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.     

Layered berthing method and experiment of unmanned surface vehicle based on multiple constraints analysis

Considering the dynamic changes of unmanned surface vehicle (USV) in berthing tasks, the planning and control modes are divided into two phases: the remote phase and the terminal phase. According to the main influencing factors of the two phases, an improved artificial potential field method is proposed to complete autonomous berthing trajectory planning based on the analysis of environment constraint, berth point constraint and USV’s dynamics constraint. Combining with the dynamic characteristics and control objectives at different phases of berthing and analyzing the fuzzy rule regulation strategy of USV’s heading and speed control, an improved adaptive fuzzy PID control method is proposed to solve the control problem of USV, which is influenced by weak maneuver, large disturbance, limited water area and strong shore effect. Finally, the comparative test of berthing simulation verifies the superiority of the proposed control method. The autonomous berthing field experiment is completed based on the "Dolphin-I" small USV. It verifies the validity and feasibility of the proposed autonomous berthing method.     

声学水面无人艇在浅水海底地貌调查中的应用

水面无人艇（USV,Unmanned Surface Vehicle）具有吃水浅、灵活机动、安全高效的特点和优势,日益成为浅水调查的重要手段。对于常规船只和考察人员不能到达的浅水环境的调查,无人艇具有填补甚至替代的价值和意义。C-Worker 4水面无人艇平台搭载了多波束测深、侧扫声呐、浅层剖面声学系统,运用脉冲同步控制和发射频率差异化配置的方法实现数据同步采集,旨在提高调查效率、优化调查方法和节约成本。基于2019年在海南岛澄迈湾1.2～22 m浅水环境的调查数据,处理和分析评估表明其采集数据可靠性高,能清晰识别海底沙波、波纹、礁石、埋藏河道、港池、航道、拖痕等微地貌单元。研究证实水面无人艇搭载多源声学系统同步测量可提供精细、立体、可靠的海底地貌基础资料,服务于海岸带地质调查、资源开发、工程建设、水运交通和国防安全等。     

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.     

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.     

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。     

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。     

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.     

一种新型双体无人监测船风力作用下的运动特性变化预报研究

小型双体无人监测船运行平稳,甲板尺寸大,吃水浅,在水环境监测、工程测量、巡逻跟踪、水产养殖等领域具有广阔的发展与应用前景。但该类船风阻大,水动力复杂,运动特性在风力作用下变化明显。本文对双体无人监测船的风作用力进行了分析,将风作用项引入其动力学模型。利用该模型,对其主要运动特性进行了仿真预报。仿真结果与现场实测数据具有良好的一致性。该研究结果可以为新型双体无人监测船运动控制算法在不同风作用环境下的适应性调整提供依据,从而提高其海上作业能力与控制精度。     

一种基于视觉的水下机器人动力定位方法

以7 000 m载人潜水器的工程需求为背景,以水下单目摄像机为视觉传感器,进行了水下机器人动力定位方法研究。该动力定位方法利用视觉系统测量得到水下机器人与被观察目标之间的三维位姿关系,通过路径规划、位置控制和姿态控制分解,逐步使机器人由初始位姿逼近期望位姿并最终定位于期望位姿,从而实现了机器人的4自由度动力定位。通过水池实验验证了提出的动力定位方法,并且机器人能够抵抗恒定水流干扰和人工位置扰动。同时,该动力定位方法还可以实现机器人对被观察目标的自动跟踪。     

基于无人机/无人艇的最优动态覆盖观测技术

针对无人机(unmanned aerial vehicle,UAV)/无人艇(unmanned surface vehicle,USV)对海面区域的最优动态覆盖观测问题,提出了一种以最大化观测收益为指标的航路优化方法。采用区域分解、子区域分配、航路规划相结合的分层求解思路:首先,根据信息密度等先验知识,采取基于高斯混合模型(Gaussian mixture model,GMM)的区域特征提取理论,从任务区域中提取出若干个子区域;然后,将子区域进行排序与分配,从而将复杂的协同优化问题转化为多个简单的单UAV或USV航路规划问题;最后,各UAV或USV在分配的子区域内采用并行滚动时域控制(receding horizon control,RHC)算法进行航路规划。仿真结果表明,本文提出的GMM-RHC方法具有更高的观测效率,可有效解决无人机/无人艇最优动态覆盖观测问题,具有重要的应用价值。     

基于无人机与卫星图像的大型绿藻孔石莼(Ulva pertusa)遥感估算研究

卫星影像是监测海面漂浮绿藻的重要数据源, 但是混合像元的存在使得绿藻提取存在一定的误差。想要实现近海区域底栖绿藻的精细监测, 需要解决绿藻亚像素覆盖度的问题。本文以厘米级分辨率无人机数据的绿藻提取结果为基准, 通过分析Landsat卫星影像绿藻光谱, 建立绿藻亚像素覆盖度与多种植被指数和多个特征波段反射率的反演模型。结果表明, 蓝、绿、红波段反射率与绿藻亚像素覆盖度呈现较好的线性关系, 随着绿藻亚像素覆盖度递增, 蓝、绿、红波段反射率的值均递减。将蓝、绿、红波段的三种绿藻亚像素覆盖模型进行验证, 发现绿波段反射率所建立的反演模型具有更高的准确性, 决定系数、均方根误差、平均相对误差分别为0.92%、0.07%、10.85%。本文所建立的模型可以估算大型绿藻亚像素覆盖度, 实现Landsat卫星影像对大型绿藻的精细监测。     

无人船系统应用于水库水样离岸采集——以棘洪滩水库为例

水库水质监测是水库水质评价的重要依据,通常需要现场采水样后带回实验室进行检测与分析。然而一些特殊情况下,例如库区无船、情况复杂等,只能获得沿岸水样,导致水质监测结果无法代表水库整体水质质量。本文针对水库的水样离岸采集,基于自研发的无人船系统,设计集成了采水泵,并利用无人船位点跟踪技术,实现了远距离定点遥控采水样功能。在青岛棘洪滩水库,利用该系统,设置了两个采样点(离岸50 m和离岸1300 m),并成功获取了水样。在实验室内,利用分光光度计、离子色谱仪、电感耦合等离子体质谱仪等设备,完成了所采集水样的水质分析。实验结果表明,无人船应用于水库水样离岸采集具有可行性、实用性。     

端口受控哈密顿方法的电力双推进无人船航向航速控制

以电力双推进无人船航速航向控制为主要研究问题,使用永磁同步电机作为无人船螺旋桨的驱动电机,采用基于端口受控哈密顿(PCH)方法,有效的降低了系统损耗,使无人船驱动系统输出功率得到了优化。仿真结果表明,系统能较快达到稳定状态,实现了无人船的速度控制要求,提升了无人船系统的续航能力。     

Parallel trajectory planning for shipborne Autonomous collision avoidance system

Collision at sea is always a significant issue affecting the safety of ship navigation. The shipborne autonomous collision avoidance system (SACAS) has the great advantage to minimize collision accidents in ship navigation. A parallel trajectory planning architecture is proposed in this paper for SACAS system. The fully-coupled deliberative planner based on the modified RRT algorithm is developed to search for optimal global trajectory in a low re-planning frequency. The fully-coupled reactive planner based on the modified DW algorithm is developed to generate the optimal local trajectory in a high re-planning frequency to counteract the unexpected behavior of dynamic obstacles in the vicinity of the vessel. The obstacle constraints, ship maneuvering constraints, COLREGs rules, trajectory optimality, and real-time requirements are satisfied simultaneously in both global and local planning to ensure the collision-free optimal navigation in compliance with COLREGs rules. The on-water tests of a trimaran model equipped with a model-scale SACAS system are presented to demonstrate the effectiveness and efficiency of the proposed algorithm. The good balance between the computational efficiency and trajectory optimality is achieved in parallel trajectory planning.     

基于无人机高光谱遥感的海岛岸线精准提取方法研究与应用

鉴于传统遥感技术手段对海岛岸线的提取在精度与效率上存在很大不足,通过无人机高光谱遥感技术,结合岸线实地踏勘活动,提出一种海岛岸线类型识别与位置提取方法,并选取实际海岛进行了实验验证,成功获取了不同类型岸线的准确位置,所得成果与传统遥感手段相比,提高了系统性与准确性,为下一步海岛的生态评估工作提供了数据支撑。     

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。     

基于无人机紫外与SAR的溢油遥感监测方法研究

溢油污染不仅会造成巨大的经济损失,而且给生态环境带来难以修复的破坏。准确、高效地监测海面溢油仍是当前亟需解决的问题。紫外传感器对油膜非常敏感,可快速发现,但存在误判;而SAR(SyntheticApertureRadar)溢油探测的精度较高,两者相结合可准确探测溢油。无人机平台可低成本地实现溢油快速应急响应,无人机载SAR和紫外传感器的载荷重量小,可同时集成于无人机上开展联合溢油探测,以满足业务化监测需求,此方面的研究尚未见有相关报道。本文拟研究溢油不同种类、厚度、在不同海洋环境条件下的紫外图像特征和SAR纹理特征、形状特征、散射特征,构建溢油特征数据库,并建立一种基于特征组合的溢油SAR与紫外联合探测方法;在此基础上研究对无人机数据获取模式和控制单元等的改造方案,进而实现溢油SAR和紫外图像的高效获取。     

Hydrodynamic shape optimization by high fidelity CFD solver and Gaussian process based response surface method

A computational framework for hydrodynamic shape optimization of complex ship hull form is proposed and applied to improve the calm water performance of the KRISO Container Ship (KCS). The framework relies on three key features: a novel shape morphing method based on a combination of subdivision surfaces and free form deformations, a robust three dimensional viscous computational fluid dynamic solver based on the openFOAM open-source libraries and a Gaussian process-response surface method (GP-RSM) based on ordinary Kriging model which has been created to speed-up the evaluation of the quantity of interest (QoI) of the design process.The accuracy of the hydrodynamic solver is proven by comparing the obtained results against available experimental measurements. A preliminary sensitivity analysis on the mesh size has been carried out aiming at reducing the computational burden required by the CFD predictions. Three GP-RSMs have been trained relying on increasing number of hull designs. Each surrogate model has been cross-validated by both leave-one-out and k-fold techniques. The behaviours of these multi-dimensional surfaces have been analyzed in details by sampling the investigated design space with 10⁷ points according to a Full-Factorial algorithm, highlighting the regions of maximum deviation with respect to the resistance of the reference hull. The three optimum designs provided by the corresponding GP-RSM models have been verified by using high-fidelity CFD simulations with a refined mesh configuration. Calm water resistance, wave patterns and pressure distributions over the selected hull surfaces have been discussed in the light of the generated shape variations.     

基于无人机高光谱的外来入侵种互花米草遥感监测方法研究——以黄河三角洲为研究区

互花米草(Spartina alterniflora)入侵性非常强,已被正式纳入我国第一批外来入侵物种名单。互花米草的疯狂蔓延已影响到当地土著物种的生长和空间分布,因此有关管理部门迫切需要互花米草的空间分布和扩散动态数据,但目前还没有一个有效的监测手段。针对这一需求,本文作者提出了基于无人机高光谱的外来入侵种互花米草遥感监测研究方案,拟以黄河三角洲为研究区,利用无人机高光谱遥感新型技术,分析不同情形下(不同生长状况、不同观测条件、不同环境条件等)互花米草的光谱特征,建立鲁棒的互花米草遥感检测模型,研究互花米草无人机高光谱图像高效获取方法,以实现互花米草的高效、准确监测,为亟需的外来入侵种互花米草业务化监测提供有效的技术手段。