A vehicle dynamics model is crucial for the design of control system for an autonomous underwater vehicle (AUV). However, it is not a simple task to determine the hydrodynamic forces especially the drag coefficient involved for any particular vehicle model. This paper describes a novel approach to approximate the drag coefficient of any given vehicle shapes and sizes using fourth order regression method. The vehicle is subjected to pre-conditioning phase, where it can be done with CFD modelling or subject to simple experimental test within an open environment. In the pre-conditioning phase, the vehicle is required to navigate freely around custom test environment to obtain the drag profile in real-time. With sufficient data, using the correlation 3D graph of drag coefficient and the change in angles, the drag profile of any given shape can be determined. The accuracy of the model is based on the frequency of trial runs, as well as the efficiency of the vehicle's on-board inertial navigation sensors. In this paper, the proposed approach is being demonstrated using ANSYS-CFX and the results obtained provide close approximation to the real drag coefficient. Therefore, the proposed novel approach is promising and can be used to find the drag coefficients for any given underwater vehicle at any conditions.
One of the key aspects in designing an Autonomous Underwater Vehicle (AUV) simulation framework is sensor modeling. This paper presents specifically the underwater sonar sensor modeling structure used in the proposed AUV simulation framework. This sensor model covers the mathematical aspects from the field of acoustics which mimics real world sensors. Simplified sonar signal models are widely used however rarely discussed in the literature. Based on this designed simulation framework, simple scenario using different sonar configuration is shown and discussed. This paper shows the formulation of a typical side-scan sonar with emphasis on the assumptions which leads to the simplification of the sonar model. The sonar sensor model is built based on a developed AUV test-bed which was done previously in the University of Adelaide.
With the recent technological advancement in submersible systems, the research and development of underwater manipulator robot is highly desirable. This paper focuses on comparing simulation versus real-time manipulator dynamics control, and comparison of intelligent underwater manipulator-robot for effective Ocean-based research, industrial and defense applications. Software package such as MATLAB is used to simulate the results of underwater manipulator performances and compare it with the real-time trials. A mathematical model for underwater manipulator which encompasses deriving modified Denavit-Hartenberg parameters, computing all transformation matrices, deriving the forward kinematic and generating trajectory. Base on cubic polynomials, the manipulator trajectory is generated by using the joint angles and translation of each trajectory point. The result of manipulator performances is simulated by using SIMULINK. The manipulator simulation, which is aimed to analyze the movement of each arm, through the parameters of locations, velocity and torques are obtained. This paper also includes the comparison of manipulator-robot performance simulation with real-time trials. In order to measure the results of real-time, the Nintendo Wii remote is attached to manipulator to record the performances. The comparison can reveal the differences between simulation and real-time test in order to optimize for underwater manipulator.
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