Dynamics and control of a towed underwater vehicle system, part I: model development

Autonomous vehicles are being developed to replace the conventional, manned surface vehicles that tow mine hunting towed platforms. While a wide body of work exists that describes numerical models of towed systems, they usually include relatively simple models of the towed bodies and neglect the dynamics of the towing vehicle. For systems in which the mass of the towing vehicle is comparable to that of the towed vehicle, it becomes important to consider the dynamics of both vehicles. In this work, we describe the development of a numerical model that accurately captures the dynamics of these new mine hunting systems. We use a lumped mass approximation for the towcable and couple this model to non-linear numerical models of an autonomous surface vehicle and an actively controlled towfish. Within the dynamics models of the two vehicles, we include non-linear controllers to allow accurate maneuvering of the towed system.     

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     

Real-time path planning and obstacle avoidance for RAIS: anautonomous underwater vehicle

This paper describes a navigation and guidance system (NGS) with real-time path planning and obstacle avoidance capabilities that has been developed for the autonomous underwater vehicle RAIS. The vehicle is designed to accomplish two missions: pre-deployment survey of sea bottom, and visual inspection of pipelines. In the first mission, the NGS must be able to track a predefined path while avoiding the unplanned occurrence of obstacles. In the second mission, the NGS must track a pipeline by locally reconstructing its location from visual information; also in this case, the unplanned occurrence of obstacles must be handled. Furthermore, the NGS must properly take into account the presence of ocean current and some drastic constraints due to sensor and actuator characteristics. Numerical and hardware-in-the-loop simulations have been developed to verify the effectiveness of the proposed NGS     

Path Planning Method Based on D~* lite Algorithm for Unmanned Surface Vehicles in Complex Environments

In recent decades, path planning for unmanned surface vehicles(USVs) in complex environments, such as harbours and coastlines, has become an important concern. The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles. In this study,we developed a novel path planning method based on the D* lite algorithm for real-time path planning of USVs in complex environments. The proposed method has the following advantages:(1) the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles;(2) a constrained artificial potential field method is employed to enhance the safety of the planned paths; and(3) the method is practical in terms of vehicle performance. The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms. The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments.     

Underwater vehicle obstacle avoidance and path planning using amulti-beam forward looking sonar

This paper describes a new framework for segmentation of sonar images, tracking of underwater objects and motion estimation. This framework is applied to the design of an obstacle avoidance and path planning system for underwater vehicles based on a multi-beam forward looking sonar sensor. The real-time data flow (acoustic images) at the input of the system is first segmented and relevant features are extracted. We also take advantage of the real-time data stream to track the obstacles in following frames to obtain their dynamic characteristics. This allows us to optimize the preprocessing phases in segmenting only the relevant part of the images. Once the static (size and shape) as well as dynamic characteristics (velocity, acceleration,…) of the obstacles have been computed, we create a representation of the vehicle's workspace based on these features. This representation uses constructive solid geometry (CSG) to create a convex set of obstacles defining the workspace. The tracking takes also into account obstacles which are no longer in the field of view of the sonar in the path planning phase. A well-proven nonlinear search (sequential quadratic programming) is then employed, where obstacles are expressed as constraints in the search space. This approach is less affected by local minima than classical methods using potential fields. The proposed system is not only capable of obstacle avoidance but also of path planning in complex environments which include fast moving obstacles. Results obtained on real sonar data are shown and discussed. Possible applications to sonar servoing and real-time motion estimation are also discussed     

一种基于有限状态机模型的局部转向避碰路径规划算法

针对多礁石、渔船等障碍物的近海复杂环境下的一些应用,提出了一种基于有限状态机(finite-state machine,FSM)模型的无人船(unmanned surface vehicle,USV)局部转向避碰路径规划算法。首先,基于速度障碍法和障碍物区域分层方法,获取无人船固定航速条件下的航向角约束解析结果。然后,基于该约束条件及障碍物探测情况设计FSM的有限状态及执行动作和状态迁移条件,其中,通过转向控制实现向目标位点或缓冲位点进行导航的状态为FSM的2个重要状态。最终通过FSM的执行实现局部转向避碰路径规划。仿真结果表明提出的多障碍物避碰算法具有可行性和实用性。该方法易于改进和扩展,且容易与当前主流的无人船控制系统结合,有利于无人船避碰系统快速工程化的实现。     

Trajectory planning and collision avoidance for underwater vehiclesusing optimal control

Energy-optimal trajectories for underwater vehicles be computed using a numerical solution of the optimal control problem. A performance index consisting of a weighted combination of energy and time consumption is proposed. Collision avoidance is solved by including path constraints. Control vector parameterization with direct single shooting is used in this study. The vehicle is modeled with six-dimensional nonlinear and coupled equations of motion. Optimal trajectories are computed for a vehicle controlled in all six degrees of freedom by dc-motor-driven thrusters. Good numerical results are achieved     

Multi-Behavior Fusion Based Potential Field Method for Path Planning of Unmanned Surface Vessel

The problem of the unmanned surface vessel(USV) path planning in static and dynamic obstacle environments is addressed in this paper. Multi-behavior fusion based potential field method is proposed, which contains three behaviors: goal-seeking, boundary-memory following and dynamic-obstacle avoidance. Then, different activation conditions are designed to determine the current behavior. Meanwhile, information on the positions, velocities and the equation of motion for obstacles are detected and calculated by sensor data. Besides, memory information is introduced into the boundary following behavior to enhance cognition capability for the obstacles, and avoid local minima problem caused by the potential field method. Finally, the results of theoretical analysis and simulation show that the collision-free path can be generated for USV within different obstacle environments, and further validated the performance and effectiveness of the presented strategy.     

Analysis of channel effects on direct-sequence and frequency-hoppedspread-spectrum acoustic communication

Multiuser underwater acoustic communication is one of the enabling technologies for the autonomous ocean-sampling network (AOSN). Multiuser communication allows vehicles, moorings, and bottom instruments to interact without human intervention to perform adaptive sampling tasks. In addition, multiuser communication may be used to send data from many autonomous users to one buoy with RF communications capability, which will then forward the information to shore. The two major signaling techniques for multiuser acoustic communication are phase-shift keying (PSK) direct-sequence spread-spectrum (DSSS) and frequency-shift keying (FSK) frequency-hopped spread-spectrum (FHSS). Selecting between these two techniques requires not only a study of their performance under multiuser conditions, but also an analysis of the impact of the underwater acoustic channel. In the case of DSSS, limitations in temporal coherence of the channel affect the maximum spreading factor, leading to situations that may be better suited to FHSS signals. Conversely, the multipath resolving properties of DSSS minimize the effects of frequency-selective fading that degrade the performance of FSK modulation. Two direct-sequence receivers potentially suitable for the underwater channel are presented. The first utilizes standard despreading followed by decision-directed gain and phase tracking. The second uses chip-rate adaptive filtering and phase tracking prior to despreading. Results from shallow water testing in two different scenarios are presented to illustrate the techniques and their performance     

履带式深海采矿车软底质行走性能分析

海底底质的物理力学参数不同于陆地土壤,其极低的抗剪强度和承压强度对深海采矿车的行走性能提出高要求。分析基于车辆地面力学理论,开展了底质土力学特性试验研究,建立了深海底质力学模型。根据深海重载作业采矿车样机结构参数,在大型动力学仿真软件Recurdyn中建立了仿真模型。通过直线行走多体动力学仿真与直线行走海试试验的对比,验证了仿真模型的准确性。在此基础上开展了采矿车样机在深海软底质上的多种行走工况动力学仿真,分析与评价其行走性能。结果表明,采矿车样机可以顺利完成转弯、爬坡、越障等基本功能。该研究成果可为深海采矿车海底行走性能评估提供理论参考,为深海采矿车和软底质的相互作用力学研究提供借鉴。     

基于径向基神经网络的水下自主航行器寻源算法研究

针对水下航行器在二维信号场中的场源搜索问题,提出了一种基于径向基函数神经网络（radial basis function neural network,简称RBFNN）的在线自主寻源算法。在神经网络中引入全局正则化参数以保证泛化性和稳定性,通过最小化广义交叉验证误差（generalized cross-validation,简称GCV）进行正则化参数的迭代优化,并利用增量式奇异值分解（incremental SVD）对迭代过程进行加速,此外通过基于样本新颖性的资源分配网络算法（resource-allocating network,简称RAN）进行径向基函数的分配,在此基础上使用动量梯度算法进行航行器运动方向的规划。最后,以热泉区硫化氢浓度分布场中的搜索作业为背景,使用该算法与其他研究中的算法进行单峰值信号场的场源搜索模拟计算对比,结果显示该算法对于信号场梯度的估计更加准确,且搜索过程的路径更短。此外在多峰值信号场的寻源模拟中该算法能够以较高的成功率通过局部最大值区域。证明该算法具有良好的拟合、预测性能以及稳定性,并且能在一定程度上避免陷入局部最优解。     

Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle

A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV.     

A task-based hierarchical control strategy for autonomous motion of an unmanned surface vehicle swarm

In this paper, a hierarchical control framework with relevant algorithms is proposed to achieve autonomous navigation for an underactuated unmanned surface vehicle (USV) swarm. In order to implement automatic target tracking, obstacle avoidance and avoid collisions between group members, the control framework is divided into three layers based on task assignments: flocking strategy design, motion planning and control input design. The flocking strategy design transmits some basic orders to swarm members. Motion planning applies the potential function method and then improves it; thus, the issue of autonomous control is transformed into one of designing the velocity vector. In the last layer, the control inputs (surge force and yaw moment) are designed using the sliding mode method, and the problem of underactuation is handled synchronously. The proposed closed-loop controller is shown to be semi-asymptotically stable by applying Lyapunov stability theory, and the effectiveness of the proposed methodology is demonstrated via numeric simulations of a homogeneous USV swarm.     

Robust control for underwater vehicle systems with time delays

A robust control scheme is presented for controlling systems with time delays. The scheme is based on the Smith controller and the LQG/LTR (linear quadratic Gaussian/loop transfer recovery) methodology. The methodology is applicable to underwater vehicle systems that exhibit time delays, including tethered vehicles that are positioned through the movements of a surface ship and autonomous vehicles that are controlled through an acoustic link. An example, using full-scale data from the tethered vehicle ARGO, demonstrates the developments     

Investigation of a method for predicting AUV derivatives

The paper addresses the problem of autonomous underwater vehicle (AUV) modelling and parameter estimation as a means to predict the dynamic performance of underwater vehicles and thus provide solid guidelines during their design phase. The use of analytical and semi-empirical (ASE) methods to estimate the hydrodynamic derivatives of a popular class of AUVs is discussed. A comparison is done with the results obtained by using computational fluid dynamics to evaluate the bare hull lift force distribution around a fully submerged body. An application is made to the estimation of the hydrodynamic derivatives of the MAYA AUV, an autonomous underwater vehicle developed under a joint Indian-Portuguese project. The estimates obtained were used to predict the turning diameter of the vehicle during sea trials.     

Wigner/cycle spectrum analysis of spread spectrum and diversitytransmissions

A high-resolution t-ω estimator, termed the Wigner distribution (WD), is shown to form a sound basis for representing nonstationary acoustic returns. Signal returns are modeled as the output of a time-variant random filter where the WD of the nonstationary signal return defines a random process whose expectation reduces to the instantaneous power spectral density defined for dispersive communication channels. From the WD, a set of relations describing time-variant channel effects on spread-spectrum and diversity transmissions are developed. These relations are shown to be useful in comparing spreading techniques under differing channel conditions and for estimating channel-imposed bounds on the spreading parameters required for effective transmission. A mapping from the Wigner distribution to the cycle spectrum is shown to produce cyclic correlations characteristic of the modulation rate. The WD-based formulation is applied to an example of spread-spectrum transmission through a reverberation-limited channel     

一种基于边缘信息的车辆检测和跟踪方法

针对智能交通系统中运动车辆的检测和跟踪问题,提出1种基于边缘信息车辆检测和跟踪方法。利用背景边缘提取模板提取当前帧的精确背景边缘,进而获得前景车辆边缘,用形态学方法对其进行修复,寻找车辆的外轮廓,确定跟踪区域;由于车辆运动的特殊性,以当前帧的车速作为下一帧车速的预测值,并结合跟踪区域的外形信息进行匹配。从实验效果来看,该算法简单有效,适合于实时的车辆检测和跟踪系统。     

Impact of vehicles on benthic macrofauna on a subtropical sand beach

Our study aimed to identify possible relationships between the structure of the benthic macrofauna and the intense use of vehicles in Cassino Beach. Physical changes in the sediment were identified, with high compaction in the sector most affected by the vehicles, especially during the summer. The benthic macrofauna was significantly affected by vehicles, with lower densities observed in the most impacted sector, mainly in the summer, unlike the control sector, where higher densities were observed during the pre-summer and summer. We concluded that the vehicle traffic changes the physical environment of the beach and consequently affects the benthic community in the face of this disturbance. We conclude that the benthic macrofauna is highly impacted by vehicle traffic at Cassino Beach, mainly in the period with the highest traffic, and alternatives are needed for this impact, helping to recover this ecosystem.     

Adaptive multiuser detection for underwater acoustical channels

An underwater acoustic local area network (ALAN) provides multipoint-to-point telemetry between many high-rate, ocean-bottom sensors and a central, surface-deployed receiver in the 10-30 kHz vertical acoustical channel. Ocean-bottom modems initiate the transmission process by requesting data channel time slots via a common narrow-band request channel. Request packets overlap in time and frequency in this channel, and the throughput and average transmission delay rely heavily on the successful resolution of the request packet collisions. This paper presents the design, analysis, and experimental demonstration of a request channel receiver capable of resolving collisions between several asynchronous and cochannel packets. The receiver algorithm differs from standard capture schemes (by demodulating the data from both strong and weak transmitters), conventional spread-spectrum receivers (by overcoming the near-far problem), and existing multiple-access demodulation techniques (by adapting to the number of interfering signals, and the unknown phase, Doppler, amplitude, and timing of each signal in the collision). The receiver demodulates the collided packets by decision-directed techniques through a novel method of estimating the interference for each user which minimizes error propagation due to inaccurate tentative decisions. An inwater experiment illustrates that this technique is extremely desirable for collision resolution in underwater acoustic local area networks, and also for underwater autonomous vehicles with both sidescan sonar as well as acoustic telemetry links     

SAR, NAUTILE, SAGA, ELIT--Four new vehicles for underwater work and exploration: The IFREMER approach

Manned or unmanned, towed, tethered, or acoustically remote-controlled underwater vehicles are the necessary tools of deep-ocean exploration as well as the exploitation of the continental shelf mineral resources. It is possible to identify categories of tasks for which a type of vehicle is best suited, and in each of those categories, the Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), the French agency for ocean research, has designed new sophisticated vehicles, giving to scientists and engineers a set of tools to fulfill most of their needs. SAR is a broad-range high-resolution side-scan sonar designed for detailed acoustic surveys; NAUTILE is a 6000-m capability manned submersible; SAGA is a large autonomy lock-out 600-m submersible. Finally, ELIT will be a totally autonomous vehicle for inspection of oil underwater structures.