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This paper describes a new framework for detection and tracking of underwater pipeline, which includes software system and hardware system. It is designed for vision system of AUV based on monocular CCD camera. First, the real-time data flow from image capture card is pre-processed and pipeline features are extracted for navigation. The region saturation degree is advanced to remove false edge point group after Sobel operation. An appropriate way is proposed to clear the disturbance around the peak point in the process of Hough transform. Second, the continuity of pipeline layout is taken into account to improve the efficiency of line extraction. Once the line information has been obtained, the reference zone is predicted by Kalman filter. It denotes the possible appearance position of the pipeline in the image. Kalman filter is used to estimate this position in next frame so that the information of pipeline of each frame can be known in advance. Results obtained on real optic vision data in tank experiment are displayed and discussed. They show that the proposed system can detect and track the underwater pipeline online, and is effective and feasible.

Owing to the complex operating environment of underwater vehicles, many uncertainties of sensors data, big noises of sensors , low precision and high rate of wild points of underwater acoustic sensors, data processing of motion sensors data for underwater vehicle navigation system becomes extremely important. The integrated navigation system of autonomous underwater vehicle based on dead-reckoning is introduced. An modified adaptive Kalman filter is adopted for underwater vehicle sensors information data processing. Experimental results show that the modified self-adaptive Kalman filter(SAKF) is effective, and can meet the underwater robots perform a variety of tasks in the navigation and positioning accuracy..

Cylinder shell stiffened by rings is used commonly in submersibles, and structure strength should be verified in the initial design stage considering the thickness of the shell, the number of rings, the shape of ring section and so on. Based on the statistical techniques, a strategy for optimization design of pressure hull is proposed in this paper. Its central idea is that: firstly the design variables are chosen by referring criterion for structure strength, then the samples for analysis are created in the design space; secondly finite element models corresponding to the samples are built and analyzed; thirdly the approximations of these analysis are constructed using these samples and responses obtained by finite element model; finally optimization design result is obtained using response surface model. The result shows that this method that can improve the efficiency and achieve optimal intention has valuable reference information for engineering application.

Accurate modeling and simulation of autonomous underwater vehicle (AUV) is essential for autonomous control and maneuverability research. In this paper, a mini AUV- “MAUV-II” was researched and the nonlinear mathematic model of the AUV in spatial motion was derived based on momentum theorem. The forces acting on AUV were resolved to several modules which were expressed in matrix form. Based on the motion model and combined with virtual reality technology, a motion simulation system was constructed. Considering the characteristic of “MAUV-II”, the heading control and depth control were simulated by adopting S-surface control method. A long distance traveling simulation experiment based on target planning was also done. The simulation results show that the “MAUV-II” has good spatial maneuverability, and verify the feasibility and reliability of control software.

S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles (AUV). However there are still problems maintaining steady precision of course due to the constant need to adjust parameters, especially where there are disturbing currents. Thus an intelligent integral was introduced to improve precision. An expert S-surface control was developed to tune the parameters on-line, based on the expert system, it provides S-surface control according to practical experience and control knowledge. To prevent control output over-compensation, a fuzzy neural network was included to adjust the production rules to the knowledge base. Experiments were conducted on an AUV simulation platform, and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents, producing good steady precision of course in a robust way.

Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was presented, which used the technique of fuzzy neural network. The structure of fuzzy neural network was constructed according to the moving characters and the back propagation algorithm was deduced. Simulation experiments were conducted on general detection remotely operated vehicle. The results show that there is a great improvement in response and precision over traditional control, and good robustness to the model’s uncertainty and external disturbance, which has theoretical and practical value.

In the previous research, the effect of the frame torsion on the local stability of a ring-stiffened cylindrical shell, which was proved to be significant, was usually omitted. In this paper this effect under the action of static water pressure is studied. The frame torsional strain energy is calculated by consulting the method used in the research on the stability of a stiffened rectangular plate. With this item of energy being introduced into the total potential energy of the structure, a new stability formula for calculating the critical pressure for the local buckling of the ring-stiffened cylindrical shell is obtained by Ritz method. This new formula can be regarded as a revision of the famous Mises’ formula. The calculation of the example shows that the critical pressure given by this formula is closer to the model test data than that given by Mises’ formula.

In order to eliminate hidden peril before the ship enter castle, the control architecture of a Ship Inspection SY-II Remote Operated Vehicle (ROV) has been developed. Based on surface control platform, it can be manipulated both through wireless joystick and by auto-depth and auto-direction control algorithm. The embedded controller of underwater robot is composed of control capsule and power supply capsule. Its main function includes acquiring sensors' information and thruster command transference. The communication highway between these two components is tether. According to Peng Lai oceanic experiments, the control architecture can work reliably in the oceanic environment, accomplish underwater observe and ship-body detection.

S-plane control is proved to be a feasible method with disadvantages at high speed in application to AUV motion control. To compensate the motion couple effect at high speed, a modified S-plane controller is proposed by analyzing AUV's dynamics and taking static force and coupling effects between longitude velocity and other dimensions into account. Besides the advantages of S controller such as simple structure, MSC can solve the motion control of AUV at high speed which is difficult to control with S-plane controller. Meanwhile, an actuator-oriented force allocation strategy is proposed for AUV's compounding actuators to solve system vibration or divergence caused by control output jump during switch operating between rudders and thrusters. Finally, experiments of velocity control, yaw control and depth control are conducted, and the results prove the feasibility and advantages in application to AUV motion control.

Considering the far unknown complex ocean environment, simulation system of automatic underwater vehicle (AUV) is very important in the whole RD the inner part is the six freedom motion simulation system, which is made for forecasting the maneuverability of long-endurance AUV (LEAUV). The whole system performs well in test.