Matko Barisic

AUV identification by use of self-oscillations

Abstract Given the fact that AUV dynamics change depending on the payload, finding a mathematical model in a rather small period of time is quite important. Classical openloop identification methods give accurate parameter identification, but are also time consuming. In the paper we present an identification method based on induced self-oscillations, which has proved to be applicable to underwater vehicles. In addition to that, an error analysis for the proposed method is presented. Experimental results obtained on an underwater vehicle are given and compared to the results obtained using open-loop identification algorithms.

Autotuning Autopilots for Micro-ROVs

Underwater vehicles are highly nonlinear and complex systems, that makes designing autopilots extremely difficult. This paper presents autotuning as a method for tuning parameters of a micro-ROV autopilot. The main benefit of this procedure is that the model of the process does not have to be known. Autotuning is often used for industrial processes but not on marine vessels. This procedure, which is performed in closed-loop, is completely automated and enables the operator to retune an autopilot whenever ROV performance is degraded (due to different operating points, tether influence, currents, etc.). In this article we use already known different autotuning recommendations (primarily designed for type 0 processes) with some modifications which we recommend for micro-ROVs. We also give results of using different types of PID controllers, whose parameters are being tuned. A real life demonstration on a VideoRay Pro II micro-ROV is provided

ROV AUTONOMIZATION - YAW IDENTIFICATION AND AUTOMARINE MODULE ARCHITECTURE

The Automarine Module is a simple cost effective method for transforming underwater remotely operated vehicles (ROVs) into autonomous underwater vehicles (AUVs), with minimum development time, and with no ROV circuit alteration. This paper presents architecture of autonomization of the VideoRay Pro II ROV together with its technical specifications. The paper also presents a procedure for open-loop identification of the nonlinear yaw model. Analytical expressions that are used for model identification are also provided.

Identification of Coupled Mathematical Models for Underwater Vehicles

The paper presents the procedure for identification of coupled mathematical models for underwater vehicles. The procedure is performed with the use of a simple laboratory apparatus that consists of a Webcam placed above the experimental pool. The video recording of the underwater vehicle in motion is then analyzed in order to obtain relative speeds within the camera frame. The experiment uses a simple maneuver which excites the vehicle in all controllable directions (in the horizontal plane). The results have shown that even though the system under observation is nonholonomic, the sway motion occurs due to coupling. This allows for determination of dynamic model in uncontrollable directions. The experimental data also show which terms in a general dynamic model can be omitted when dealing with micro underwater vehicles, in order to preserve the simplicity.

Transfer function identification by using self-oscillations

The work presented in this paper deals with the process of transfer function identification by using self-oscillation method (autotuning identification method). The algorithm is given in a general matrix form and some modifications are introduced. The modifications of the algorithm include augmentation of the initial algorithm for Type k systems, systems with delays and discrete-time systems. The paper also includes simulation examples which describe the introduced modifications. Apart from being rather simple, this method is applicable to real systems. Its greatest advantage is quick identification of a transfer function (depends on the system).

Kinematic simulative analysis of virtual potential field method for AUV trajectory planning

This paper deals with an analysis of applicability, capabilities, benefits and pitfalls of using a virtual potential field approach to autonomously planning trajectories in non-communicating autonomous underwater vehicles (AUV-s). Virtual potentials represent an approach to this problem with cross-layer design features. Examples of different layers of control that can be achieved with the same fundamental approach are: obstacle-avoidance, energy-optimal trajectories, forming up with other moving agents, controlled formation fragmentation into well-posed sub-formation etc. This paper shows, on the basis of extensive simulated experiments, that such a trajectory planner based on virtual potentials, guarantees good extendibility, scalability and performance in a hard-real-time hardware-in-the-loop system.

Sigma-point Unscented Kalman Filter used for AUV navigation

This paper presents an implementation of the Sigma-point Unscented Kalman Filter (SP-UKF) used in the simulated task of open-water navigation of two types of AUV. The first simulated vehicle is a large cruise-type vehicle modeled after the Instituto Superior Tecnico, Lisbon vehicle Infante. The second is a small, almost fully actuated vehicle with tunnel thrusters modeled after the SSC Pacific, San Diego vehicle CETUS II. The SP-UKF shows itself, after properly taking care of implementation details, to be a robust methodology which allows for efficient and correct navigation, aided by several typical sensors (DVL, USBL hydroacoustic localization systems, AHRS). The influence of currents on the navigation, and the ability of estimating the current components is also researched. The navigation fix is fed back to the low-level control loops aboard each vehicles to achieve sane and rational navigation of the waterspace that follows stably and robustly the command signals.

A Kinematic Virtual Potentials Trajectory Planner For AUV-s

Abstract This paper deals with trajectory planning for an autonomous, non-communicating submerged vehicle (AUV). Most maneuvering, esp. that related to obstacle avoidance, in a typical mission scenario for an AUV consists of motion at single submerged depth. Therefore a trajectory planning scheme operating in 2D has sufficient merit and applicability. A scheme for trajectory planning with cross-layer features, such as implicit inclusion of obstacle-avoidance and forming up with other moving agents, is developed in a simulated environment, at a kinematic level. The trajectory planner is based on virtual potentials, an approach that guarantees good extendibility, scalability and performance in a hard-real-time hardware-in-the-loop system.

Developing the Croatian Underwater Robotics Research Potential

Abstract This paper proceeds to lay out the activities being performed by the Croatian group of researchers from University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Control and Computer Engineering, Laboratory for Underwater Systems and Technologies (LABUST), after having successfully applied to the REGPOT-2008-1 call and having been awarded a capacity-building grant for the “Developing the Croatian Underwater Robotics Research Potential – CURE” project. The scientific contributions to the state of the art of underwater and marine system technology of LABUST, based on which the capacity to further and intensify research activity is being built within the CURE project, fall mainly into three categories: (1) unmanned small vessel modeling and identification, cf. Miskovic et al. (2009a,b,c). (2) distributed coordinated and cooperative control, cf. Barisic at al. (2008, 2009a,c). (3) embedded control systems engineering and software design, cf. Barisic et al. (2009b,d).

A MOOS-based online trajectory Re-planning system for AUVs

his paper describes an open source navigation system architecture for use in autonomous underwater vehicles. It is based on the Mission Oriented Operating System proposed, published and programmed by ( [1], [2]). It is uniquely applicable for work-in-progress type and development-stage software and capability installation onto an AUV system. This applicability is achieved by its completely modular nature, which is obtained by the operating system kernel running separate processes for each advanced navigation or control feature. Robustness is also achieved in this respect since failures and errors will cause only the individual modules that incurs them to fail. Such critical errors, bugs and failures will thereby be contained and their propagation halted from completely freezing even the low-level control loops and decision-making processes needed to successfully retrieve the malfunctioning AUV.