Kaizhou Liu

The development of autonomous underwater vehicle's semi-physical virtual reality system

A semi-physical virtual reality system applying to autonomous underwater vehicle control study is presented in this paper. This system is composed of three nodes: (1) autopilot node for mission planning and control, (2) virtual node for virtual devices and sensors and (3) visualization node for virtual ocean environment and display the state of AUV. The autopilot node can be both linked to the real sensors and actuators dealing with a real mission, and linked to the virtual world for simulation. The advantages of this semi-physical virtual reality system include that: (1) the vehicle software can he simulated in the laboratory before real experiments taking place, (2) the merit and demerit of some newly AUV system can be confirmed, (3) Moreover intensive testing is easy and its cost is not too expensive.

Dynamic Sliding Mode Control Based on Multi-model Switching Laws for the Depth Control of an Autonomous Underwater Vehicle

This manuscript presents an improved control algorithm, called Dynamic Sliding Mode Control based on Multiple Models Switching Laws (DSMC-MMSL), for the control of the depth of the studied Autonomous Underwater Vehicle (AUV) system, the diving plane controller of which faces disturbances arising from the coupled states. The diving plane model is strongly coupled with the state variables, such as surge speeds and course angles. To achieve the desired dynamic performance, the proposed algorithm consists of two parts: the diving plane control part and the pitch control part, which is used to avoid large pitch angles. Some direct switching control laws are used for the two parts to avoid some impulse phenomena on the control executions. The error-states exponential decay is recommended to eliminate the chattering on the sliding surface. The DSMC-MMSL controller was successfully implemented and experimentally validated with the studied AUV system designed and built by Shenyang Institute of Automation. The results of some lake trials demonstrated that the depth control performances of the AUV system were as desired, and that the AUV system was robust enough for the coupled state variables under the DSMC-MMSL algorithm control.

An adaptive square-root unscented Kalman filter for underwater Vehicle navigation

In order to increase the approximation accuracy of the state estimate of nonlinear systems and to guarantee numerical stability of the unscented Kalman filter (UKF), a novel adaptive square-root unscented Kalman filter (ASRUKF) based on modified Sage-Husa noise statistics estimator is proposed. The new adaptive filter method with adaptability to statistical characteristic of noise is able to compensate the lack of a priori knowledge of the systems noise statistics. A six-degree-of-freedom dynamic model is introduced to denote the motion model of Human Occupied Vehicle (HOV) in the water, while the adaptive SRUKF is employed for off-line estimation of the state of HOV. Tests are conducted with respect to the data obtained from previous sea trial, and the results are compared with those obtained by normal UKF and SRUKF to indicate its effectiveness and improvements.

Toward a generalized architecture for unmanned underwater vehicles

A common feature of unmanned vehicles is their complexity, which grows apace and provides its own challenges. Frameworks for managing this growing complexity have always been one of the key aspects of designing an unmanned vehicle. In this paper, a generalized architecture is proposed to not only address the complexity in developing an unmanned vehicle, but also support the algorithm exchange and technology transfer for integrating efforts from different researchers. We first detail the autonomic element, which is the fundamental unit of the architecture. Then the architecture is constructed, and thorough discussions are given. Finally, simulations on a semi-physical platform are carried out to examine the performance of this architecture.

The Design and Development of Simulator System—For Manned Submersible Vehicle

A semi-physical virtual reality system applying to MSV (manned submersible vehicle) control study is presented in this paper. This system is composed of three nodes: (1) control node for receiving sensors information and sending control command, (2) virtual sensors node for virtual devices and sensors and (3) Visualization node for virtual ocean environment and displaying the posture of MSV. The control node can be both linked to the real sensors and actuators dealing with a real mission, and linked to the virtual world for test purpose. The advantages of this semi-physical virtual reality system include that: (1) the MSV software can be tested in the laboratory before real experiments taking place, (2) the merit and demerit of some newly underwater vehicle system can be verified, (3) Moreover intensive testing is easy and its cost is not too expensive

Label field initialization for MRF-based sonar image segmentation by selective autoencoding

The optimal solution of a Markov random field (MRF) can be solved by constructing a Markov chain that eventually goes to a balance state. However, in most situations, only an suboptimal solution can be obtained, because it is hard to choose the ideal initial state and the updating strategy. While the updating strategy has been extensively investigated, the initialization issue has been fully neglected. Though k-means-clustering has been used exclusively in initializing the label field, it suffers from the lack of account of the local constraints, which is the most essential part of the MRF model. A structural method based on selective autoencoding (SAE) is proposed for the label field initialization of MRF model in the task of sonar image segmentation. SAE is similar to the AutoEncoder, with the largest difference on the activation function, where a piece-wise sigmoid activation function with two different slop parameters is used to selectively encode image patches that resemble shadow ares or other areas. The synapse matrixes of SAE network act as information filters, preserve specific area adaptively and selectively, generating a label field that is much closer to the balance state. Experiments on sonar image segmentation demonstrate the efficiency of the SAE algorithm.

Virtual platform of a manned submersible vehicle carrying an underwater manipulator

In this paper, we develop a virtual platform of a manned submersible vehicle carrying an underwater manipulator to animate operation tasks under the deep sea. The models of the vehicle and the manipulator refer to the structures of the “Jiaolong” deep manned submersible vehicle and a master-slave servo hydraulic manipulator, respectively. The master-slave manipulator with 7 functions developed by Shenyang Institute of Automation (SIA), Chinese Academy of Sciences, is able to perform operation tasks below the oceans surface 7000 meters. The platform is a powerful multi-purpose tool: First, it can be used for training an operator to telepresence operate the virtual manipulator to complete basic tasks under the deep sea by coordinating a cradle head, the manned submersible vehicle and the underwater manipulator; Second, it can be used to test or to validate motion control methods for operating the submersible and manipulator. In order to demonstrate the feasibility and effectiveness of the virtual platform, we present two typical underwater operation tasks: picking-up a rock sample and making a mark.

Electronic chart based ocean environment development method and its application in digital AUV platform

For the purpose of building a robust AUV controller, which could be used to handle dangerous ocean environment, a method of obtaining benthonic terrain based on Electronic Chart is presented. Firstly, some terrain conversion algorithms for development of the benthonic terrain, such as nearest neighbor interpolation, linear interpolation, cubic interpolation and v4-interpolation are compared; Later a new terrain conversion algorithm for development of the benthonic terrain DTTCGSFD (Delaunay Triangle-based Terrain Considering of Grid, Sparse, Feature Data) is introduced. This method consider the data not only distance constant grid data, Sparse data, but also feature data with the terrain data, such as fathom line etc. In the end, build benthonic terrain making use of Electronic Chart ESRI shapefile database. The result, which is of importance in the AUV research of terrain matching navigation, path planning and obstacle avoidance strategy, has been applied in the research work of our digital AUV platform.

Command Filter Based Globally Stable Adaptive Neural Control for Cooperative Path Following of Multiple Underactuated Autonomous Underwater Vehicles with Partial Knowledge of the Reference Speed

Abstract This paper investigates the problem of cooperative path following for a fleet of underactuated autonomous underwater vehicles (AUVs) with uncertain nonlinear dynamics. Path following controllers for individual AUVs are developed to ensure that each AUV converges to the desired position. The coordination mission is completed by reaching synchronization on a suitably defined path variable, even in the presence of partial knowledge of the reference speed. The key features of the proposed cooperative path following design scheme can be summarized as follows. First, the command filter design technique based cooperative path following control strategy is derived by introducing compensating error signals to remove the requirement of the higher derivative of reference signal, and a simplified cooperative path following controller is proposed. Second, a smoothly switching function is designed to yield neural network (NN) based energy-efficient controller. Third, by designing the distributed speed estimator, the global knowledge of the reference speed is relaxed. Finally, all the signals in the closed-loop system are guaranteed to be globally uniformly ultimately bounded (GUUB) under the proposed algorithm, and the path following error is proven to converge to a small neighborhood of the origin. Simulation example is provided to validate the performance of the control strategy.

Design and implementation of Manned Submersible semi physical simulation system

In order to improve the safety factors of MSV (Manned Submersible Vehicle) and shorten the pilot training cycle, the real hardware and software system combine with the modelling and simulation calculation of its sensors, equipment, actuators submersible ontology and motion status in deep sea environment, realizing the semi physical simulation system. First of all, the system model is built and hardware structure is introduced; then the model calculation software structure is studied, mainly focusing on the motion data simulation; finally open-loop motion data, close-loop motion data, all virtual devices and their network data transmission delay time are estimated. The conclusions that the MSVs semi physical simulation system network performance is better than Jiaolongs and the motion data is favourable are got, realizing the simulation of sensors, equipment, actuators and three-dimensional motion data. This lays foundation for improvement of MSVs safety factors and contraction of pilot training period.