An autonomous underwater vehicle and SUNSET to bridge underwater networks composed of multi-vendor modems

Nowadays, underwater acoustic communication is an interesting topic of research. This is especially true in the case of Autonomous Underwater Vehicles (AUVs): due to the limitations of the underwater environment, where WiFi and radio communications are limited, it is very important to rely on efficient and reliable tools for acoustic data exchange. Indeed, an underwater network of acoustic nodes can enhance the navigation and localization capabilities of one or more vehicles. However, cooperation and networking is not feasible in underwater networks composed of vehicles with different software architecture and multi-vendor modems due to the lack of communication standards. In this paper, the authors investigate the use of an AUV as a mobile bridging node within a network of fixed heterogeneous acoustic modems. In particular, MARTA AUV, developed and built by the Department of Industrial Engineering of the University of Florence, is employed to enable data transmission between modems of different manufacturers. The networking and the handling of multiple and multi-vendor modems are instead performed through the SUNSET Software Defined Communication Stack (SDCS) framework, developed by University of Rome La Sapienza jointly with WSENSE Srl. Different bridging tests have been performed in field to evaluate the feasibility of such approach, showing that AUVs can efficiently accomplish the role of gateway between the nodes of the network communicating through the SUNSET SDCS framework.     

Mobile Underwater Sensor Networks for Protection and Security: Field Experience at the UAN11 Experiment

The EU‐funded project UAN (Underwater Acoustic Network) was aimed at conceiving, developing, and testing at sea an innovative and operational concept for integrating underwater and above‐water sensors in a unique communication system to protect offshore and coastline critical infrastructures. This work gives details on the underwater part of the project. It introduces a set of original security features and gives details on the integration of autonomous underwater vehicles (AUVs) as mobile nodes of the network and as surveillance assets, acoustically controlled by the command and control center to respond against intrusions. Field results are given of the final UAN project sea trial, UAN11, held in May 2011 in Norway. During the experimental activities, a UAN composed of four fixed nodes, two AUVs, and one mobile node mounted on the supporting research vessel was operated continuously and integrated into a global protection system. In this article, the communication performance of the network is reported in terms of round‐trip time, packet loss, and average delivery ratio. The major results of the experiment can be thus summarized: the implemented network structure was successful in continuously operating over five days with nodes seamlessly entering and exiting the network; the performance of the network varied greatly with fluctuations in the acoustic channel; the addition of security features induced a minor degradation in network performance with respect to channel variation; the AUVs were successfully controlled from a remote station through acoustic signals routed by the network. © 2013 Wiley Periodicals, Inc.     

多AUV协同导航问题的研究现状与进展

自主水下航行器(Autonomous underwater vehicle, AUV)协同导航是未来50年解决水下中间层区域AUV导航定位的重要方法. 本文针对多AUV协同导航, 对该领域相关问题的研究进展进行了综述, 包括: 1)论述多AUV协同导航领域的研究现状, 包括协同导航问题界定、特点综述与讨论; 2)分析多AUV协同导航系统模型及相关算法的研究进展, 包括基于优化的、 基于参数估计的和基于贝叶斯估计的滤波算法; 3)对协同导航网络下的误差建模与补偿方法的研究进展进行了综述, 包括未知洋流的影响、水声通信延迟补偿等; 4)从影响协同导航定位精度的角度出发, 对AUV协同导航的可观测性与编队最优构型设计的研究进展进行了一系列的分析; 5)陈述目前多AUV协同导航中存在的关键问题, 并讨论其发展趋势.     

基于移动长基线的多AUV 协同导航

基于扩展卡尔曼滤波（EKF）理论研究了多AUV 协同导航定位的移动长基线算法．移动长基线多AUV 协同导航结构中,主AUV 内部装备高精度导航设备,从AUV 内部装备低精度导航设备,外部均装备水声装置测量 相对位置关系,利用移动长基线算法融合内部和外部传感器信息,实时获取从AUV 的位置信息．建立了协同导航 系统数学模型,设计了EKF 协同导航算法,在各种测试情况下通过仿真验证了所推导的分析结果,对EKF 和几何 解方程算法的导航效果进行了比较．研究结果表明,以主AUV 作为移动的长基线节点时,通过EKF 算法可以显著 提高群体的导航定位精度．     

Cooperative navigation of AUVs via acoustic communication networking: field experience with the Typhoon vehicles

A cooperative navigation procedure for a team of autonomous underwater vehicles (AUVs) is described and validated on experimental data. The procedure relies on acoustic communication networking among the AUVs and/or fixed acoustic nodes, and it is suitable as a low-cost solution for team navigation. Embedding the acoustic localization measurements in the communication scheme causes delays and sometimes loss of acoustic data, depending on acoustic propagation conditions. Despite this drawback, the results obtained show that on-board localization estimates have an error of the order of few meters, improving the overall navigation performance and leading the system towards long-term autonomy in terms of operating mission time, without the need of periodic resurfacings dedicated to reset the estimation error. The data were collected during the CommsNet ’13 experiment, led by the NATO Science and Technology Organization Center for Maritime Research and Experimentation (CMRE), and the Breaking The Surface ’14 workshop, organized by the University of Zagreb.     

Localization of AUVs using visual information of underwater structures and artificial landmarks

Autonomous underwater vehicles (AUVs) can perform flexible operations in complex underwater environments due to their autonomy. Localization is one of the key components of autonomous navigation. Since the inertial navigation system of an AUV suffers from drift, observing fixed objects in an inertial reference system can enhance the localization performance. In this paper, we propose a method of localizing AUVs by exploiting visual measurements of underwater structures and artificial landmarks. In a framework of particle filtering, a camera measurement model that emulates the camera’s observation of underwater structures is designed. The particle weight is then updated based on the extracted visual information of the underwater structures. Detected artificial landmarks are also used in the particle weight update. The proposed method is validated by experiments performed in a structured basin environment.     

基于复合AUVs的水声传感网拓扑优化机制

为提高网络拓扑的健壮性和自适应性, 基于拓扑重构思想提出基于复合自主式水下航行器的水声传感网拓扑智能优化机制来提高网络的连通性; 进一步, 在发现水声传感网拓扑结构形成的内在规律的基础上, 提出三角淡化关键节点网络拓扑优化方法, 该方法有助于提高网络抗毁再生能力. 最后通过仿真实验对比分析验证了所提出机制的有效性, 实验结果表明, 在牺牲约8.5\%覆盖度的条件下, 抗毁性能提高约50\%.     

Closed‐loop one‐way‐travel‐time navigation using low‐grade odometry for autonomous underwater vehicles

This paper extends the progress of single beacon one‐way‐travel‐time (OWTT) range measurements for constraining XY position for autonomous underwater vehicles (AUV). Traditional navigation algorithms have used OWTT measurements to constrain an inertial navigation system aided by a Doppler Velocity Log (DVL). These methodologies limit AUV applications to where DVL bottom‐lock is available as well as the necessity for expensive strap‐down sensors, such as the DVL. Thus, deep water, mid‐water column research has mostly been left untouched, and vehicles that need expensive strap‐down sensors restrict the possibility of using multiple AUVs to explore a certain area. This work presents a solution for accurate navigation and localization using a vehicle's odometry determined by its dynamic model velocity and constrained by OWTT range measurements from a topside source beacon as well as other AUVs operating in proximity. We present a comparison of two navigation algorithms: an Extended Kalman Filter (EKF) and a Particle Filter(PF). Both of these algorithms also incorporate a water velocity bias estimator that further enhances the navigation accuracy and localization. Closed‐loop online field results on local waters as well as a real‐time implementation of two days field trials operating in Monterey Bay, California during the Keck Institute for Space Studies oceanographic research project prove the accuracy of this methodology with a root mean square error on the order of tens of meters compared to GPS position over a distance traveled of multiple kilometers.     

Cooperative bathymetry-based localization using low-cost autonomous underwater vehicles

We present a cooperative bathymetry-based localization approach for a team of low-cost autonomous underwater vehicles (AUVs), each equipped only with a single-beam altimeter, a depth sensor and an acoustic modem. The localization of the individual AUV is achieved via fully decentralized particle filtering, with the local filter’s measurement model driven by the AUV’s altimeter measurements and ranging information obtained through inter-vehicle communication. We perform empirical analysis on the factors that affect the filter performance. Simulation studies using randomly generated trajectories as well as trajectories executed by the AUVs during field experiments successfully demonstrate the feasibility of the technique. The proposed cooperative localization technique has the potential to prolong AUV mission time, and thus open the door for long-term autonomy underwater.     

Field Testing of Moving Short‐baseline Navigation for Autonomous Underwater Vehicles using Synchronized Acoustic Messaging

This paper presents the results from field testing of a unique approach to the navigation of a fleet of autonomous underwater vehicles (AUVs) using only onboard sensors and information provided by a moving surface ship. The approach, considered moving short‐baseline (MSBL) navigation, uses two transponders mounted on a single surface ship that alternately broadcast acoustic messages containing one of the parameters of the kinematic state of the surface ship. The broadcasts are initiated according to a predefined schedule so that the one‐way travel time (OWTT) of the acoustic messages may be used to determine the range to the transponder. Each AUV in the fleet uses the surface ship state measurements and ranges provided by the acoustic messages in two extended Kalman filters (EKFs) for state estimation. The first EKF merges the intermittent surface ship state measurements with a kinematic model to estimate the state of the surface ship. This is necessary because the presented approach uses 13‐bit acoustic messages as opposed to the more commonly used 32‐byte messages, which allow the full state to be encoded in a single broadcast. The second EKF uses the current surface ship state estimate to properly interpret the acoustic ranges, combining them with a kinematic model to estimate the state of the AUV itself. Numerous MSBL navigation experiments were compared against a more traditional approach using a long‐baseline (LBL) array of transponders and OWTT acoustic ranging. The results of all tests were verified by independent LBL measures of position.     

Adaptive autonomous underwater vehicles for littoral surveillance

Autonomous underwater vehicles (AUVs) have gained more interest in recent years for military as well as civilian applications. One potential application of AUVs is for the purpose of undersea surveillance. As research into undersea surveillance using AUVs progresses, issues arise as to how an AUV acquires, acts on, and shares information about the undersea battle space. These issues naturally touch on aspects of vehicle autonomy and underwater communications, and need to be resolved through a spiral development process that includes at sea experimentation. This paper presents a recent AUV implementation for active anti-submarine warfare tested at sea in the summer of 2010. On-board signal processing capabilities and an adaptive behavior are discussed in both a simulation and experimental context. The implications for underwater surveillance using AUVs are discussed.     

Typhoon at CommsNet13: Experimental experience on AUV navigation and localization

This paper presents two acoustic-based techniques for Autonomous Underwater Vehicle (AUV) navigation within an underwater network of fixed sensors. The proposed algorithms exploit the positioning measurements provided by an Ultra-Short Base Line (USBL) transducer on-board the vehicle to aid the navigation task. In the considered framework the acoustic measurements are embedded in the communication network scheme, causing time-varying delays in ranging with the fixed nodes. The results presented are obtained with post-processing elaborations of the raw experimental data collected during the CommsNet13 campaign, organized and scientifically led by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE). The experiment involved several research institutions and included among its objectives the evaluation of on-board acoustic USBL systems for navigation and localization of AUVs. The ISME groups of the Universities of Florence and Pisa jointly participated to the experiment with one Typhoon class vehicle. This is a 300 m depth rated AUV with acoustic communication capabilities originally developed by the two groups for archaeological search in the framework of the THESAURUS project. The CommsNet13 Typhoon, equipped with an acoustic modem/USBL head, navigated within the fixed nodes acoustic network deployed by CMRE. This allows the comparison between inertial navigation, acoustic self-localization and ground truth represented by GPS signals (when the vehicle was at the surface).     

RT2: real-time ray-tracing for underwater range evaluation

The paper deals with the distributed acoustic localization of teams of autonomous underwater vehicles (AUVs) and proposes a novel algorithm, real-time ray-tracing (RT²), for evaluating the distance between any pair of AUVs in the team. The technique, based on a modified formulation of the non-linear sound-ray propagation laws, allows efficient handling of the distorted and reflected acoustic ray paths. The proposed algorithm can be easily implemented on-board of low-cost AUVs, requiring the presence, on each vehicle, of an acoustic modem and a pair of look-up tables, a-priori built on the basis of the assumed knowledge of the depth-dependent sound velocity profile. On such a basis, every AUV can compute its distance w.r.t. to any other neighbor team member, through time-of-flight measurements and the exchanges of depth information only.     

A practical and useful autonomous towed vehicle for port area inspection

This paper presents a novel underwater vehicle for port area inspection, which has various navigation modes (towed mode, autonomous mode and kite mode) to stand against fast and changeable sea currents. The property assures safe and reliable observation performance irrespective of current speed. Since in a port area sea currents are fast and complex, such a vehicle must be practical and useful for port area application. The unique point of the vehicle is the employment of an autonomous underwater vehicle (AUV) as a towed vehicle. In general, AUVs and towed vehicles are mutually contradictory. This paper describes the process of development to achieve the three different navigation modes. The system components and the results of computer simulations and towing tank tests to investigate the stability of the vehicle are presented. In addition, results of the first sea trial are also presented. These results show that the vehicle can navigate stably in the three different navigation modes.     

基于单领航者相对位置测量的多AUV协同导航系统定位性能分析

自主水下航行器 (Autonomous underwater vehicle, AUV) 的协同导航是解决水下导航定位问题的重要方法, 其中导航系统的定位误差增长特性是衡量其定位性能的关键指标. 本文针对单领航者相对位置测量的多 AUV 协同导航系统, 利用扩展卡尔曼滤波方法建立了导航系统的整体定位误差关于相对位置量测误差的传递方程. 在此基础上, 通过求解系统定位误差随时间演化的代数黎卡提方程, 得到了其在稳态情形下的方差上界估计. 理论分析表明, 单领航 AUV 协同导航系统的整体定位误差有界收敛且与初始化滤波方差无关, 具有良好的综合性能. 最后, 仿真实例验证了文中理论分析结果的正确性.     

Navigation of an AUV for investigation of underwater structures

There is a great demand for autonomous underwater vehicles (AUVs) to investigate artificial underwater structures such as piles and caissons in harbours, and risers and jackets of deep-sea oilfields. This paper proposes an autonomous investigation method of underwater structures using AUVs that is implemented by initially detecting the target objects, localizing them, then approaching them by taking video images while closely tracing their shape. A laser ranging system and a navigation method based on the relative position with respect to the target objects are introduced to realize this behaviour.     

A cooperative architecture for target localization using multiple AUVs

A recent concern in marine robotics is to consider the deployment of fleets of autonomous underwater vehicles (AUVs) and autonomous surface vehicles (ASVs). Multiple vehicles with heterogeneous capabilities have several advantages over a single vehicle system, and in particular the potential to accomplish tasks faster and better than a single vehicle. This paper addresses in this context the problem of underwater targets localization. A systematic and exhaustive coverage strategy is not efficient in terms of exploration time: it can be improved by making the AUVs share their information to cooperate, and optimize their motions according to the state of their knowledge on the target localization. We present techniques to build environment representations on the basis of which adaptive exploration strategies can be defined, and define an architecture that allows information sharing and cooperation between the AUVs. Simulations are carried out to evaluate the proposed architecture and the adaptive exploration strategies.     

Terrain‐aided navigation for long‐endurance and deep‐rated autonomous underwater vehicles

Terrain‐aided navigation (TAN) is a localisation method which uses bathymetric measurements for bounding the growth in inertial navigation error. The minimisation of navigation errors is of particular importance for long‐endurance autonomous underwater vehicles (AUVs). This type of AUV requires simple and effective on‐board navigation solutions to undertake long‐range missions, operating for months rather than hours or days, without reliance on external support systems. Consequently, a suitable navigation solution has to fulfil two main requirements: (a) bounding the navigation error, and (b) conforming to energy constraints and conserving on‐board power. This study proposes a low‐complexity particle filter‐based TAN algorithm for Autosub Long Range, a long‐endurance deep‐rated AUV. This is a light and tractable filter that can be implemented on‐board in real time. The potential of the algorithm is investigated by evaluating its performance using field data from three deep (up to 3,700 m) and long‐range (up to 195 km in 77 hr) missions performed in the Southern Ocean during April 2017. The results obtained using TAN are compared to on‐board estimates, computed via dead reckoning, and ultrashort baseline (USBL) measurements, treated as baseline locations, sporadically recorded by a support ship. Results obtained through postprocessing demonstrate that TAN has the potential to prolong underwater missions to a range of hundreds of kilometres without the need for intermittent surfacing to obtain global positioning system fixes. During each of the missions, the system performed 20 Monte Carlo runs. Throughout each run, the algorithm maintained convergence and bounded error, with high estimation repeatability achieved between all runs, despite the limited suite of localisation sensors.     

基于多AUV协作的稀疏水下传感网定位技术研究

如何在稀疏部署的水下传感器网络中实现传感器节点的高效定位是一个研究热点.提出了一种基于多个移动AUV协作的水下传感器网络内节点定位机制,利用AUV的精确自导航功能实现对网内未知位置节点的定位协助.提出的协作定位算法扩展了水下传感器网络的网内节点位置迭代估计方法,将信标节点和多AUV联合作为定位参考点,然后推导了基于最小二乘法的定位估计方程.仿真结果验证了该方法可以在定位节点比例、归一化定位误差和平均置信度等几个方面提高定位性能.     

Towards an autonomous underwater vehicles test range: At-sea experimentation of bearing-only tracking algorithms

Underwater navigation performance of Autonomous Underwater Vehicles (AUVs) strongly affects the quality of the collected data. Scientific literature extensively addresses the AUV tracking and self-localisation problems. However, no standard evaluation methods for vehicle navigation exist. Therefore, the authors’ visionary perspective is to develop and implement an Underwater Test Range (UTR) to certify the vehicle compliance with long-term underwater navigation. This paper describes a first step along this research path represented by an in field validation of such conceived measurement network. Experiments are soundly based on extensive simulation analysis presented in previous works. In particular, an underwater network composed of acoustic modems with Ultra Short BaseLine capabilities is deployed as measurement rig. This setup, through bearing-only measurements, allows the tracking of an Autonomous Surface Vehicle (ASV) equipped with Differential GPS as position ground truth. Results show how the proposed methodology performs in a real marine scenario with challenging conditions due to shallow waters and magnetically noisy environment.