一种基于超短基线定位的便携式AUV回坞导航方法

自主水下机器人(AUV)对接技术是目前水下机器人的研究热点,精确可靠的AUV的回坞导航是实现对接的关键技术。对于追求轻便的便携式AUV的对接系统,考虑到便携式AUV的搭载能力有限又需要足够的定位精度用于对接,提出了一种基于超短基线(USBL)定位的回坞导航方法,该方法让AUV只需装载电子罗盘和水声应答器就能完成精确的回坞定位。根据导航方法的特点,设计了一种改进的扩展卡尔曼滤波算法,其优点是能在处理滞后的USBL数据的同时动态估算海流、更新状态方程以消除海流造成的定位误差。通过湖试和大量仿真实验,验证了定位算法在海流影响下的定位性能。     

用于AUV定位的等效声速剖面改进算法研究

以自主式水下机器人为载体,搭载多种测量设备的深海工程作业的方式,目前已经得到了广泛的应用。而基于AUV完成各类水下任务的前提是能否精确的进行定位,传统的声学定位方法因过于依赖声速剖面而导致定位精度不高且造成实际操作过程复杂化,在各种声线改进的方法中,等效声速剖面法的计算过程较为简单,且对实际声速剖面的依赖程度较低,然而最大的问题是相对面积误差的求解过于复杂。结合AUV自身特点,提出了超短基线与等效声速剖面法相结合的水下AUV定位方法,并改进了等效声速剖面法。实验结果表明,改进后的方法计算精度得到提高且相对面积误差的求解更加简单,另外也改进了原始方法误差随水深及掠射角变化而增加的问题,具有良好的工程应用价值。     

海底地形匹配高效质点滤波导航方法

海底地形匹配导航技术可实现自主水下机器人(Autonomous Underwater Vehicle,AUV)长时间的水下精确导航。质点滤波器(Point-Mass Filter,PMF)是实现 AUV 精确海底地形匹配导航的重要方法,但质点权重计算过程中需要寻找空间分布不规则的实测地形数据点与网格化先验地形图数据点间空间对应关系,造成大量计算消耗,严重影响了地形匹配导航算法实时性能。提出一种海底地形匹配高效质点滤波导航方法,通过构建伪输入高斯过程(Sparse Pseudo-input Gaussian Processes,SPGPs)模型,实现实测海底地形数据高效、精确网格化插值过程,并根据 SPGPs 方法提供的插值置信度实现网格化概率地图构建;搭建质点滤波器算法框架,提出适用于概率地图的质点权重计算过程,通过考虑网格化地图不同节点插值置信程度差别,提高地形匹配导航精度。于青岛中沙礁展开海上数据获取试验,并利用海试数据完成算法回放式仿真验证。试验结果证明,所提出网格化插值方法可实现高精度、高效地形深度插值过程,所提出海底地形匹配高效质点滤波导航方法可为 AUV 在线提供精确导航结果,且实时导航圆概率误差小于 3 m。     

基于DIDSON的未知海域覆盖规划算法

针对自主水下机器人的路径规划问题,提出一种基于双频识别侧扫声呐(DIDSON)的全局路径规划算法。根据双频识别侧扫声呐的物理特性对AUV进行数学建模,根据声呐的工作频率不同,将AUV分为高频、低频两种工作模式。高频模式下成像精度高,低频模式下成像范围大。文中提出了一种D2-CPP算法,根据声呐返回的识别结果,算法会自主切换AUV的工作模式,并动态规划出对应的路径点,直到覆盖所有区域。通过与割草机算法的仿真对比,证明了算法的有效性,近海实验证明了算法的可靠性。     

基于改进量子粒子群算法的AUV路径规划研究

针对海洋环境下自主水下机器人（AUV）的路径规划问题,提出了一种基于框架四叉树的改进量子粒子群算法（QPSO）,首先使用框架四叉树的方法对障碍物建模,该方法提高了建模的精度且对后续算法的效率也有极大的改进,之后设计改进的量子粒子群算法,并且结合水下环境的特殊性设计适应度函数,综合考虑航线路径长度、偏转角度以及海流影响,使得算法可以在水下环境中寻得能耗最短的解路径。最后通过仿真试验验证,相比于传统的栅格法和粒子群算法,改进量子粒子群算法的运算时间更短,收敛速度更快,其独特的适应度函数可以使AUV能更好适应水下多变的环境,且能利用海流设计能耗更小的路径,具有很大的实用价值。     

AUV水下对接装置控制系统设计

自主式水下机器人(Autonomous Underwater Vehicle,简称AUV)在航行使命结束后需要回收至甲板或陆地进行补给和维护。为避免重复布放回收所带来的不便,根据锥形导向式回收原理,针对水下对接装置及其控制系统进行了设计。水下对接装置控制系统由水面控制终端,水下控制系统和水下外部设备等部分组成,使用超短基线引导AUV进入指定区域,在对接过程中依靠行程开关和无线电反馈的信息判断AUV的相对位置及状态,并通过驱动相应的液压机构对AUV姿态进行校正和固定,进而完成对接过程。水下对接装置在千岛湖进行了试验,在吊装水下7 m的情况下实现了AUV的水下对接,并利用湿插拔电连接器完成了对AUV的有线充电和数据上传。试验验证了对接方案的可行性以及控制系统的稳定性,为将来AUV能够进行长时间、不间断航行提供了可能。     

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。     

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。     

水下导航定位技术在大洋科考调查中的应用

水下声学定位、惯性导航定位、多普勒声纳以及组合导航定位是目前我国大洋科考调查工作中的几种主要水下导航定位技术。通过分析常规调查装备、ROV、AUV和载人潜水器等4类主要水下科考设备的导航定位系统实测数据,给出不同水下导航定位模式的现场作业精度,为我国大洋科考调查工作中水下导航定位技术的选择与应用等工作提供参考。     

20kg级便携式自主水下机器人(AUV)设计与实现

便携式AUV具有结构紧凑、机动性好、制造和使用成本低等优点,本文设计AUV的底层控制系统和自主导航系统,并进行仿真验证和人工湖试验,结果证明底层控制系统具有很好的鲁棒性,基于AHRS、数字罗盘和GPS的惯性导航算法能够通过浅水节点潜航方式实现AUV自主导航。     

Visually Augmented Navigation for Autonomous Underwater Vehicles

As autonomous underwater vehicles (AUVs) are becoming routinely used in an exploratory context for ocean science, the goal of visually augmented navigation (VAN) is to improve the near-seafloor navigation precision of such vehicles without imposing the burden of having to deploy additional infrastructure. This is in contrast to traditional acoustic long baseline navigation techniques, which require the deployment, calibration, and eventual recovery of a transponder network. To achieve this goal, VAN is formulated within a vision-based simultaneous localization and mapping (SLAM) framework that exploits the systems-level complementary aspects of a camera and strap-down sensor suite. The result is an environmentally based navigation technique robust to the peculiarities of low-overlap underwater imagery. The method employs a view-based representation where camera-derived relative-pose measurements provide spatial constraints, which enforce trajectory consistency and also serve as a mechanism for loop closure, allowing for error growth to be independent of time for revisited imagery. This article outlines the multisensor VAN framework and demonstrates it to have compelling advantages over a purely vision-only approach by: 1) improving the robustness of low-overlap underwater image registration; 2) setting the free gauge scale; and 3) allowing for a disconnected camera-constraint topology.      

基于GPS的水下导航算法误差仿真研究

首先介绍了水下导航算法,采用GPS和水下参量测算相结合的方案,即当运行器在水下运行时,利用电子罗盘测量运行器的相对航向,水流传感器测算运行器的相对速度大小,利用学习阶段计算出海水流速,在水下运行器潜行时进行船位推算导航,用GPS精准的定位信号进行导航误差的校正。此算法精度的高低很大程度上取决于用来进行水下参量测算的传感器和用来方位校准的GPS。文中从各个传感器的误差着手,通过模拟仿真详细分析了电子罗盘、水流传感器和GPS的误差对导航精度的影响,对工程应用具有实际的指导意义。     

接收机自主完好性监测算法及其性能分析

完好性是卫星导航系统的重要性能参数,接收机自主完好性监测作为用户端的完好性监测方法具有低成本、实施方便的优势。基于统计理论,给出RAIM算法统计检测量的设计方法,推导了阈值的确定方法及RAIM可用性判定方法。对一天中2880个采样时刻的RAIM性能进行仿真分析,结果表明,RAIM算法对于固定伪距误差的故障和慢变故障有良好的监测效果,排除故障星之后的定位误差可以保持在正常的水平。     

In Situ Alignment Calibration of Attitude and Doppler Sensors for Precision Underwater Vehicle Navigation: Theory and Experiment

This paper reports the development and experimental evaluation of two in situ least squares techniques for estimating the alignment matrix of Doppler sonars commonly used for precision navigation of oceanographic submersibles. Most previously reported methods addressed the problem of single degree-of-freedom heading alignment using bottom-lock Doppler sonar data and global positioning system (GPS) navigation data. This paper reports and evaluates two techniques for three degree-of-freedom calibration of attitude and Doppler sonar sensors using sensor data available to vehicles at full ocean depth. The first technique provides a general linear least squares estimate of the alignment matrix. The second technique results in a least squares alignment matrix estimate constrained to the group of rotation matrices. The performance of these estimates is evaluated with a laboratory remotely operated vehicle (ROV) and a field-deployed autonomous underwater vehicle (AUV). Experimental results are reported which demonstrate that Doppler navigation employing the reported alignment calibration techniques significantly improves navigation precision. The experiments show that the latter technique provides calibration estimates that improve Doppler navigation precision not only on the calibration data set itself, but also provide improved precision over a wide variety of vehicle trajectories other than the calibration data set.     

Simulation of an Inertial Acoustic Navigation System With Range Aiding for an Autonomous Underwater Vehicle

This paper presents an integrated navigation system for underwater vehicles to improve the performance of a conventional inertial acoustic navigation system by introducing range measurement. The integrated navigation system is based on a strapdown inertial navigation system (SDINS) accompanying range sensor, Doppler velocity log (DVL), magnetic compass, and depth sensor. Two measurement models of the range sensor are derived and augmented to the inertial acoustic navigation system, respectively. A multirate extended Kalman filter (EKF) is adopted to propagate the error covariance with the inertial sensors, where the filter updates the measurement errors and the error covariance and corrects the system states when the external measurements are available. This paper demonstrates the improvement on the robustness and convergence of the integrated navigation system with range aiding (RA). This paper used experimental data obtained from a rotating arm test with a fish model to simulate the navigational performance. Strong points of the navigation system are the elimination of initial position errors and the robustness on the dropout of acoustic signals. The convergence speed and conditions of the initial error removal are examined with Monte Carlo simulation. In addition, numerical simulations are conducted with the six-degrees-of-freedom (6-DOF) equations of motion of an autonomous underwater vehicle (AUV) in a boustrophedon survey mode to illustrate the effectiveness of the integrated navigation system.     

SINS/DGPS矢量重力测量系统滤波技术研究

以单通道捷联惯性导航系统的速度误差和姿态误差方程为状态方程,以陀螺仪误差和垂线偏差为过程噪声,以DGPS的速度与捷联惯导的速度之差为观测量,建立Kalman滤波模型,经滤波得到高精度实时导航信息。从导航信息中提取水平重力信息,进而得到垂线偏差。对高精度惯性元件构建的惯导系统进行数值仿真,仿真结果表明,组合系统可以有效提高实时导航和姿态精度,经50s平均后,可以得到精度为2″的垂线偏差。     

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.     

Hypothesis grids: improving long baseline navigation for autonomous underwater vehicles

Navigation continues to fundamentally limit our ability to understand the underwater world. Long baseline navigation uses range measurements to localize a remote vehicle using acoustic time-of-flight estimates. For autonomous surveys requiring high precision navigation, current solutions do not satisfy the performance or robustness requirements. Hypothesis grids represent the survey environment capturing the spatial dependence of acoustic range measurement, providing a framework for improving navigation precision and increasing the robustness with respect to non-Gaussian range observations. Prior association probabilities quantify the measurement quality as a belief that subsequent observations will correspond to the direct-path, a multipath, or an outlier as a function of the estimated location. Such a characterization is directly applicable to Bayesian navigation techniques. The algorithm for creating the representation has three main components: Mixed-density sensor model using Gaussian and uniform probability distributions, measurement classification and multipath model identification using expectation-maximization (EM), and grid-based spatial representation. We illustrate the creation of a set of hypothesis grids, the feasibility of the approach, and the utility of the representation using survey data from the autonomous benthic explorer (ABE).