Trajectory planning and tracking control for underactuated unmanned surface vessels

The trajectory planning and tracking control for an underactuated unmanned surface vessel(USV) were addressed.The reference trajectory was generated by a virtual USV,and the error equation of trajectory tracking for underactuated USV was obtained,which transformed the tracking and stabilization problem of underactuated USV into the stabilization problem of the trajectory tracking error equation.A nonlinear state feedback controller was proposed based on backstepping technique and Lyapunov's direct method.By means of Lyapunov analysis,it is proved that the proposed controller ensures that the solutions of closed loop system have the ultimate boundedness property.Numerical simulation results are presented to validate the effectiveness and robustness of the proposed controller.

Analysis of Design Directions for Unmanned Surface Vehicles (USVs)

In recent years, because of the development of marine military science technology, there is a growing interest in the unmanned systems throughout the world. Also, the demand of Unmanned Surface Vehicles (USVs) which can be autonomously operated without the operator intervention is increasing dramatically. The growing interests lie in the facts that those USVs can be manufactured at much lower costs, and can be operated without the human fatigue, while can be sent to the hostile or quite dangerous areas that are inherently unhealthy for human operators. The utilization and the deployment of such vessels will continue to grow in the future. In this paper, along with the technological development of unmanned surface vehicles, we investigate and analyze the cases of already developed platforms and identify the trends of the technological advances. Additionally, we suggest the future directions of development.

Interpolation Technique for the Underwater DEM Generated by an Unmanned Surface Vessel

High-resolution underwater digital elevation models(DEMs)are important for water and soil conservation,hydrological analysis,and river channel dredging.In this work,the underwater topography of the Panjing River in Shanghai,China,was measured by an unmanned surface vessel.Five different interpolation methods were used to generate the underwater DEM and their precision and applicability for different underwater landforms were analyzed through cross-validation.The results showed that there was a positive correlation between the interpolation error and the terrain surface roughness.The five interpolation methods were all appropriate for the survey area,but their accuracy varied with different surface roughness.Based on the analysis results,an integrated approach was proposed to automatically select the appropriate interpolation method according to the different surface roughness in the surveying area.This approach improved the overall interpolation precision.The suggested technique provides a reference for the selection of interpolationmethods for underwater DEMdata.

Trajectory tracking control for underactuated unmanned surface vehicles with dynamic uncertainties

The trajectory tracking control problem for underactuated unmanned surface vehicles(USV) was addressed, and the control system took account of the uncertain influences induced by model perturbation, external disturbance, etc. By introducing the reference, trajectory was generated by a virtual USV, and the error equation of trajectory tracking for USV was obtained, which transformed the tracking problem of underactuated USV into the stabilization problem of the trajectory tracking error equation. A backstepping adaptive sliding mode controller was proposed based on backstepping technology and method of dynamic slide model control. By means of theoretical analysis, it is proved that the proposed controller ensures that the solutions of closed loop system have the ultimate boundedness property. Simulation results are presented to illustrate the effectiveness of the proposed controller.

A Review of Current Research and Advances in Unmanned Surface Vehicles

Following developments in artificial intelligence and big data technology,the level of intelligence in intelligent vessels has been improved.Intelligent vessels are being developed into unmanned surface vehicles(USVs),which have widely interested scholars in the shipping industry due to their safety,high efficiency,and energy-saving qualities.Considering the current development of USVs,the types of USVs and applications domestically and internationally are being investigated.USVs emerged with technological developments and their characteristics show some differences from traditional vessels,which brings some problems and advantages for their application.Certain maritime regulations are not applicable to USVs and must be changed.The key technologies in the current development of USVs are being investigated.While the level of intelligence is improving,the protection of cargo cannot be neglected.An innovative approach to the internal structure of USVs is proposed,where the inner hull can automatically recover its original state in case of outer hull tilting.Finally,we summarize the development status of USVs,which are an inevitable direction of development in the marine field.

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 real- time 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.

LSTM-DPPO based deep reinforcement learning controller for path following optimization of unmanned surface vehicle

To solve the path following control problem for unmanned surface vehicles(USVs),a control method based on deep reinforcement learning(DRL)with long short-term memory(LSTM)networks is proposed.A distributed proximal policy opti-mization(DPPO)algorithm,which is a modified actor-critic-based type of reinforcement learning algorithm,is adapted to improve the controller performance in repeated trials.The LSTM network structure is introduced to solve the strong temporal cor-relation USV control problem.In addition,a specially designed path dataset,including straight and curved paths,is established to simulate various sailing scenarios so that the reinforcement learning controller can obtain as much handling experience as possible.Extensive numerical simulation results demonstrate that the proposed method has better control performance under missions involving complex maneuvers than trained with limited scenarios and can potentially be applied in practice.

基于移动长基线和导航误差修正的USV/UUV协同导航算法

针对无人水下航行器长时间协同运动,惯性导航误差累积增长的问题,为减小USV/UUV之间相对导航误差,提高UUV导航精度,提出一种基于移动长基线和导航误差修正的无人水面艇(USV)/无人水下航行器(UUV)协同导航算法。该算法基于水声通信测距,首先由UUV收集其与USV间相对距离信息,计算相对导航误差修正量,接着将修正量添加到USV当前导航位置中,结合USV与UUV间的队形设置以及UUV自身低精度导航设备解算的位置,最终实现对UUV累积的惯导位置误差修正。仿真结果表明,在USV/UUV协同运动过程中,通过对修正后UUV位置信息以及UUV惯导解算得到的位置量进行融合,可显著提高UUV导航精度。

一种UAV-USV-UUV跨域协同时钟同步算法

随着海洋科学技术的发展,水下任务更加强调跨平台系统的协作,然而不同应用场景对时钟同步的要求不同,由于水下通信的弱通信与高延迟,对涉及多场景的异构系统,需要新的同步方法。针对随机时延影响下的全网时钟同步问题,文中提出了基于神经网络的无人机(UAV)-无人水面艇(USV)-无人水下航行器(UUV)跨域协同的时钟同步算法。首先,考虑随机时延影响,将USV时钟作为基准时钟;其次,通过递推滤波和神经网络对UAV时钟偏差进行校正;最后,USV辅助UUV估计水下的长时延,设计了神经网络算法估计时钟漂移和时钟偏移。通过仿真验证了上述算法的有效性。

基于扰动观测的USVs协同路径跟踪控制

论文针对多无人艇协同控制系统中出现的通信资源有限、存在外界环境扰动及收敛速度慢等问题,提出了一种基于扰动观测器的固定时间无人艇协同路径跟踪控制算法。首先,结合固定时间算法、参数协同算法及事件触发通信机制,设计了固定时间事件触发参数协同模块,以此协同期望路径上的参数、计算无人艇在各自期望路径上的理想位置并降低通讯资源消耗。其次,为了使无人艇不受外界环境干扰并令其固定时间内实现轨迹跟踪控制,设计了固定时间轨迹跟踪控制模块,其中包括固定时间扰动观测器以及固定时间跟踪控制器。文中各模块算法都能保证固定时间收敛,因而整个系统能够实现固定时间收敛。仿真结果验证了论文设计算法的有效性。

基于改进粒子群算法的 USV 航向分数阶控制

针对欠驱动水面船舶(underactuated surface vessel,USV)航向保持稳定性问题,对船舶自动舵控制系统设计了分数阶PIλDμ控制器。积分阶次λ和微分阶次μ的引入使得分数阶比例-积分-微分(proportion integration differentiation,PID)PIλDμ控制器具有更好的鲁棒性和抗扰动能力,但同时也加大了算法设计的难度。使用改进粒子群算法对分数阶PIλDμ控制器参数进行整定,即解决了粒子群算法容易使粒子陷入局部最优问题,又解决了分数阶PIλDμ控制器整定参数多、设计复杂问题。通过仿真对比实验,结果表明,该控制器能很好地根据船舶动态特性变化,自动进行适应性参数优化,具有跟踪速度快、航向控制超调小以及抗扰性强等优点。

多USV协同系统研究现状与发展概述

无人水面艇(Unmanned Surface Vehicle,USV)具有较高的智能化程度,较好的隐身性能,较强的机动能力以及较低的造价,被认为是一种作战用途广泛的新概念武器。在无人驾驶运载工具中,USV发展相对较晚,但已逐渐成为一个研究热点课题。文中简述目前国内外USV的研究情况;重点介绍多USV协同系统的现状;阐述高性能艇型、控制体系、通信技术、避碰、任务规划与决策5项关键技术;提出未来发展趋势;展望多USV协同系统在海上补给、水上安全保护、完善无人作战系统、水文气象信息采集和水面搜救方面的应用前景。

USV-LIF遥测系统的控制系统设计与实现

无人船作为一种新型平台,在海洋环境监测中具有布放灵活、自动测量等优势。对于近岸港口等溢油事故发生频繁区域的环境监测,相比于传统的机载和船载溢油激光荧光遥感技术,采用无人船平台搭载激光荧光传感器进行探测更为方便有效。本文对基于无人船的激光荧光(USV-LIF)遥测系统进行总体方案设计,并详细设计了其控制系统,该系统包括岸基远程控制模块和USV-LIF现场机控制模块两部分。利用无线网络通信链路实现从岸基终端对USV-LIF现场机的远程控制与通信,并通过现场机的控制模块实现对USV-LIF现场机的仪器状态控制、数据采集以及时序控制等功能。在实验室条件下,对USV-LIF遥测系统的整体运行、远程控制数据传输以及系统长时间连续工作进行了模拟联调测试,结果表明,所研发的控制系统的功能基本达到了现场探测需求。

基于目标候选的USV海上船艇检测

海上船艇检测是无人水面艇(unmanned surface vehicle,USV)视觉系统最主要的任务之一.提出了一种基于目标候选(object proposal)的USV海上船艇检测算法.首先,基于改进的边缘框(edgebox)算法提取了图像的边缘信息,并建立“目标性”评分函数获取目标候选框;然后,对船艇目标进行方向梯度直方图(histogram of oriented gradient,HOG)特征进行建模,利用支持向量机(support vector machine,SVM),采用“自举法”训练分类器进行迭代;最后,将目标候选框的特征描述子输入到分类器中,对船艇进行检测.此外,基于USV在海天环境下的运行场景,结合海天线的特性进一步提升算法的检测性能.实验结果表明,该算法能快速、准确地检测船艇目标,且具有较高的检测率,对尺度以及光照条件的变化也有较强的鲁棒性.

基于DAMPSO算法的USVs集群攻击任务规划研究

现代防御技术的迅速发展使得水面舰艇的攻击效果大大下降,水面无人舰艇自主编队集群攻击技术已经成为未来海战的关键技术之一,多水面无人舰艇之间的任务规划是保证无人舰艇顺利、高效完成任务的关键。将水面无人舰艇集群攻击任务规划问题看成是多约束的任务分配过程,建立任务规划模型,提出了基于分布式拍卖机制的粒子群优化算法,该算法结合分布式拍卖机制对粒子群优化算法的粒子初始化和寻优过程进行改进,使得粒子既符合任务的约束条件,又保持了多样性,避免粒子在寻优过程中陷入局部最优。仿真结果表明应用分布式拍卖机制粒子群优化算法得到的方案不仅完全满足水面无人舰艇集群攻击任务的要求,而且比传统粒子群优化算法和其他群体智能算法具有更好的收敛性。

基于USV与AUV异构平台协同海洋探测系统研究综述

对基于无人水面艇(USV)和多自主水下机器人(AUVs)组成的异构协同海洋探测系统进行综述。首先介绍不同的USV与多AUVs组成的异构海洋探测系统的最新进展和应用成果,从系统设计概念和技术特点对这些异构系统进行分析和比较;其次对多水下机器人异构系统研究中的协同关键技术进行综述,重点分析协同问题中异构协同、系统任务分配、路径规划和编队控制等问题;而后从环境和硬件的外界约束以及海洋探测系统辅助技术两个方面分析海洋探测系统所面临的技术难点与问题;最后通过分析当前取得的进展和实际需求对多水下机器人异构海洋探测系统的发展前景进行展望。

面向海上搜救的UAV与USV集群协同路径跟踪控制

[目的]针对由无人机(UAV)与水面无人艇(USV)组成的异构无人集群系统,研究其在海上搜救过程中的三维协同路径跟踪控制问题。[方法]首先,在固定坐标系和机体坐标系下建立UAV和USV的运动学模型,同时建立流体坐标系,以设计适宜运动控制的三维路径跟踪控制器,并在Serret-Frenet坐标系下建立UAV和USV的路径跟踪误差模型;然后,在运动学层面设计三维视线(LOS)制导律,并基于此提出一种适用于异构海洋航行器集群的协同路径跟踪控制方法,从而使UAV与USV组成的集群系统可以有效跟踪设定的参数化路径;最后,基于李雅普诺夫稳定性理论分析该控制系统的稳定性。[结果]仿真结果验证了所提异构海洋航行器集群协同路径跟踪控制方法的有效性。[结论]研究成果可为面向海上搜救的无人航行器集群协同路径跟踪控制方法提供参考。

移动长基线定位USV的队形优化

在移动长基线定位系统中,无人水上舰船(USV)的队形以及与定位目标之间的位置关系对定位精度有着重要的影响。本文基于球面交会法,设计了一种精度评价函数。利用此精度评价函数分别研究了多USV结构对定位精度的影响;被定位目标与多USV阵型间的位置关系对定位精度的影响;量测精度对定位精度的影响。通过推理证明,得到被定位目标在4艘USV组成的正方形基阵中垂线上时定位精度最高的结论。仿真结果表明,USV队形对定位精度有显著影响。

不确定性下USV可变自主控制结构及算法

针对水面无人艇(unmanned surface vehicle,USV)在具有不确定性的实际任务形势下实现可变自主的问题,提出一种包含可变自主控制结构和自主等级决策算法的解决方案。可变自主控制结构中考虑了自主等级的划分、自主等级的评价和管理,并设计了基于多属性决策方法的自主等级决策算法。最后在USV导航任务为背景的仿真实验中,证明了可变自主系统控制结构和自主等级决策算法是合理的和有效的,同时显示了可变自主系统研究的实际意义及其对于系统规划性能的提高作用。

基于非对称模型的欠驱动USV路径跟踪控制

针对水面无人艇(unmanned surface vessel,USV)的非对称和欠驱动特性,提出了一种非对称模型下的改进视线法导向路径跟踪控制方法。首先通过对系统进行全局微分同胚变换,解决了由非对称性带来的系统系数矩阵非对角线元素存在非零项的问题;其次基于目标路径参考点建立坐标系,在视线法中引入跟踪误差函数,使视线法导向角跟随曲线路径自适应调整;然后针对系统的欠驱动特性,以目标路径切线方向速度作为虚拟控制输入,基于反步法和拉塞尔不变原理以及李亚普诺夫稳定性理论,设计了无人艇全局渐近稳定的路径跟踪控制器;最后通过仿真试验验证了所提出方法和所设计控制器的有效性和可靠性。