基于改进遗传算法的无人水下航行器路径规划

针对无人水下航行器（Autonomous Underwater Vehicle,AUV）运动约束多,传统遗传算法的路径寻优效率低、收敛速度慢等问题,提出了一种改进遗传算法的 AUV 路径规划方法。该算法选用栅格法构建环境,使用路径长度、平滑度和危险区域作为评价函数。改进遗传算法种群初始化过程,引入周围点栅格提高收敛速度,同时结合灾变思想避免群体陷入局部最优解。该算法根据 AUV 最大转角的约束条件,设计了 AUV 平滑过程和删除过程,避免了 AUV 航行出现急停急转。仿真及湖上试验结果表明：改进遗传算法相比传统遗传算法,路径长度减少 11.4%,收敛速度加快 20.0%,且收敛路径满足 AUV 航行约束要求。     

多自主式水下航行器协同控制的人工物理法研究

对水下多自主式水下航行器(Autonomous Underwater Vehicle,AUV)的编队协同控制和队形重构技术进行研究是水下AUV系统协同完成作业任务的重要研究内容。人工物理法通过设定虚拟的物理力完成机器人速度和方向信息的计算,并根据结果进行实时控制。由于分布式具有对水下传感信息和通信的依赖度较低的控制特点,因此可以很好的应用于可扩展的水下多AUV协同控制中。本文采用人工物理法完成多AUV的队形协同控制,研究了7个AUV采用人工物理法保持六边形队形,进行编队控制穿越障碍区间,AUV通过传感器探测外界环境,获得相关环境信息并确定障碍物的位置;AUV编队在穿越障碍区间时转换为一字队形,并采用边界检测法,沿边行走绕过障碍物;在穿越障碍区间后,AUV编队再次转换为六边形;依据判决条件完成多智能体控制的模态转换,进行队形重构。仿真结果证明本章所提方法的有效性,并具有较好的适时性与柔性。     

水下搜救中基于先验信息的AUV区域覆盖路径规划

搭载侧扫声呐(side-scan sonar,SSS)的自主水下航行器(autonomous underwater vehicle,AUV) 执行大规模海上搜救(search and rescue,SAR)任务时通常采用区域覆盖路径规划(coverage path planning, CPP)技术。由于任务失败的可能性很大,因此实现完全覆盖的同时,优先搜索目标可能存在的区域并提高侧扫声呐的数据质量十分必要。针对以上问题,提出了一种面向操作的全覆盖路径规划方法 SAS-A*,通过生成全覆盖路径,有效提高目标可能存在区域的覆盖速度和声呐数据的质量。该方法基于救援专家预测的目标位置和轨迹,采用二维高斯分布建立目标存在的概率模型,作为路径规划的先验信息。提出的 SAS-A*算法将下一个路径点选择策略转化为多目标决策问题,采用加权度量法来进行多目标优化,使 AUV 以更短路程、更少的转弯优先搜索目标可能出现的区域。仿真结果表明：SAR- A*路径规划方法适用于大规模搜救任务,可快速提高目标的搜索概率。     

基于AUV的声纳水下目标实时探测机制研究

针对传统船载声纳探测水下目标存在成像分辨率低、主观性强、耗时长、应用区域局限,以及自主式水下潜航器(autonomous underwater vehicle, AUV)受水声通信限制导致数据无法实时回传、处理及目标实时探测的问题,提出了一种基于AUV的声纳水下目标实时探测机制。首先对基于AUV搭载声纳设备实施水下目标探测的系统进行了阐述;然后提出了基于AUV的声纳水下目标实时探测实施流程和关键技术;最后通过海上试验,验证了该机制在一定程度上克服了水声通信限制,实现实时、高效、智能的水下目标探测,具有较强的实际指导意义。     

欠驱动AUV水平面动力定位控制方法研究

以欠驱动自主水下机器人(Autonomous Underwater Vehicle,AUV)为试验平台,提出了一种水平面动力定位控制方法.根据自研AUV平台的运动执行机构配置,针对其欠驱动特性设计运动控制器,控制纵向推力与转艏力矩,经过路径跟踪与区域镇定两个阶段,使航行器先沿预设路径快速接近目标点,再低速逐渐调整水平位...     

多无人艇协同目标分配算法研究

未来战争中很多作战任务需要由多艘无人艇相互配合才能完成,多无人艇协同目标分配是无人艇自主协同控制研究的关键技术之一。为了解决多参数、多约束条件下的目标分配问题,改进贝叶斯优化算法中网络构造方式及需要存储大量数据的不足,提出了基于决策图贝叶斯优化算法(Bayesian Optimization Algorithm with Decision Graphs,DBOA)的多无人艇协同目标分配方法。根据无人艇的消耗、目标价值的毁伤和执行任务预计耗费时间 3 个决策变量,并结合约束条件构建了多无人艇协同目标分配数学模型。仿真实例表明,DBOA 算法收敛速度快,能够达到全局最优解,基于 DBOA 的协同目标分配方法具有良好的时间效率和分配效果。     

大型复杂电极-海水负载陆上构建方法

为满足大型复杂扫雷电极-海水负载陆上模拟需要,分析了陆上重建方式,提出了多个小型电极对插入电解液并联模拟的方法,建立了电极对接触电阻计算模型,以及模拟负载优化的多目标决策模型。 为求解决策模型,将其简化为单目标决策模型,并利用库恩 ? 塔克条件法得到单目标模型解,利用理性点法求出了多目标决策模型解。 最后,对模拟优化方法进行了仿真验证,计算结果表明,在保证两者负载相同的情况下,陆上模拟负载总尺寸及模拟电极尺寸显著缩小,证明了模拟方法高效,优化方法正确。     

大型AUV及其水面侦察技术浅析

传统的自主水下无人航行器（AUV）主要执行包括军事活动在内的水下情报收集、环境监测和水下目标探测与处置等。近年来随着信息化技术和人工智能的发展,AUV行业受到各界尤其是各国军方越来越多的关注,得到了快速发展和广泛应用。作为一种无人侦察平台,AUV逐渐突破了常规尺度,向大型化和超大型化方向发展,可搭载的载荷类型和尺度有了明显的变化和提升。通过分析大型AUV作为侦察型装备的国内外发展现状,对利用大型AUV开展水面侦察的能力建设进行了分析,重点提出了大型AUV搭载水面侦察载荷需要解决的关键技术,为进一步提升和拓展AUV作战能力和作战领域提供支持。     

6000m级探测型AUV优化设计与阻力分析

使用ISIGHT集成EXCEL,ICEM,ANSYS FLUENT软件,搭建封闭耦合优化仿真平台。根据任务需求和布置需要得到设计变量、状态变量和目标函数,采用多岛遗传算法,优化求解得到局部最优AUV设计结果。借助SOLIDWORKS设计得到全附体模型,使用ANSYS CFX分别在0°,±2°,±4°,±8°,±16°攻角的条件下,计算其阻力值,经过经验公式对摩擦阻力的计算结果进行理论验证,证明了计算结果的可靠性。为6 000 m级探测型AUV的总体方案设计提供了线型参考和布局依据。     

AUV重力测量的运动加速度建模及平台优选

针对适合捷联式重力仪的AUV搭载平台的选型问题,基于国内AUV实际航行数据,分析了多推进器组合、推进器和浮力舱组合、推进器和鳍舵组合等3类AUV的定深航行运动特性;推导了AUV水下航行在3个坐标轴方向上对重力仪产生的运动加速度计算公式,得到运动加速度与AUV水下6个自由度运动要素的解析表达式;基于运动加速度分析,讨论了适用于水下移动重力测量的AUV平台和推进装置设计,进行了AUV搭载平台的优选,并给出了重力仪安装位置建议;选定的AUV实验平台实施移动重力测量验证试验重复线精度达到0.42mGal,验证了搭载平台优选的有效性。     

便携式AUV水下对接过程中的碰撞分析与罩式对接平台优化设计

以便携式自主水下机器人(AUV)和罩式导向对接平台的水下对接过程为研究对象,将碰撞力大小和对接时间作为评价指标,研究导向罩形状、对接管尺度以及AUV与对接管的偏心距对整个对接过程的影响。在三维建模的基础上,使用ADAMS软件进行动力学仿真分析,结果表明,减小导向罩开口角度、增大对接管直径、减小偏心距可以适当减小碰撞力和对接时间。通过对上述影响因素与评价指标建立函数关系,利用多目标优化设计的方法并结合实际情况对参数做出合理的分析和筛选,为水下机器人对接平台提供设计依据。     

A Variable Buoyancy Control System for a Large AUV

A large autonomous undersea vehicle (AUV), the Seahorse, has been designed, constructed, and tested by the Applied Research Laboratory at Pennsylvania State University (ARL/PSU, University Park, PA) for the U.S. Naval Oceanographic Office (NAVOCEANO, Stennis Space Center, MS). The vehicle is required to launch in shallow water (<10 m) and to hover without propulsion. Additionally, due to the very large size of the vehicle, low operating speeds and very long missions, small changes in vehicle trim resulting from battery replacement, sensor exchanges, and water temperature variations can result in significant drag-induced energy penalties over the duration of a mission. It is, therefore, important to continually maintain the AUV in fore-aft trim over the course of the mission. The vehicle is equipped with a two tank variable buoyancy system (VBS) to meet these requirements. The resulting control problem is one where the control variable, pump rate, is proportional to the third derivative of the sensed variable, depth; there are significant delays, and forces are nonlinear (including discontinuous) and highly uncertain. This paper describes the design of the VBS and the control software operating in two modes: depth control mode and trim control mode. In-water test data and simulation results are presented to illustrate the performance of the VBS controller. The benefits of the presented approach lie in the intuitiveness and simplicity of the design and the robustness as evidenced by the performance in both fresh and salt water. This paper provides practical insight into the operation of a VBS with an AUV and discusses actual operational experience. To our knowledge, no previous work considers the significance of an observed surface capture phenomenon to the design of a VBS control system, especially in very shallow water.     

Autonomous underwater vehicle homing/docking via electromagneticguidance

Central to the successful operation of an autonomous undersea vehicle (AUV) is the capability to return to a dock, such that consistent recovery of the AUV is practical. Vehicle orientation becomes increasingly important in the final stages of the docking, as large changes in orientation near the dock are impractical and often not possible. A number of homing technologies have been proposed and tested, with acoustic homing the most prevalent. If AUV orientation is required as well as bearing and distance to the dock, an acoustic homing system will require high update rates, and extensive signal conditioning. An Electromagnetic Homing (EM) system is one alternative that can provide accurate measurement of the AUV position and orientation to the dock during homing. This system offers inherent advantages in defining the AUV orientation, when compared to high frequency acoustic systems. The design and testing of an EM homing system are given, with particular attention to one can be adapted to a wide class of AUVs. A number of homing, docking, and latching trials were successfully performed with the design. Homing data include dead reckoning computation and acoustic tracking of the homing track, and video documentation of homing into the dock     

The NDRE-AUV flight control system

The flight control system of an autonomous underwater vehicle (AUV) developed at the Norwegian Defence Research Establishment (NDRE) is presented. A mathematical model of the vehicle is derived and discussed. The system is separated into lightly interacting subsystems, and three autopilots are designed for steering, diving, and speed control. The design of the separate controllers is based on PID techniques. Results from extensive sea testing show robust performance and stability for the autopilot     

Three-dimensional visualization of mission planning and control forthe NPS autonomous underwater vehicle

The Naval Postgraduate School (NPS) is constructing a small autonomous underwater vehicle (AUV) with an onboard mission control computer. The mission controller software for this vehicle is a knowledge-based artificial intelligence (AI) system requiring thorough analysis and testing before the AUV is operational. The manner in which rapid prototyping of this software has been demonstrated by developing a controller code on a LISP machine and using an Ethernet link with a graphics workstation to simulate the controller's environment is discussed. The development of a testing simulator using a knowledge engineering environment (KEE) expert system shell that examines AUV controller subsystems and vehicle models before integrating them with the full AUV for its test environment missions is discussed. This AUV simulator utilizes an interactive mission planning control console and is fully autonomous once initial parameters are selected     

The Morpheus ultramodular autonomous underwater vehicle

The Advanced Marine Systems Lab at Florida Atlantic University has developed a new ultramodular plastic mini autonomous underwater vehicle (AUV), called the Morpheus, for littoral military and coastal oceanographic sampling, survey, and mapping. The name Morpheus was chosen because the Greek god Morpheus could change shape or "morph." The higher degree of modularity of the Morpheus AUV allows it to "morph" or change its size and components for different applications. This vehicle is composed of modular injection-molded plastic pressure vessels and a cabling system that allow the modules to be rearranged without rewiring bulkheads. The plastic pressure vessels are inexpensive, inherently mass-producible, extremely corrosion-resistant, and have low magnetic signatures. The pressure vessels are small but are sized to fit most standard electronic board standards. The mini AUV can be anywhere from 4 to 10 ft in length, depending on its mission. The vehicle architecture is an adaptation of the Ocean Explorer AUV system and uses an ANSI 709.1 (LonTalk) distributed control network for connecting all sensors and actuator subsystems as smart nodes. The modularity in containers, control, and power makes this vehicle rapidly reconfigurable and easy to repair or upgrade. This paper will present details of the motivation, design, and construction of the new mini AUV. The Morpheus was deployed during the summer of 2000 in field exercises for very shallow and shallow water mine counter measures. Some results from these tests will be presented     

An interface system for autonomous undersea vehicles

Central to the successful operation of an autonomous undersea vehicle (AUV) is the capability to return from a mission, in that there is consistent recovery or docking of the AUV. In addition, some missions may require communication with and power transfer to the AUV after docking. This paper describes an inductive system that provides a nonintrusive power and communications interface between the dock and the AUV. The system makes up to 200 W of AC or DC power available to the AUV. The communications interface is 10BaseT Ethernet and is platform- and protocol-independent. The overall design of the system is given as well as results from wet laboratory and field tests     

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.     

Development of A Three-Dimensional Guidance System for Long-Range Maneuvering of A Miniature Autonomous Underwater Vehicle

The present paper introduces a three-dimensional guidance system developed for a miniature Autonomous Underwater Vehicle（AUV）. The guidance system determines the best trajectory for the vehicle based on target behavior and vehicle capabilities. The dynamic model of this novel AUV is derived based on its special characteristics such as the horizontal posture and the independent diving mechanism. To design the guidance strategy, the main idea is to select the desired depth, presumed proportional to the horizontal distance of the AUV and the target. By connecting the two with a straight line, this strategy helps the AUV move in a trajectory sufficiently close to this line. The adjacency of the trajectory to the line leads to reasonably short travelling distances and avoids unsafe areas. Autopilots are designed using sliding mode controller. Two different engagement geometries are considered to evaluate the strategy＇s performance： stationary target and moving target. The simulation results show that the strategy can provide sufficiently fast and smooth trajectories in both target situations.     

Transformed equations of motion for underwater vehicles

A method for dynamics investigation and coupling detection between velocities of autonomous underwater vehicles (AUVs) is presented in this paper. The method is based on transformation of equations of motion, which are usually used for an underwater vehicle, into equations with a diagonal mass matrix. The obtained equations contain quasi-velocities and allow one to give a further insight into the AUV dynamics especially for an underactuated system. Some advantages of the proposed approach are discussed, too. An analytical example for a 3-DOF AUV shows possible application of the transformed equations. Moreover, the given approach is validated via simulation on a 6-DOF vehicle.