A new hybrid terrain coverage method for underwater robotic exploration

It is well known that it is difficult to explore underwater terrains using an autonomous underwater vehicle due to the varieties and complexities of underwater terrain elements. Since conventional underwater terrain coverage techniques are usually based on the assumption that the underwater surface is planar, they generate an unnecessary exploration path especially on steep sloped surfaces of ocean basins. This paper proposes a new type of coverage technique, the hybrid terrain coverage framework (HTCF), which considers various surface conditions in three-dimensional environments and generates an efficient exploration path for all environments. The HTCF incorporates a planar terrain coverage algorithm, a spiral path terrain coverage algorithm, and a hybrid decision module to recognize and select the most suitable technique depending on the sloped surface variations. Simulation results show that the proposed HTCF is more efficient than the conventional terrain coverage algorithm in terms of the energy consumption of the underwater vehicle.     

内河无人船局部路径规划和循迹控制

提出了内河无人船在水流中的局部路径规划算法,并在直线Line of Sight算法基础上设计了一般曲线路径的LOS循迹控制算法。将此算法结合完成了内河无人船的航行试验,实现了在落潮、涨潮等不同水流条件下的无人自主航行,验证了所提算法的有效性和实用性,对内河无人船的应用研究具有借鉴意义。     

基于分数阶PIλDμ的船舶航向控制

船舶在海上航行时受到海风、海浪和海流等环境扰动作用,这造成在不同航速下船舶动力学模型的参数不确定性,本文对船舶本体运动和风浪流干扰进行建模,提出一种基于分数阶PIλDμ的抑制风浪干扰的的航向控制算法,并与传统 PID算法进行对比,针对某型船舶动力学模型在6级海风和5级海浪海况下进行对比数字仿真。仿真结果表明,该算法在不同航速下具有较好的控制品质和鲁棒性,对风浪干扰具有良好的适应性,可应用于船舶的航向控制,易于工程实现。     

多约束条件下无人艇和无人机集群协同航迹规划

[目的]为实现海上无人集群在执行任务过程中的安全航行和通信保持,开展无人艇(USV)和无人机(UAV)集群协同航迹规划问题的研究。[方法]采用禁入和禁出地理围栏进行场景建模,将规避威胁和障碍问题转化为地理围栏约束。针对平台之间的碰撞冲突和通信连接问题,提出基于时序检测的碰撞冲突和通信保持约束判断准则。以集群平均航行时间为航迹优化函数,将多约束条件转化为惩罚函数,采用自适应差分进化算法进行优化求解。[结果]仿真结果表明,所提方法能够在威胁和障碍环境中保持无人艇和无人机集群的安全航行和通信连接,并在满足多约束的条件下实现集群平均航行时间最短。[结论]该方法可用于海上无人集群面对威胁和障碍环境时的离线航迹规划,具有一定的应用价值。     

基于差分进化算法的自主式水下航行器在时变水下环境中的快速路径规划方法（英文）

Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.     

Planning method for AUV region detection under ocean current

In this paper we present two strategies of AUV (Autonomous Underwater Vehicle) region detection and an approach to decompose the detection region according to the direction of the ocean current. In the task of local detection and identification, the algorithm against the ocean current was proposed. In the tasks of closing obstacle, going back or moving, the fuzzy logic theory was used to solve the effect of ocean current. In one of our strategies the concept of weighted journey based on the angle between heading and ocean current is suggested and the TSP‘s exact optimal result is utilized to solve the global path planning. Simulations demonstrate the feasibility of this approach.     

基于深度强化学习的智能船舶航迹跟踪控制

[目的]智能船舶的航迹跟踪控制问题往往面临着控制环境复杂、控制器稳定性不高以及大量的算法计算等问题。为实现对航迹跟踪的精准控制,提出一种引入深度强化学习技术的航向控制器。[方法]首先,结合视线(LOS)算法制导,以船舶的操纵特性和控制要求为基础,将航迹跟踪问题建模成马尔可夫决策过程,设计其状态空间、动作空间、奖励函数;然后,使用深度确定性策略梯度(DDPG)算法作为控制器的实现,采用离线学习方法对控制器进行训练;最后,将训练完成的控制器与BP-PID控制器进行对比研究,分析控制效果。[结果]仿真结果表明,设计的深度强化学习控制器可以从训练学习过程中快速收敛达到控制要求,训练后的网络与BP-PID控制器相比跟踪迅速,具有偏航误差小、舵角变化频率小等优点。[结论]研究成果可为智能船舶航迹跟踪控制提供参考。     

Hydrodynamic experiment of submerged floating tunnel under regular wave and current actions during construction period

Submerged floating tunnel (SFT) is an innovative cable-supported structural system for crossing deep and long-distance ocean environments. In the complex ocean environment, the construction of SFT needs to consider wave and current forces. Specific construction measures and control also require in-depth study and understanding of the dynamic response of SFT under such environmental loads. In this study, the dynamic response of SFT and cable forces under the action of waves alone and wave-current interactions are investigated by using a large wave-current basin. A total of 138 regular wave and wave-current cases were conducted during the experiments, and the influence of waves and wave-current interactions on the dynamic response of SFT and cable forces are discussed in detail by combining experimental data with corresponding analysis. Results show that the wave height, current velocity, and ratio of wavelength to structure size are important factors affecting the dynamic response of SFT and cable forces. The multi-anchor cable arrangement used in the present experimental tests distribute cable force more effectively and reduce the potential safety hazard caused by cable breakage. This study can provide a useful reference for the construction and control of the single SFT segment under construction in a complex ocean environment, especially under the interaction of waves and currents.     

Robustness of autonomous underwater vehicle control in variable working conditions

The performance of the control systems of autonomous underwater vehicles (AUVs) in the presence of parameter variations was studied. With an AUV working at different operating speeds and in different ocean environments, the physical parameters such as speed, hydrodynamic coefficients, or inertias may be perturbed from their nominal values. The vehicle control systems can be modeled as systems with parameter uncertainty. An existing robust control method, which uses the robustness properties of polynomials, was used for this system to calculate the permissible ranges of variation in the parameters. The method was applied to the Naval Postgraduate School AUV II and the results were verified by simulating the motion control of the vehicle under the influence of parameter perturbations.     

框架四叉树的自主水下航行器追踪动态目标研究(英文)

An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because of the uneven distribution of obstacles in the real world, the efficiency of the algorithm decreases if the global environment is represented by regular grids with all of them at the highest resolution. The framed quadtree data structure is able to more efficiently represent the environment. When planning the path, the dynamic object is expressed instead as several static objects which are used by the path planner to update the path. By taking account of the characteristics of the framed quadtree, objects can be projected on the frame nodes to increase the precision of the path. Analysis and simulations showed the proposed planner could increase efficiency while improving the ability of the AUV to follow an object.     

Application of A* algorithm for real-time path re-planning of an unmanned surface vehicle avoiding underwater obstacles

This paper describes path re-planning techniques andunderwater obstacle avoidance for unmanned surface vehicle （USV）based on multi-beam forward looking sonar （FLS）. Near-optimalpaths in static and dynamic environments with underwaterobstacles are computed using a numerical solution procedure basedon an A algorithm. The USV is modeled with a circular shape in 2degrees of freedom （surge and yaw）. In this paper, two-dimensional（2-D） underwater obstacle avoidance and the robust real-time pathre-planning technique for actual USV using multi-beam FLS aredeveloped. Our real-time path re-planning algorithm has beentested to regenerate the optimal path for several updated frames inthe field of view of the sonar with a proper update frequency of theFLS. The performance of the proposed method was verifiedthrough simulations, and sea experiments. For simulations, theUSV model can avoid both a single stationary obstacle, multiplestationary obstacles and moving obstacles with the near-optimaltrajectory that are performed both in the vehicle and the worldreference frame. For sea experiments, the proposed method for anunderwater obstacle avoidance system is implemented with a USVtest platform. The actual USV is automatically controlled andsucceeded in its real-time avoidance against the stationary underseaobstacle in the field of view of the FLS together with the GlobalPositioning System （GPS） of the USV.     

无人船在海洋调查领域的应用分析与思考

基于无人船机动灵活、安全性高、可在常规调查平台受限的水域作业的特点,将其引入海洋调查领域,作为一种新型调查平台使用。海洋调查无人船主要用于海洋环境观测和海底探测,目前其发展的关键在于如何降低平台对任务载荷的扰动,保证循线精度,提高通信系统的可靠性。根据水深、水动力和水底地形地貌等条件,将无人船工作环境分为岛礁区、滨海区、浅海区、半深海区和深海区5类;结合作业环境,以无人船的体量和吃水深度为依据,建议将其分为微型平台、小型平台、中型平台、大型平台和超大型平台,并对适配任务载荷作出分析。     

基于扩张状态观测器的双桨推进无人艇抗干扰目标跟踪控制

[目的]针对无人艇(USV)的模型不确定性和未知海洋环境扰动,提出一种基于扩张状态观测器(ESO)的双桨推进无人艇抗干扰目标跟踪控制算法。[方法]在运动学层级,设计基于平行接近制导原理的目标跟踪制导律;在动力学层级,针对模型不确定性和未知环境扰动,设计基于ESO的纵荡速度和艏摇角速度自抗扰控制律,以减小模型不确定性和环境扰动的影响;最后,通过输入状态稳定性定理和级联定理分析所提控制器的稳定性。[结果]实验结果表明,基于所提的自抗扰目标跟踪控制方法能使跟踪船有效地跟踪虚拟目标点。[结论]研究成果可为无人艇在环境扰动下的目标跟踪提供参考。     

基于AQPSO算法的圆碟形水下滑翔机路径规划

为解决复杂海洋环境影响下圆碟形水下滑翔机的路径规划问题,采用多黏性Lamb涡叠加方法模拟洋流环境模型。以最小能量消耗为优化目标,结合B-spline方法生成光滑的曲线路径,采用自适应性基于量子行为的粒子群优化算法对圆碟形水下滑翔机的路径选择进行优化求解。将该算法与粒子群优化算法和基于量子行为的粒子群优化算法相对比,仿真结果验证了各算法在求解航行路径问题方面的有效性。此外,基于能耗最优原则分析各算法的适用性。     

临时路径发生器学引的UUV跟踪控制(英文)

A path following control algorithm for an unmanned underwater vehicle(UUV) using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and orientation,the path following control in the horizontal plane may yield a poor performance.To deal with the negative effect induced by initial states,a temporary path generation was presented based on the relationship between the original reference path and the vehicle’s initial states.With different relative positions between the vehicle and reference path,including out of straight lines,as well as inside and outside a circle,the related temporary paths guiding the vehicle to the reference path were able to be generated in real time.The vehicle was guided to steer along the temporary path until it reached the tangent point at the reference path,where the controller was designed using the input-output feedback linearization method.Simulation results demonstrated that the proposed algorithm is effective under the three different situations mentioned above.     

自主水下航行器发展概述

自主水下航行器（AUVs）因其应用于海洋勘探而逐渐成为一个有趣的研究对象。波浪滑翔机是一种行驶于波浪表面的无人滑行器（SUV）,它借助海洋能来推动自己,这对于典型的AUVs所采用的电机供能以及昂贵的锚链系统浮标供
　　能来说,是一种技术上的重大跨越。该文讨论了最有效率的AUVs类型。第一部分为每一种类型的发展历程,第二部分为它们各自的技术特点。此外,波浪滑翔机作为应用于海洋部门的一种新型水下机器人,文中简要地给出它的过去,现在以及未来的发展概述。研究波浪滑翔机的意义在于证明它的效率以及实用性,进而取代诸多的AUVs来实现各种实际应用。而研究结果也表明波浪滑翔机确实可以应用于众多领域。对于海洋检测而言,相比于其他AUVs,波浪滑翔机提供了更廉价,更经济,更环保的作业模式,同时也不需要缆绳、船舶等海上作业服务。     

ISS-based robust adaptive fuzzy algorithm for maintaining a ship's track

This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability(ISS) theory used to verify the system is input-to-state stable. Combining the Nussbaum gain with backstepping techniques,a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system. It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded. Consequently,a ship's linear track-keeping control can be implemented. Simulation results using Dalian Maritime University's ocean-going training ship 'YULONG' are presented to validate the effectiveness of the proposed algorithm.     

ISS-based robust adaptive fuzzy algorithm for maintaining a ship＇s track

This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability （ISS） theory used to verify the system is input-to-state stable. Combining the Nussbaum gain with backstepping techniques, a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system. It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded. Consequently, a ship＇s linear track-keeping control can be implemented. Simulation results using Dalian Maritime University＇s ocean-going training ship ＇YULONG＇ are presented to validate the effectiveness of the proposed algorithm.     

海流对声纳目标定位精度影响分析

侧扫声纳在海洋工程等各方面都有广泛的应用,实际工作中经常采用拖曳方式作业,由于海洋环境的特殊性,风流对拖体的水中姿态有明显的影响,声纳测量和显示的是从拖曳载体到反射物体的距离,反射物体的实际位置依据拖体的水平姿态特性,所以其定位精度受海流等各方面影响较大。根据海洋调查侧扫声纳定位的基本原理和声纳工作的主要参考技术指标,分析对海流声纳探测目标定位精度影响,提出削弱海流影响的主要方法。     

智能水下机器人路径规划方法综述

路径规划方法是智能水下机器人技术研究的核心内容之一,是实现自主航行和作业的关键环节。本文将水下机器人的路径规划方法按智能程度分为传统和智能两大类。传统方法包括基于路线图构建的路径规划方法、基于单元分解的路径规划方法以及基于人工势场的路径规划方法,智能方法包括基于群智能的路径规划方法和基于机器学习的路径规划方法。针对水下机器人规划环境的特点,分别对这几类典型方法进行总结与评价,重点分析了智能方法的优缺点和关键问题,最后展望智能水下机器人路径规划的未来研究方向。