous Underwater Vehicle Navigation
Evolution in Electrical and Electronic Engineering, 2021
The Autonomous Underwater Vehicles (AUV) industry is growing dramatically with the increase in the reliability and technical abilities of these vehicles. The vehicles require autonomous guidance and control system in order to perform underwater tasks. The Inertial Sensor Self-Calibration Navigation module is the important mission module that can be implemented into the navigation target, it permits the vehicle to follow preprogrammed trajectories wherever and whenever required. Without this module, the vehicle will not be able to achieve the desired mission. In this work, the Mission module need to be able to identify the task, detect the target, coordinate the state of AUV (attain desired height and yaw angle) and makes decision on path based on mission time elapsed. To navigate this Autonomous Underwater Vehicle (AUV), the navigation module selects Inertial Navigation System (INS). This navigation system used computers, accelerometers, gyroscopes, and sometimes magnetic sensors to calculate the dead reckoning, orientation and velocity (movement direction and speed) moving objects without external reference requirements. The AUV was able to navigate underwater and track underwater object without the need of operator assistance.
Development of a Navigation Algorithm for Autonomous Underwater Vehicles
IFAC-PapersOnLine, 2015
In this paper, the authors present an underwater navigation system for Autonomous Underwater Vehicles (AUVs) which exploits measurements from an Inertial Measurement Unit (IMU), a Pressure Sensor (PS) for depth and the Global Positioning System (GPS, used during periodic and dedicated resurfacings) and relies on either the Extended Kalman Filter (EKF) or the Unscented Kalman Filter (UKF) for the state estimation. Both (EKF and UKF) navigation algorithms have been validated through experimental navigation data related to some sea tests performed in La Spezia (Italy) with one of Typhoon class vehicles during the NATO CommsNet13 experiment (held in September 2013) and through Ultra-Short BaseLine (USBL) fixes used as a reference (ground truth). Typhoon is an AUV designed by the Department of Industrial Engineering of the Florence University for exploration and surveillance of underwater archaeological sites in the framework of the Italian THESAURUS project and the European ARROWS project. The obtained results have demonstrated the effectiveness of both navigation algorithms and the superiority of the UKF (very suitable for AUV navigation and, up to now, still not used much in this field) without increasing the computational load (affordable for on-line on-board AUV implementation).
A real-time navigation system for autonomous underwater vehicle
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2014
This paper focuses on the study and implementation of a navigation system in order to estimate position, velocity and attitude of an autonomous underwater vehicle, AUV. The extended Kalman filter, EKF, is investigated for the fusion of the sample data from different sensors: the strapdown inertial measurement unit, magnetic compass, Doppler velocity log, depth sensor, and an acoustic positioning system. Results are applied to the development of a navigation system for the Pirajuba AUV, an autonomous underwater vehicle that is being developed at the mechatronics department of the Politechnic School of the University of Sao Paulo. The navigation system is composed by off the shelf components integrated in a CAN based network. On the hardware platform, a software architecture is implemented based on free and largely known tools, like C language, and the GNU compiler. The real-time performance of the filter is validated through laboratory and field tests. The last one includes experiment using an automobile vehicle. Results in the field tests indicate the correct choice for the system model assumed in the EKF, and the good performance of the navigation algorithm in real-time. During the simulation, the accuracy obtained in the estimation of the AUV position and attitude are satisfactory.
Recent Advances in Navigation of Underwater Remotely Operated Vehicles
2013
A review of the most significant technical papers related to the navigation of underwater remotely operated vehicles is presented, with special interest in aided inertial navigation. Sensors used for implementation, fusion algorithms and models that describe the navigation systems are presented. From this review, it was concluded that the implementation of an estimator, based on the vehicle kinematic and dynamic models, limits the growth of the estimated error, even in case that the only available information is that provided by an inertial measurement unit.
The need to successfully navigate in an underwater environment is rapidly becoming an important concern in the 1990's. This paper presents the development of an integrated navigation system for autonomous underwater vehicles (AUV) using GPS, INS and sonar. This paper discusses the existing problems with sub-sea navigation, the motivation for an integrated system, the mathematical derivation for an integrated GPS/INS/sonar system, and the results obtained from extensive testing.
Drones, 2021
The navigation of autonomous underwater vehicles is a major scientific and technological challenge. The principal difficulty is the opacity of the water media for usual types of radiation except for the acoustic waves. Thus, an acoustic transducer (array) composed of an acoustic sonar is the only tool for external measurements of the AUV attitude and position. Another difficulty is the inconstancy of the speed of propagation of acoustic waves, which depends on the temperature, salinity, and pressure. For this reason, only the data fusion of the acoustic measurements with data from other onboard inertial navigation system sensors can provide the necessary estimation quality and robustness. This review presents common approaches to underwater navigation and also one novel method of velocity measurement. The latter is an analog of the well-known Optical Flow method but based on a sequence of sonar array measurements.