Mosaic-based navigation for autonomous underwater vehicles

We propose an approach for vision-based navigation of underwater robots that relies on the use of video mosaics of the sea bottom as environmental representations for navigation. We present a methodology for building high-quality video mosaics of the sea bottom in a fully automatic manner, which ensures global spatial coherency. During navigation, a set of efficient visual routines are used for the fast and accurate localization of the underwater vehicle with respect to the mosaic. These visual routines were developed taking into account the operating requirements of real-time position sensing, error bounding, and computational load. A visual servoing controller, based on the vehicle's kinematics, is used to drive the vehicle along a computed trajectory, specified in the mosaic, while maintaining constant altitude. The trajectory toward a goal point is generated online to avoid undefined areas in the mosaic. We have conducted a large set of sea trials, under realistic operating conditions. This paper demonstrates that without resorting to additional sensors, visual information can be used to create environment representations of the sea bottom (mosaics) and support long runs of navigation in a robust manner.     

Enhancement of the inertial navigation system for the Morpheusautonomous underwater vehicles

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     

Hypothesis grids: improving long baseline navigation for autonomous underwater vehicles

Navigation continues to fundamentally limit our ability to understand the underwater world. Long baseline navigation uses range measurements to localize a remote vehicle using acoustic time-of-flight estimates. For autonomous surveys requiring high precision navigation, current solutions do not satisfy the performance or robustness requirements. Hypothesis grids represent the survey environment capturing the spatial dependence of acoustic range measurement, providing a framework for improving navigation precision and increasing the robustness with respect to non-Gaussian range observations. Prior association probabilities quantify the measurement quality as a belief that subsequent observations will correspond to the direct-path, a multipath, or an outlier as a function of the estimated location. Such a characterization is directly applicable to Bayesian navigation techniques. The algorithm for creating the representation has three main components: Mixed-density sensor model using Gaussian and uniform probability distributions, measurement classification and multipath model identification using expectation-maximization (EM), and grid-based spatial representation. We illustrate the creation of a set of hypothesis grids, the feasibility of the approach, and the utility of the representation using survey data from the autonomous benthic explorer (ABE).     

A high-resolution pulse-Doppler underwater acoustic navigation system

A high-resolution underwater acoustic pulse-Doppler navigation system has been developed and tested at sea. The system provides continuous, highly accurate tracking of underwater and ocean-surface platforms in a fixed 50-km²navigation net. Three reference buoys, moored 20 m from the ocean bottom, provide the navigation net used by shipboard processing equipment. Each reference buoy contains an acoustic transponder, used to obtain the acoustic travel times from the transponder to the platform, and a continuous-tone beacon, used to obtain the Doppler shift due to platform motion. The system is capable of determining the position of a platform with respect to the reference net with an error of 2-3 m. The relative position of the platform on a fix-to-fix basis can be determined within several centimeters over short time intervals (approx 10min).     

水下模块化自重构机器人对接导引

给出一种水下自重构机器人的基本构成模块,针对模块化自重构机器人的对接要求,设计一套基于蓝光波段的可见光定位系统,检测需要对接的两个面之间的位置与姿态关系.在主动连接面呈正三角形安装三个蓝光LED光源,在相应的被动连接面中心安装一个光敏二极管作为光强接收传感器,利用光强接收传感器接收到的信息,设计一套位置检测算法,根据计算出的相对方位误差,修正两对接面的方位.实验结果表明,所设计的蓝光波段可见光导引系统能够在水下准确检测两对接面相对方位,误差小于2cm.     

Power systems for autonomous underwater vehicles

In this paper, we examine the issues involved in designing battery systems and power-transfer (charging) techniques for Autonomous Underwater Vehicles (AUVs) operating within an Autonomous Ocean Sampling Network (AOSN). We focus on three different aspects of the problem, battery chemistry, pack management and in situ charging. We look at a number of choices for battery chemistry and evaluate these based on the requirements of maximizing power density and low temperature operation particular to AUVs. We look at the issues involved in combining individual cells into large battery packs and at the problems associated with battery monitoring, and the charging and discharging of packs in a typical AUV application. Finally, we present a methodology for charging an AUV battery pack in situ in support of long term deployments at remote sites     

Mine avoidance techniques for underwater vehicles

It is shown that by implementing certain mine avoidance techniques, an underwater vehicle equipped with an obstacle avoidance sonar (OAS) and a navigation system can safely navigate an unknown minefield. The mine avoidance techniques take into account the physical limitations of the sonar and the navigation system, the maneuverability constraints on the underwater vehicle, and the required safe standoff distance from all mines. Extensive computer simulations have verified the mine avoidance capability in more than 50 different minefields. In all 50 simulations the vehicle reached a predetermined end point and maintained at least the specified, minimum safe standoff distance from each mine. The simulation accurately models the major difficulties associated with the sonar, the navigation system, and the vehicle dynamics. The sonar model includes surface, bottom, and volume reverberation; thermal, ambient, and flow noises; actual receiver and projector beam patterns; and false alarms and missed detections. The navigation system model contains the effects of biases, random noises, and scale factor errors. The vehicle dynamic model simulates angular velocities and accelerations associated with underwater vehicles     

Transformed equations of motion for underwater vehicles

A method for dynamics investigation and coupling detection between velocities of autonomous underwater vehicles (AUVs) is presented in this paper. The method is based on transformation of equations of motion, which are usually used for an underwater vehicle, into equations with a diagonal mass matrix. The obtained equations contain quasi-velocities and allow one to give a further insight into the AUV dynamics especially for an underactuated system. Some advantages of the proposed approach are discussed, too. An analytical example for a 3-DOF AUV shows possible application of the transformed equations. Moreover, the given approach is validated via simulation on a 6-DOF vehicle.     

Pseudo long base line navigation algorithm for underwater vehicles with inertial sensors and two acoustic range measurements

This paper presents an integrated navigational algorithm for unmanned underwater vehicles (UUV) using two acoustic range transducers and strap-down inertial measurement unit (SD-IMU). A range measurement model is derived for a UUV having one acoustic transducer and cruising around two reference transponders at sea floor or surface. The proposed algorithm, called pseudo long base line (PLBL), estimates the position of the vehicle integrating the SD-IMU signals corrected with the two range measurements. Extended Kalman filter was applied to propagate error covariance, to update measurement errors and to correct state equation whenever the external measurements are available. Simulations were conducted to illustrate the effectiveness of the PLBL using the 6-d.o.f. nonlinear numerical model of a UUV at current flow, excluding bottom-fixed DVL. This paper also shows the error convergence of the vehicle's initial position by the additional range measurements without velocity information.     

Decoupled PD set-point controller for underwater vehicles

A set-point controller for autonomous underwater vehicles (AUVs) is proposed in this paper. The controller is expressed in transformed equations of motion with a diagonal inertia matrix. It takes into account the dynamics of the system and it can be applied for fully actuated AUVs. The stability of the designed control law is demonstrated by means of a Lyapunov-based argument. Some advantages arising from the use of the controller are considered too. The performance of the proposed controller is validated via simulation on a 6-DOF underwater vehicle.     

Evolutionary path planning for autonomous underwater vehicles in a variable ocean

This paper proposes a genetic algorithm (GA) for path planning of an autonomous underwater vehicle in an ocean environment characterized by strong currents and enhanced space-time variability. The goal is to find a safe path that takes the vehicle from its starting location to a mission-specified destination, minimizing the energy cost. The GA includes novel genetic operators that ensure the convergence to the global minimum even in cases where the structure (in space and time) of the current field implies the existence of different local minima. The performance of these operators is discussed. The proposed algorithm is suitable for situations in which the vehicle has to operate energy-exhaustive missions.     

A neural net controller for underwater robotic vehicles

Results of a study on the application of neural networks to the control system of underwater robotic vehicles (URVs) are presented. The robustness of the control system with respect to nonlinear dynamic behavior and parameter uncertainties is investigated by computer simulation. The results show the feasibility of using unpredictable changes in the dynamics of the vehicle and its environment     

Accurate and practical thruster modeling for underwater vehicles

The thruster is the crucial factor of an underwater vehicle system, because it is the lowest layer in the control loop of the system. In this paper, we propose an accurate and practical thrust modeling for underwater vehicles which considers the effects of ambient flow velocity and angle. In this model, the axial flow velocity of the thruster, which is non-measurable, is represented by ambient flow velocity and propeller shaft velocity. Hence, contrary to previous models, the proposed model is practical since it uses only measurable states. Next, the whole thrust map is divided into three states according to the state of ambient flow and propeller shaft velocity, and one of the borders of the states is defined as critical advance ratio (CAR). This classification explains the physical phenomenon of conventional experimental thrust maps. In addition, the effect of the incoming angle of ambient flow is analyzed, and Critical Incoming Angle (CIA) is also defined to describe the thrust force states. The proposed model is evaluated by comparing experimental data with numerical model simulation data, and it accurately covers overall flow conditions within ±2 N force error. The comparison results show that the new model's matching performance is significantly better than conventional models'.     

Robust trajectory control of underwater vehicles

underwater vehicles present difficult control-system design problems due to their nonlinear dynamics, uncertain models, and the presence of disturbances that are difficult to measure or estimate. In this paper, a recent extension of sliding mode control is shown to handle these problems effectively. The method deals directly with nonlinearities, is highly robust to imprecise models, explicitly accounts for the presence of high-frequency unmodeled dynamics, and produces designs that are easy to understand. Using a nonlinear vehicle simulation, the relationship between model uncertainty and performance is examined. The results show that adequate controllers can be designed using simple nonlinear models, but that performance improves as model uncertainty is decreased and the improvements can be predicted quantitatively.     

水下机器人运动的S面控制方法

由于水下机器人的强非线性以及系统存在不确定性，同时考虑到港湾环境下水声的噪声大，因此，水下机器人进行精确作业时的运动控制一直是其实用化过程中困扰人们的问题，通常水下机器人的控制方式有PID控制器，神经网络控制器和模糊逻辑控制器三种，但是，由于这三种方法在实际应用中都存在一些参数难以确定的缺陷，为了解决这一问题，本文从模糊逻辑控制方式出发，借鉴PID控制的结构形式，推导出一种全新而简单有效的控制方法，定义为S面控制法，从水下机器人的水池试验和海上实验来看，不论是定点的控制精度还是运动过程中的控制效果都较令人满意，尤其是在风浪，潮流都比较大的海上实验中得到验证，鲁帮性很好。     

Design of wake-adapted contra-rotating propellers for high-speed underwater vehicles

Based on the lifting-surface vortex lattice model, a numerical design method of wake-adapted contra-rotating propellers (CRPs) for high-speed underwater vehicles is proposed. According to the given radial circulation distribution, the method can use prescribed camber line shapes to design maximum cambers and pitches of blade sections by controlling circulation at the leading edge, which makes the chordwise distribution of blade loading similar to that of NACA a = 0.8. It also can be performed under prescribed chordwise circulation distributions, where camber line shape and blade section pitch are designed. The Newton–Raphson iterative algorithm is utilised in the design of the pitch and camber. The radial circulation distribution of a set of CRPs for an underwater vehicle is used to redesign CRPs by the proposed method, and the design results are then validated via numerical simulations by solving the Reynolds-averaged Navier-Stokes equations. The results indicate that the proposed method is suitable for the design of CRPs with tapered hubs and skewed blades, and it also exhibits good mesh convergence. The CRPs designed with the given camber line shape and the given chordwise loading distribution both have relatively uniform pressure distributions, with the latter being superior.     

Survey of underwater robot positioning navigation

Underwater robot positioning and navigation achieve autonomous underwater robot movement based on the premise that positioning obtains the coordinates of the relative position of the underwater robot using a sensor, and navigation yields a known location to the destination path planning. Due to the location of an underwater robot and the complex and changing environment in which it operates, it is difficult to achieve precise positioning using the traditional positioning method. This paper systematically analyzes and summarizes several typical localization and navigation methods of underwater robots, such as multisensor information fusion technology, underwater acoustic localization and navigation methods, GPS buoy, underwater vision, SLAM and coordinate localization and navigation of multiple underwater robots. Multisensory information fusion technology integrates the advantages of the above methods, enhances the system stability and robustness, overcomes the disadvantages of traditional positioning and navigation, and enables the autonomous navigation and positioning of underwater robots. Underwater acoustics enable flexible and convenient positioning, whereas GPS can achieve high-precision and high-positioning navigation information, and visual positioning effectively overcomes the problem of error accumulation. Multirobot cooperative positioning resolves the problem of positioning failure caused by the collapse of a single system and completes complex tasks that cannot be completed by a single robot, thus enhancing the stability and robustness of the system. This paper systematically describes the realization of these methods, presents an actual analysis of their respective advantages and problems, and discusses the development of the field of research prospects and application prospects.     

Application of a panel method to hydrodynamics of underwater vehicles

A low-order singularity panel method based on Green's formulation is used to predict the hydrodynamics characteristics of underwater vehicles. The low-order modeling employs constant strength sources and doublets, and the body surface is modeled by quadrilaterals. The method is first applied to predicting the force and moment coefficients of underwater vehicles for the body-alone and finned configurations. Hydrodynamic coefficients of added mass and added moment of inertia are also calculated by modifying the code. Results for several two and three-dimensional bodies show the usefulness of the method for predicting the added mass and added moment of inertia.     

Multivariable self-tuning autopilots for autonomous and remotelyoperated underwater vehicles

The effectiveness of subsea intervention has been found to be dependent upon the capability of an autonomous underwater vehicle's (AUV's) or remotely operated underwater vehicle's (ROV's) auto-positioning system. However, these vessel's dynamics vary considerably with operating condition, and are strongly coupled; they are expensive and difficult to derive, theoretically or through conventional testing, making the design of conventional autopilots difficult to achieve. Multi-input-multi-output self-tuning controllers offer a possible solution. Two such schemes are presented. The first is an implicit linear quadratic online, self-tuning controller, and the other uses a robust control law based on a first-order approximation of the open-loop dynamics and online recursive identification. The controllers' performance is evaluated by examining their behavior when controlling a comprehensive nonlinear simulation of an ROV and its navigation system. An interesting offshoot of this study is the application of recursive system identification techniques to the derivation of ROV models from data gathered from the trials; the potential advantages of this method are discussed