Classification of Sailboat Tell Tail Based on Deep Learning

The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface.It is of great significance to make accurate judgement on the drift of the tell tail of the sailboat during sailing for the best sailing effect.Normally it is difficult for sailors to keep an eye for a long time on the tell sail for accurate judging its changes,affected by strong sunlight and visual fatigue.In this case,we adopt computer vision technology in hope of helping the sailors judge the changes of the tell tail in ease with ease.This paper proposes for the first time a method to classify sailboat tell tails based on deep learning and an expert guidance system,supported by a sailboat tell tail classification data set on the expert guidance system of interpreting the tell tails states in different sea wind conditions,including the feature extraction performance.Considering the expression capabilities that vary with the computational features in different visual tasks,the paper focuses on five tell tail computing features,which are recoded by an automatic encoder and classified by a SVM classifier.All experimental samples were randomly divided into five groups,and four groups were selected from each group as the training set to train the classifier.The remaining one group was used as the test set for testing.The highest resolution value of the ResNet network was 80.26%.To achieve better operational results on the basis of deep computing features obtained through the ResNet network in the experiments.The method can be used to assist the sailors in making better judgement about the tell tail changes during sailing.

Analysis of Influencing Factors on Lift Coefficients of Autonomous Sailboat Double Sail Propulsion System Based on Vortex Panel Method

Sail is the core part of autonomous sailboat and wing sail is a new type of sail. Wing sail generates not only propulsion but also lateral force and heeling moment. The latter two will affect the navigation status and bring resistance. Double sail can effectively reduce the center of wind pressure and heeling moment. In order to study the effect of distance between two sails, airfoil and attack angle on the total lift coefficient of double sail propulsion system, pressure coefficient distribution and lift coefficient calculation model have been established based on vortex panel method. By using the basic finite solution, the fluid dynamic forces on the two-dimensional sails are computed.The results show that, the distance in the range of 0 to 1 time chord length, when using the same airfoil in the fore and aft sail, the total lift coefficient of the double sail increases with the increase of distance, finally reaches a stable value in the range of one to three times chord length. Lift coefficients of thicker airfoils are more sensitive to the change of distance. The thicker the airfoil, the longer distance is required of the total lift coefficient toward stable.When different airfoils are adopted in fore and aft sail, the total lift coefficient increases with the increase of the thickness of aft sail. The smaller the thickness difference is, the more sensitive to the distance change the lift coefficient is. The thinner the fore sail is, the lower the influence will be on the lift coefficient of aft sail.

Influence of Autonomous Sailboat Dual-Wing Sail Interaction on Lift Coefficients

To analyze the influence of the chord length ratio and angle of attack on lift coefficients and explore the interaction mechanism between the two,we established a calculation model of the pressure distribution coefficient on the airfoil surface and lift coefficient of a dual-wing sail on the basis of the vortex panel method.Computational fluid dynamics was used in auxiliary calculation and analysis.Results revealed a reciprocal interference between the front-wing and rear-wing sails.The total lift coefficient of the dual-sail increased with an increase in the front sail chord length.The lift coefficient of the rear sail decreased with an increase in the front sail chord length or angle of attack.The front sail wake affected the pressure distribution on the upper and lower surfaces of the rear sail leading edge.

Path Planning and Navigation of Oceanic Autonomous Sailboats and Vessels: A Survey

Oceanic autonomous surface vehicles(ASVs) are one kind of autonomous marine robots that have advantages of energy saving and is flexible to use. Nowadays, ASVs are playing an important role in marine science, maritime industry, and national defense. It could improve the efficiency of oceanic data collection, ensure marine transportation safety, and protect national security. One of the core challenges for ASVs is how to plan a safe navigation autonomously under the complicated ocean environment. Based on the type of marine vehicles, ASVs could be divided into two categories: autonomous sailboats and autonomous vessels. In this article, we review the challenges and related solutions of ASVs' autonomous navigation, including modeling analysis, path planning and implementation. Finally, we make a summary of all of those in four tables and discuss about the future research directions.

Sailboat navigation control system based on spiking neural networks

In this paper,we presented the development of a navigation control system for a sailboat based on spiking neural networks(SNN).Our inspiration for this choice of network lies in their potential to achieve fast and low-energy computing on specialized hardware.To train our system,we use the modulated spike time-dependent plasticity reinforcement learning rule and a simulation environment based on the BindsNET library and USVSim simulator.Our objective was to develop a spiking neural network-based control systems that can learn policies allowing sailboats to navigate between two points by following a straight line or performing tacking and gybing strategies,depending on the sailing scenario conditions.We presented the mathematical definition of the problem,the operation scheme of the simulation environment,the spiking neural network controllers,and the control strategy used.As a result,we obtained 425 SNN-based controllers that completed the proposed navigation task,indicating that the simulation environment and the implemented control strategy work effectively.Finally,we compare the behavior of our best controller with other algorithms and present some possible strategies to improve its performance.

Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle

Suffering from actuator failure and complex sideslip angle,the motion control of a sailboat becomes challenging.In this paper,an improved double finite-time observer-based line-of-sight guidance and finite-time control(IDFLOS-FC)scheme is presented for path following of sailboats.The salient features of the proposed IDFLOS-FC scheme are as follows:(1)Considering the problem of actuator failure,an actuator failure model is introduced into the dynamics model of a sailboat.(2)The time-varying sideslip angle of the sailboat is accurately observed by the double finite-time sideslip observers(DFSOs),which reduces the error in line-of-sight(LOS)guidance.(3)A radial basis function(RBF)neural network is used to fit the uncertainty of the model,and the upper bound of the sum of fault effects and external disturbances is estimated based on adaptive theory,so that the controller has accurate tracking and interference suppression.(4)According to the Lyapunov method,the system is finite-time stable.Finally,simulation was used to validate the effectiveness of the method.

基于改进快速行进平方法的无人帆船动态避碰方法

[目的]为解决无人帆船在开阔水域的多船避碰问题,对基于改进快速行进平方(IFMS)法的局部动态避碰算法进行研究。[方法]考虑到帆船的速度不可控,将其避碰行为转化为航向控制问题,并以总势场梯度下降方向为期望避碰航向。当帆船没有碰撞危险或顺风航行时,仅通过构造时间势场来避开所有静止不规则障碍并到达目标点;而当帆船存在航行约束时,根据《国际海上避碰规则》(COLREGS)为特定会遇场景设计高斯似然函数用以动态地构建障碍势场。同时,考虑到帆船的航行死区,引入局部风势场,实现帆船动态避碰与“之”字形航行策略相结合的应用需求。[结果]结果显示,所提算法可以使无人帆船在遵守避碰规则和避免航行死区的同时,成功地在各种会遇场景下实现与其他帆船、受限机动船的避碰操作,相比原始快速行进平方(FMS)算法,逆风航行时间大大缩短,避碰航迹也更加合理、安全。[结论]所提方法符合帆船运动特性及避碰规则,在复杂环境下具有较高的安全性和鲁棒性,对无人帆船自主避障技术发展具有一定的科学价值。

激光雷迪尔级帆船水动力特性试验与数值计算研究

采用试验观测和数值计算的方法研究了六自由度激光雷迪尔级帆船的水动力特性.设计了一套帆船六元力试验测量方法,通过拖曳水池试验获得帆船的水动力特性.采用雷诺时均计算方法和重叠网格技术,通过对试验和仿真的六元力结果进行对比,验证了数值计算方法的准确性.对不同航行姿态下的帆船水动力性能进行了模拟,分析了船体航速、迎角、侧倾角、漂角四个因素对帆船六元水动力的影响规律.研究结果表明:对纵向力影响权重较高的因子是航速和迎角,纵向力与航速呈非线性关系;对横向力影响较大的因子是漂角且两者呈线性关系;侧倾力矩主要受侧倾角和漂角的影响,随侧倾角的增加先减小后增大,在侧倾角为15°附近出现拐点;俯仰力矩受航速和迎角影响较大,随迎角的增大呈线性增大关系;转首力矩对漂角变化响应最大,随漂角增大线性增大.文中获得的六元水动力特性和数据可为提高帆船的操纵性提供重要数据支撑.

社会转型视野中的湖南木帆船运输业探析(1949—1952)

1949—1952年是国民经济恢复时期,社会急剧变革,各行业在新民主主义经济秩序下重建和发展。木帆船运输市场得以重建,成为当时重要的运输力量。以湖南为例,新中国成立后,木帆船运输业逐渐恢复,建立了新民主主义的运输市场秩序;降低运价,加强管理,在城乡物资交流中发挥着民船联运的优势,大运输体系建立起来;土产、矿产和粮食得以外运,工业品和食盐输往农村,农村初级市场末端得以拓展,新商业路线得到开辟,在国家工程建设中发挥着重要作用。

基于模型预测控制的无人帆船轨迹跟踪方法

[目的]面向无人帆船在水面、水下跨域异构海洋机器人的协同作业场景,提出基于模型预测控制(MPC)的无人帆船轨迹跟踪方法。[方法]针对“海鸥”号无人帆船,建立其动力学模型及运动学模型,通过分析无人帆船动力学特点及执行器约束条件,构建MPC目标函数及系统约束条件,将无人帆船的轨迹跟踪问题转化为优化问题,并利用Matlab软件开展仿真实验验证。[结果]仿真结果表明,与“帆–舵”分离的PID轨迹跟踪控制方法相比,所提出的无人帆船“帆–舵”联合MPC控制方法更便于添加约束条件,其在风向变化的情况下能以更小的轨迹跟踪误差来更快地收敛于指定轨迹,且其可以实现逆风折线航行。[结论]研究成果可为无人帆船的帆、舵控制提供新的思路,提高其轨迹跟踪能力,进一步为无人帆船与AUV的高效协同作业提供技术保障。

无人帆船刚性翼帆翼型优化研究

刚性翼帆无人帆船在阵风或恶劣海况下航行时,作用在翼帆上的空气动力强度变化较大,导致翼型空气动力学性能变差,影响无人帆船的航行性能。采用Bezier曲线方程建立翼型的数学模型和NSGA-II多目标优化算法,集成三维CAD软件SolidWorks和CFD软件STAR CCM+,以最大推力和最小侧向力为优化目标对刚性翼帆的翼型进行优化。结果表明,在15°帆向角下和(30~80)°航向角范围内,优化翼型比初始翼型推力平均值增加,侧向力基本保持不变。优化翼型在保证无人帆船航行稳性不变的情况下,有助于提升无人帆船的快速性和机动性。

基于数据融合的无人帆船真风计算方法

针对无人帆船真风获取困难且所用风传感器受帆船姿态影响的问题,提出了一种基于姿态信息、相对风和航行风融合的无人帆船真风计算方法。首先利用姿态仪获得帆船的俯仰角和横滚角,通过空间坐标旋转变换矫正相对风测量结果;其次利用卡尔曼滤波算法对航行风和矫正后的相对风进行滤波;最后利用扩展卡尔曼滤波进行真风融合计算。实验证明,该方法能够有效抑制帆船运动对风测量的影响,准确提取真风风速和风向,满足无人帆船航行控制需求。

明至民国时期无锡木船业的发展初探

无锡民间造船业可追溯至明代。随着社会经济的发展,货物流通、商旅往返、渔业捕捞等对船只的需求益盛,至清末民初,无锡木船业发展达到鼎盛,形成了以“五姓十三家”从业人员为主的造船行业繁荣景象,杨、蒋、尤、徐、邵五姓宗族也由此成为江苏境内的造船大户。通过对地方文献的梳理,可以了解无锡木船业的发展历程,探知当地舟船的主要种类及其用途,并以无锡代表性船型——西漳船为例,展现当地木帆船的主要特点与建造工艺。

帆船直线航行比赛最优路径动态规划方法研究

针对帆船直线航行比赛的赛场情况,提出一种基于模糊综合评价和动态规划理论的帆船直航训练最优路径动态规划方法.首先以模糊逻辑为基础,建立帆船相对于目标点的隶属函数,并以此描述帆船的当前位置和方向信息;然后综合考虑行驶速度和接近目标点两个因素,建立综合评价函数,并以航道宽度为限制条件,利用动态规划原理分阶段进行航向决策.最后通过仿真验证了算法的有效性.

我国产学研合作动力机制研究

认为动力机制在很大程度上影响产学研合作的效果,通过分析影响企业、高等院校和科研院所合作的动力因素和阻力因素,提出了一种产学研合作的帆船动力机制模型。运用该模型深入研究了我国产学研合作的动力机制,并指出产学研合作应充分认识"合力"的重要性,通过"聚力"、"借力"和"避力"来提升产学研合作效果的政策性结论。

基于模糊综合评价的帆船行驶最优路径规划方法

路径规划是帆船比赛取胜的重要环节。综合栅格法和模糊概念,提出了基于模糊综合评价的帆船行驶最优路径规划方法。该方法采用栅格法建立帆船航行的二维平面信息,以模糊逻辑为基础,结合帆船的运动信息建立帆船在运动平面上的二维隶属函数模型,并采用模糊综合评价思想,综合考虑行驶速度和接近目标2个因素建立综合评价函数,进行行驶方向决策。利用宽度优先搜索算法实现全局最优路径搜索。仿真结果证明,该路径规划方法能够取得较好的规划结果,对指导帆船运动员进行科学训练有很好的应用价值。

基于Sugeno模糊模型的帆船控制方法研究

针对非线性、时变的帆船航行系统,提出一种基于Sugeno模糊模型的帆船控制新方法.采集舵手的航行经验建立知识库,将专家知识融合到控制系统中,提高了控制系统的智能度;采用Sugeno模糊模型,将舵角的非线性控制局部线性化,并设计相应的局部线性控制器,通过模糊推理综合各局部线性控制器的输出,得到全局控制量.仿真结果表明,该方法能实现对帆船航向的智能控制,具有一定的实用价值.

不同纵倾角度下激光雷迪尔级帆船船体水动力性能研究

为掌握不同纵倾角度下激光雷迪尔级帆船船体水动力性能的差异,基于数值模拟方法对激光雷迪尔级帆船船体水动力性能进行了研究。通过参数化来确定船体的排水量及自由液面位置,考虑自由液面的影响,对不同纵倾角度的激光雷迪尔级帆船船体粘性绕流场进行数值模拟,得到不同纵倾角度下的船体阻力、表面压力和兴波情况,分析了纵倾角度对船体速度的影响和船体兴波能量损失情况,为提高帆船运动员控制运动帆船能力提供了科学依据。

帆船的模糊自适应控制方法研究

针对非线性、时变的帆船航行系统,提出了一种基于T-S模糊模型的帆船模糊自适应控制新方法.该方法采用T-S模糊模型,将舵角的非线性控制局部线性化,设计相应的局部线性控制器,通过模糊推理综合各局部线性控制器的输出,得到全局控制量.利用线性神经网络技术的自学习技术,获取模糊推理规则,优化模糊控制器的参数,提高系统的自适应性.仿真结果表明,该方法能实现对帆船航向的智能控制,具有一定的实际应用价值.

赛场环境实时变化的帆船比赛最优路径规划

最优行驶路径规划是帆船比赛取胜的关键环节。文章提出了赛场环境参数实时变化时,基于模糊综合评价的帆船直航比赛最优路径规划方法。该方法利用模糊综合评价思想,综合考虑行驶速度和接近目标两个因素建立综合评价函数进行航行方向决策,赛场环境参数变化时,从当前航行位置相对目标点重新进行路径规划,保证局部状态始终最优,利用宽度优先搜索算法实现全局最优路径搜索。仿真结果证明,该路径规划方法能够取得较好的规划结果,对指导帆船运动员进行科学训练有很好的理论意义和应用价值。