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。     

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.     

Smoothed A* algorithm for practical unmanned surface vehicle path planning

An effective path planning or route planning algorithm is essential for guiding unmanned surface vehicles (USVs) between way points or along a trajectory. The A* algorithm is one of the most efficient algorithms for calculating a safe route with the shortest distance cost. However, the route generated by the conventional A* algorithm is constrained by the resolution of the map and it may not be compatible with the non-holonomic constraint of the USV. In this paper an improved A* algorithm has been proposed and applied to the Springer USV. A new path smoothing process with three path smoothers has been developed to improve the performance of the generated route, reducing unnecessary ‘jags’, having no redundant waypoints and offering a more continuous route. Both simulation and experimental results show that the smoothed A* algorithm outperforms the conventional algorithm in both sparse and cluttered environments that have been uniformly rasterised. It has been demonstrated that the proposed improved A* route planning algorithm can be applied to the Springer USV providing promising results when tracking trajectories.     

Radar-based collision avoidance for unmanned surface vehicles

Unmanned surface vehicles (USVs) have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into realtime marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle (V-obstacle) which adjusts the USV’s heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.     

Model-free adaptive control method with variable forgetting factor for unmanned surface vehicle control

We present a new type of model-free adaptive control (MFAC) method based on an adaptive forgetting factor for unmanned surface vehicle (USV) heading control under uncertain influence. Firstly, we analyze the compact form dynamic linearization based MFAC (CFDL-MFAC) method and its main problems with regard to USV heading control. Secondly, in order to address the problems of overshoot, oscillation, and slow convergence of the heading control with the MFAC method and considering the dynamics of the USV heading control subsystem, we introduce an adaptive forgetting factor into the CFDL-MFAC to arrive at the CFDL-MFAC with variable forgetting factor (CFDL-MFAC-VFF) method. Our simulation studies show that the CFDL-MFAC-VFF method yields low overshoot and low oscillations and is insensitive to changes in the system parameters and output error. Finally, our field experiments with the small USV “Dolphin-I” demonstrate the effectiveness and engineering practicability of our proposed method.     

Trajectory-cell based method for the unmanned surface vehicle motion planning

A trajectory-cell based method was proposed for unmanned surface vehicle (USV) motion planning to combine the expression of the dynamic constraints and the discretization of the search space. The dynamic constraints were expressed by the USV trajectories produced by the mathematical model. The search space was performed by the discretization rules with the consideration of the path continuity, the search convenience and the maneuvering simplification. Therefore, the trajectory-cells were the discretized trajectories, which made the search space meet the USV dynamic constraints, and guaranteed the final spliced path continuous. After abstracting the characteristics of those cells, the available waypoints and headings were represented as the search indexes. Finally, a trajectory-cell based path searching strategy was proposed by determining the cost function of the A* algorithm. The results showed that the proposed algorithm can plan a practical motion path for the USV.     

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.     

Information fusion model-free adaptive control algorithm and unmanned surface vehicle heading control

Based on the model-free adaptive control (MFAC) theory, the heading control problem of unmanned surface vehicles (USVs) with uncertainties is explored. First, as a USV’s heading subsystem does not satisfy the quasilinear assumption of the MFAC theory, a new type of input and output information fusion MFAC, i.e., the IOIF–MFAC algorithm is proposed. The novel algorithm proposed herein renders the MFAC theory applicable to the heading control of USVs. Next, the input and output information of the heading subsystem, namely the rudder angle and heading angle, are combined, and the data model of the heading subsystem is subsequently deduced using a compact format dynamic linearization method. Based on which, the stability of the control system is proved. Finally, the effectiveness and practicability of the IOIF–MFAC algorithm are verified by simulation and field experiments through the “Dolphin IB” test platform developed by our group.     

无人船运动控制方法综述

为实现无人船海上自主作业,无人船运动控制的快速性、准确性以及鲁棒性亟待提高。首先从全驱动控制和欠驱动控制角度,分别概括了国内外无人船航向控制、航速控制、轨迹跟踪控制以及路径跟踪控制的主流控制方法。其次,归纳总结了处理海洋环境不确定扰动的研究进展,包括扰动的建模和消除、抑制扰动的主流方法。最后,总结了无人船运动控制现状与存在的问题,并从工程应用和理论研究两个角度对未来的研究方向进行了展望。     

Minimum time-energy trajectory planning for automatic ship berthing

A ship optimal trajectory planning method based on the dynamic model of the ship is presented. First a mathematical modular model is introduced for describing the non-linear dynamics of the ship. Then the problem of optimal trajectory planning is discussed. The trajectory is obtained through the optimization of a time-energy criterion, taking into account constraints on the steering system, environment, non-linearities, and non-convexity of the state space equations. The discrete augmented Lagrangian approach is used to compute the optimal constrained controller. The method was programmed on a HP700 workstation. This approach was applied to automatic ship berthing maneuver     

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.     

Design of a sliding mode fuzzy controller for the guidance and control of an autonomous underwater vehicle

This work demonstrates the feasibility of applying a sliding mode fuzzy controller to motion control and line of sight guidance of an autonomous underwater vehicle. The design method of the sliding mode fuzzy controller offers a systematical means of constructing a set of shrinking-span and dilating-span membership functions for the controller. Stability and robustness of the control system are guaranteed by properly selecting the shrinking and dilating factors of the fuzzy membership functions. Control parameters selected for a testbed vehicle, AUV-HM1, are evaluated through tank and field experiments. Experimental results indicate the effectiveness of the proposed controller in dealing with model uncertainties, non-linearities of the vehicle dynamics, and environmental disturbances caused by ocean currents and waves.     

一种新型无人船海洋水深测量技术

在海洋测深中,由于波浪和潮汐的影响,调查船或无人船所测量的瞬时水深不能直接作为海图水深。本文提出了一种新型的无人船海洋水深测量技术,以评估搭载RTK和单波束测深仪的无人船用于海洋水深测量的潜能。首先,使用无人船所搭载RTK的厘米级精度高程数据,通过低通滤波剔除波浪信息,而获得海平面高程。然后,基于潮汐表和无人船海平面高程,构建了一种参考椭球面和海图的两个基准面之差的获取方法;在常规的海洋调查中,该基准面差通常需要由长期的验潮获得。最后,利用海图基准和无人船测量的瞬时水深的转换关系,计算出海图水深。在海南省蜈支洲岛周边海域,利用自研发的无人船“USBV”开展了相关海上实验,以验证所提出的技术方法。实验结果验证了该无人船海洋水深测量技术。     

Fòlaga: A low-cost autonomous underwater vehicle combining glider and AUV capabilities

The paper describes the current developments of a class of low-cost, light-weight autonomous underwater vehicles for coastal oceanographic applications; the vehicle class is named Fòlaga, the Italian name of an aquatic bird that swims on the water surface and dives to catch fish. The main design characteristics of the most recent vehicle of the class, the Fòlaga III, are reviewed. Navigation and control system design are discussed, with particular attention to the diving phase, which is accomplished as in oceanographic gliders by varying the vehicle buoyancy and attitude. Experimental results show that the PID robust controllers implemented are effective in the diving control phase. Finally, a distributed cooperation algorithm to be applied by a team of Fòlaga-like vehicles in adaptive oceanographic sampling applications is described. The algorithm optimizes area coverage while taking into account the accuracy in the reconstruction of the oceanographic field and inter-vehicle communication through a range constraint. The resulting dynamic programming algorithm can be implemented in a distributed fashion among the team components.     

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.     

一类全局最优化问题的动态隧道方法

研究了连续变量函数的全局最优化问题 ,给出了动态隧道方法。该动态隧道方法由局部搜索和动态隧道 2个阶段构成。在局部搜索阶段用了动态系统方法。对全局最优化问题的实例进行了数值实验 ,数值结果表明了该方法的稳健性和有效性。     

Time-domain simulation of berthing problem between FPSO and shuttle tanker in waves

A time-domain simulation method based on potential flow model has been developed to investigate the berthing problem between two floating bodies in wave. The boundary value problem is formulated with respect to an earth-fixed coordinate system because the relative positions of the two vessels continuously change during the berthing operation. The classical finite element method is used to solve the Laplace equation in the fluid domain with moving boundary. The linearized free-surface boundary conditions are integrated in time by applying 4th-order Adams–Bashforth–Moulton method. A simple re-mesh algorithm with local and global mesh systems is introduced to update mesh by considering large horizontal movement of the berthing vessel. The developed numerical method is used to investigate the berthing problem between a FPSO and shuttle tanker in waves. The focus is on the wave-induced motion response during the berthing process. The characteristics of the motion responses in berthing operation are examined with various wave frequencies, berthing speeds and wave headings.     

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     

Study on Ship Automatic Berthing System with Mooring Lines

This study describes an automatic berthing system with mooring lines. It is designed to be berthed by using mooring device on the upper deck of a ship. It is to berth once maintaining parallel with the quay by controlling both forward and aft breast lines. Berthing method is used through length adjustment of mooring lines connected between ship and quay by controlling the angular velocity and the torque of hydraulic motor in mooring device. The study is conducted under three changing conditions of draft, such as even-keel, rise of the gravity center and trim to stern. Variables affecting berthing stability are determined based on the control performance of each condition. Bond graphs method is used to model the system. Controller is designed as PID control method of reference-model algorithm. The control program is composed of synchronous control system based on the equations derived with the numerical analysis. The tank test is conducted to verify the usefulness of the control program.     

Adaptive fuzzy controller design for dynamic positioning system of vessels

This paper develops an adaptive fuzzy controller for the dynamic positioning (DP) system of vessels with unknown dynamic model parameters and unknown time-varying environmental disturbances. The controller is designed by combining the adaptive fuzzy system with the vectorial backstepping method. An adaptive fuzzy system is employed to approximate the uncertain term induced by unknown dynamic model parameters and unknown time-varying environmental disturbances. It is theoretically proved that the proposed adaptive fuzzy DP controller can make the vessel be maintained at the desired values of its position and heading with arbitrary accuracy, while guaranteeing the uniform ultimate boundedness of all signals in the closed-loop DP control system of vessels. Simulation studies with comparisons on a supply vessel are carried out, and the results illustrate the effectiveness of the proposed control scheme.