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.     

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.     

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.     

分体式船体设计的水下测绘AUV回转运动的建模和分析（英文）

There is much need for autonomous underwater vehicles(AUVs) for inspection and mapping purposes.Most conventional AUVs use torpedo-shaped single-rigid hull,because of which their manoeuvrability is limited.Moreover,any increase in payload results in a larger hull size and the turning diameter,limiting its operation in constrained areas.As a solution to this problem,we develop M-Hull,a subsurface mapping AUV with a modular-split hull design that provides better manoeuvrability than a conventional torpedo-shaped vehicle.At the same time,it has more agility than an unconventional bio-inspired snake-like vehicle though their designs look similar.This approach makes it a hybrid solution between conventional torpedo-shaped AUVs and unconventional bio-inspired vehicles.We focus on improving the turning diameter during the mapping operation,and hence this paper concentrates on the dynamic aspects of the 2 D turning motion of the vehicle.It will provide the relationship between turning speed,thrust,and joint torque requirements for the multi-hull underwater vehicle.Different turning modes are compared to choose an optimum turning configuration,and the critical speed is calculated for the vehicle's safe operation.In the end,the modelling is verified using the experimental data.One can follow the method followed here for the 2 D motion analysis of similar underwater vehicles.     

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。     

基于OpenGL的深海开架式潜水器视景仿真设计

采用虚拟仿真技术,以正在研发的深海开架式潜水器的设计尺寸和数字海底理论为基础,采用基于面向对象数据模型和基于表面三角剖分的方法来构建水下目标的三维空间数据模型。以三角形的空间拓扑关系为基础,利用SolidWorks建模工具和VC++OpenGL图形开发库,实现了深海虚拟环境下的系统仿真。通过水下目标的建模实例,验证了仿真平台的正确性和可行性,该平台还可应用于深海综合调查研究、水下机器人操纵运动控制仿真等领域。     

Path optimization for marine vehicles in ocean currents using reinforcement learning

This study proposes a path planning algorithm for marine vehicles based on machine learning. The algorithm considers the dynamic characteristics of the vehicle and disturbance effects in ocean environments. The movements of marine vehicles are influenced by various physical disturbances in ocean environments, such as wind, waves, and currents. In the present study, the effects of ocean currents are the primary consideration. A kinematic model is used to incorporate the nonholonomic motion characteristics of a marine vehicle, and the reinforcement learning algorithm is used for path optimization to generate a feasible path that can be tracked by the vehicle. The proposed approach determines a near-optimal path that connects the start and goal points with a reasonable computational cost when the map and current field data are provided. To verify the optimality and validity of the proposed algorithm, a set of simulations were performed in simulated and actual ocean current conditions, and their results are presented.     

小型水下机器人在复杂水下地形中的目标搜寻应用

针对水下目标搜寻工作所遇到的现实困难及搜寻作业的特点,提出一种在局部水域范围内基于小型ROV的水下小目标搜寻方案,以提高水下复杂地形中的目标搜寻效率。工程应用实践证明该方案具有高效率、低风险及低成本等特点。     

一种基于多波束测深声呐图像的水下地势辅助导航方法（英文）

Underwater terrain-aided navigation is used to complement the traditional inertial navigation employed by autonomous underwater vehicles during lengthy missions. It can provide fixed estimations by matching real-time depth data with a digital terrain map. This study presents the concept of using image processing techniques in the underwater terrain matching process. A traditional gray-scale histogram of an image is enriched by incorporation with spatial information in pixels. Edge corner pixels are then defined and used to construct an edge corner histogram, which employs as a template to scan the digital terrain map and estimate the fixes of the vehicle by searching the correlation peak. Simulations are performed to investigate the robustness of the proposed method, particularly in relation to its sensitivity to background noise, the scale of real-time images, and the travel direction of the vehicle. At an image resolution of 1 m~2/pixel, the accuracy of localization is more than 10 meters.     

自主式水下机器人最优路径规划问题的研究

路径规划是水下机器人实现自主航行的重要环节。根据自主式水下机器人的动力学性质，路径规划的特点以及实现智能行为的要求，采用基于案例的遗传算法，实现了自主式水下机器人最优路径规划。给出该方案的基本框架和算法，在基于案例类比的学习方法中引入模糊多属性综合决策的方法建立决策算子进行案例的匹配，在遗传算法中实际知识的指导，适当地改进遗传算子，加快搜索速度。仿真结果证明该路径规划方法能够取得较好的规划结果，使自主式水下机器人具有了一定的自主导航，自主避障和自主作业的能力。     

Power efficient formation configuration for centralized leader–follower AUVs control

Autonomous underwater vehicles (AUVs) have rapidly developed in the last few decades due to their autonomous properties in the investigation of an underwater environment. The goal of this paper is to develop a power efficient formation control for the cooperative motion of AUVs with a support vessel as a leader. In this paper, a kinematic algorithm for the joint motion of an AUV with a support vessel was developed and that algorithm was expanded for the formation of AUVs. The AUV yaw, surge and sway control loops were designed for that purpose. The complexing navigation system structure for the AUV was also developed. Simulation results demonstrated efficiency of the proposed kinematic algorithm for the joint motion of AUVs. Also, influence of lateral ocean current was considered. After development of the centralized leader?Cfollower formation control for the group of AUVs with a support vessel as a leader, we optimized a formation configuration in terms of power efficiency. Drag forces caused by AUV motion in the water can significantly influence power consumption. We investigated the relationship between the AUV's formation configuration, underwater coverage efficiency, communication quality and power consumption. As a result of research, we proposed a power efficient formation configuration for typical underwater operations. As a result, the effect of the AUV formation configuration on the power consumption was investigated and a trade-off solution for the optimal AUV positions in formation with minimal energy consumption, high coverage efficiency and small communication power consumption was derived.     

BIM技术在航道水下地形空间监测中的应用

地形是区域环境的重要组成部分,三维地形分析为地表演化过程研究提供了全新的技术支撑。本文依托黑沙洲航道整治二期工程多期水下地形测量数据,基于BIM技术实现各个时期航道水下地形表面的三维可视化,并对其进行动态监测分析。研究表明,基于BIM技术实现航道水下地形空间监测,能够更加形象直观地展示区域地形演变、泥沙淤积等三维情况,对于航道的维护和整治具有重大意义。     

基于改进A*GBNN算法的AUV路径规划研究

针对现有的离散生物启发神经网络(Glasius bioinspired neural networks, GBNN)算法在未知环境下，存在的路径规划时间长、易陷入局部最优等问题，提出一种结合A*与GBNN模型的改进算法。在GBNN活性值栅格网络中，算法将各栅格的活性值作为A*的代价函数进行运算并使用跳点搜索规则优化，实现未知环境下的实时路径规划。仿真实验结果表明，该算法有效改善了自主水下航行器在未知环境下的寻路效率，可以满足自主水下航行器实时路径规划需求。     

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.     

基于自适应多分辨率曲面的多波束滤波方法研究

针对常规固定分辨率曲面滤波精度不足的问题,提出一种基于自适应多分辨率曲面的多波束滤波方法.在地形变化较大的陡坎和细小目标突起物等测量环境下,多分辨率曲面根据地形坡度变化,对有特征地形或地物的局部区域,自动增强多波束水深曲面的分辨率,从而得到更精确的水底表面模型.基于该表面模型可进行自动滤波,从而保留更加完整的水下地形特...     

排气角度对航行体表面等压气膜演化机制及流动特性影响研究

等压排气是一种可有效改善航行体绕流流场特性、抑制纵向偏转的流动控制技术。文章数值模拟了带等压排气的航行体水下垂直运动过程,给出了不同排气角度时的排气流量及速度、气膜长度等参数变化规律,分析了排气角度对等压气膜非定常发展过程及航行体绕流流场特性的影响,建立了排气孔附近及其下游流场、气膜尾部回射流场的拓扑结构,探讨了等压气膜的形态特征、演化规律及其降低航行体表面压力的机制,研究结果有助于深入理解等压排气技术改善航行体流体动力学特性的物理本质。     

水下机器人平面直航运动稳定性分析

应用古尔维茨(Hurwitz)判别法对水下机器人平面扰动运动微分方程的特征方程式根的实部符号进行判断,进而用一次近似法对水下机器人平面直航稳定性进行分析,试图为水下机器人在稳定性方面的设计以及对其稳定性进行评估提供可靠的依据。最后,实例说明该方法可行。     

水下拖曳系统水动力特性的计算流体力学分析

提出了一种新型的水下拖曳系统三维水动力数学模型。在该模型中拖曳缆绳的控制方程由Ablow andSchechter模型给出,Gertler and Hargen的水下运载体六自由度运动方程被用来描述拖曳体的水动力状态。通过对拖曳缆绳和拖曳体的控制方程在连接点处进行边界条件耦合,从而构成整个拖曳系统的水动力数学模型。在研究中,拖曳系统的水动力数学模型通过时间与空间的中心差分方程来逼近,每一时刻拖曳体所受的水动力通过求解Navier-Stokes方程得到。所提出的模型特别适用于拖曳体为非回转体、非流线型的主体,或必须考虑拖曳体各组成部分的水动力相互影响的情况。计算结果与相应的实验室样机试验结果的比较表明,所提出的模型可以有效地预报拖曳系统的水动力特性。利用所提出的水动力模型,对华南理工大学提出的自主稳定可控制水下拖曳体在实际海况下的数值模拟结果显示,所分析的拖曳体具有良好的运动与姿态稳定性,是一种值得开发研究的新型水下拖曳体。     

基于近场声全息技术的声对接装置

声对接技术以平面近场声全息理论算法为基础,利用声传播的近场特性,在一定的介质条件下来模拟声场远场传播特性的技术。在近场条件下,平面近场声全息技术能够针对不同的测试频率范围以及声场分布等要求,计算出相应的传输介质厚度以及对接阵阵元分布等参数,从而设计出声对接阵。通过仿真验证,采用平面近场声全息技术设计的声对接阵完全能够满足与水中兵器基阵实现声对接的要求。     

水下航行体水动力参数智能辨识方法研究

通过水下航行体的状态方程和试验观测方程,利用智能辨识技术对水下航行体的模拟运动数据进行了仿真辨识,求得了10个水动力参数.结果表明,智能算法简单有效,对目标函数没有可微性和连续性要求,避免了复杂的梯度矩阵计算,适合在复杂的非线性水动力系统辨识中应用.