Navigation Technologies for Autonomous Underwater Vehicles

With recent advances in battery capacity and the development of hydrogen fuel cells, autonomous underwater vehicles (AUVs) are being used to undertake longer missions that were previously performed by manned or tethered vehicles. As a result, more advanced navigation systems are needed to maintain an accurate position over a larger operational area. The accuracy of the navigation system is critical to the quality of the data collected during survey missions and the recovery of the AUV. Many different methods for navigation in different underwater environments have been proposed in the literature. In this correspondence paper, the state of the art in navigation technologies for AUVs is investigated for theoretical and operational systems. Their suitability for use in different environments is compared and current limitations of these methods are identified. In addition, new approaches to address these current problems and areas for future research are suggested. Finally, it is concluded that only geophysically referenced methods will enable AUVs to navigate accurately over large areas and that advances in underwater feature recognition are required before these methods can be implemented in operational AUVs.     

Autosub: an autonomous unmanned submersible for ocean datacollection

Developing an understanding of the processes involved, and ultimately a predictive capability, has led to increasing demand for data of all types. Although Earth observation satellites can now provide remote means of sampling the ocean surface, many of the measurement techniques applied in the deep oceans are still heavily dependent on ships. An alternative which is being explored in many countries is the use of unmanned autonomous underwater vehicles to gather data. In this context the paper describes the progress made in the Autosub project of the Natural Environment Research Council     

Control architecture and operator interface for a free-flyingrobotic vehicle

Space and underwater vehicles with robotic arms can severely tax the capability of conventional control systems. Submersible vehicles used in neutral buoyancy simulation are subject to even greater demands since they must simulate the dynamics of spacecraft in orbit as well as function as a remotely-operated underwater vehicle. In this report, the onboard control architecture, human-machine interface, and vehicle/operator communications are described for one such vehicle in operation at the University of Maryland Neutral Buoyancy Research Facility (NBRF). The Ranger Neutral Buoyancy Vehicle (RNBV) exemplifies the high-dimensional, computationally intensive nature of the current fleet of autonomous underwater vehicles while its complement of four manipulators exceeds the capabilities of most remotely operated vehicles in service today. The sensor-based, embedded onboard control system is described, and its implementation using multiple control stations is discussed     

Underwater acoustic sensor networks: research challenges

Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area.In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined.     

有人/无人机协同作战

介绍了国外有人/无人机协同作战的发展概况,给出了有人/无人机之间协同作战的几种可能模式,并分析了有人机实现无人机地面控制站功能的可行性。相关结论对该领域技术人员开展有人/无人机协同作战研究具有重要意义。     

无人航空和有人航空混合运行的管制员负荷研究

域管制员的工作负荷的研究非常重要,提出一种无人航空和有人航空混合运行下的管制员指挥无人机的工作负荷量化方法,为研究融合空域的容量奠定基础。通过对比管制员对无人航空器和有人航空器发布指令的时间,制定了问卷,通过分析问卷结果得出混合运行方式下的管制员指挥无人机的工作负荷的量表。     

One-layer neural-network controller with preprocessed inputs for autonomous underwater vehicles

Navigating, guiding, and controlling autonomous underwater vehicles (AUVs) are challenging and difficult tasks compared to the autonomous surface-level operations. Controlling the motion of such vehicles require the estimation of unknown hydrodynamic forces and moments and disturbances acting on these vehicles in the underwater environment. In this paper, a one-layer neural-network (NN) controller with preprocessed input signals is designed to control the vehicle track along a desired trajectory, which is specified in terms of desired position and attitude. In the absence of unknown disturbances and modeling errors, it is shown that the tracking error system is asymptotically stable. In the presence of any bounded ocean currents or wave disturbances, the uniformly ultimately boundedness of the tracking error and NN weight estimates are given. The NN does not require an initial offline training phase and weight initialization is straightforward. Simulation results are shown by using a scaled version of the Naval Post-Graduate School's AUV. Results indicate the superior performance of the NN controller over conventional controllers. Providing offline NN training may improve the transient performance.     

Internet-based solutions in the development and operation of an unmanned robotic airship

Internet robotic systems have a different role in the use and development of aerial robots compared to that for ground robots. While for ground robotic vehicles, Internet is useful for remote operation or to make remote development, in aerial vehicles, in addition, the safety aspect must be considered very carefully. This paper addresses the requirements to the specific case of Internet aerial robots. It describes the conceptual and implementation aspects of an Internet-based software architecture for the AURORA unmanned autonomous airship project, showing its use in the different project phases.     

Vulnerable objects detection for autonomous driving: A review

Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.     

基于改进A*算法的水下航行器自主搜索航迹规划

以水下航行器在水下路径规划为研究重点,提出了基于改进型A*算法的水下无人航行器自主搜索航迹规划算法。一般航迹规划可由多种算法完成,而在这些算法中以A*的计算流程最为简单、算法易于实现,并在理论上可保证全局最优解的收敛性;且程序较为简短,可在一些低功耗、低主频的系统中应用。由于传统的A*算法不具备最小转弯半径等约束条件,因此,针对水下航行器高低速问题,对传统的A*算法进行改进,使得A*算法可实现高速与低速相结合的应用。     

Autopilots of the deep

Autonomous underwater vehicles (AUVs) are shedding their testbed origins and finding homes in marine science, ecology, offshore oil, and naval operations. The transition is being aided by improved controllers and energy sources. The author discusses the developments of AUV systems and describes some of the AUVs that are in operation. The various applications of AUVs are also discussed     

基于C-V2X的车路协同自动驾驶关键技术与应用

随着车联网技术的演进,自动驾驶在单车智能的基础上,又有了新的发展形态——车路协同自动驾驶。通过“人-车-路-云”深度融合形成的一体化复杂信息物理系统（cyber physical system,CPS）,可以与自动驾驶车辆实现协同感知、协同决策规划甚至协同控制,提升自动驾驶安全性,帮助克服各类复杂交通环境。首先介绍了车路协同的复杂信息物理系统的概念内涵和总体架构,并提出了车路协同自动驾驶的一系列典型应用场景、技术原理、C-V2X(cellular vehicle-to-everything)性能要求、车路协同系统功能与性能要求,可以为下一阶段智能网联汽车与智能交通的深度融合发展提供参考和解决思路。     

Overview of networking protocols for underwater wireless communications

Underwater wireless communications can enable many scientific, environmental, commercial, safety, and military applications. Wireless signal transmission is also crucial to remotely control instruments in ocean observatories and to enable coordination of swarms of autonomous underwater vehicles and robots, which will play the role of mobile nodes in future ocean observation networks by virtue of their flexibility and reconfigurability. To make underwater applications viable, efficient communication protocols among underwater devices, which are based on acoustic wireless technology for distances over one hundred meters, must be enabled because of the high attenuation and scattering that affect radio and optical waves, respectively. The unique characteristics of an underwater acoustic channel -- such as very limited and distance-dependent bandwidth, high propagation delays, and timevarying multipath and fading -- require new, efficient and reliable communication protocols to network multiple devices, either static or mobile, potentially over multiple hops. In this article, we provide an overview of recent medium access control, routing, transport, and crosslayer networking protocols.     

基于MOOS的AUV的数据采集和监控系统

随着海洋事业的发展,对海洋的探测和开发工作提出了更高要求。自主式水下机器人能很好的适应水下复杂的环境,通过自主导航定位,路径规划来完成相应的工作。为实现水下机器人稳定可靠的数据采集工作,采用以MOOS为平台的分布式设计方法,提高了数据采集系统的精度和效率,从而提高了AUV导航定位的准确性和可靠性。     

某型水下航行体长报文通信机制

当前应用于水下航行体领域的“北斗一代”卫星导航系统的通信协议主要为短报文来实现“点对点”、“点对多”的通信方式,文中在分析现状的基础上介绍了一种基于“北斗一代”卫星导航系统的长报文可靠通信机制。经验证,该机制可有效提高水下航行体与地面保障设备的通信效率。     

有人/无人机协同空地作战关键技术综述

有人/无人机协同作战是C4KISR体系下一种典型的作战方式,综合有人/无人机协同作战在各国的研究及进展情况,给出了有人/无人机协同作战指挥控制系统的结构,按照空域和时域两个方面分析了有人机、无人机两个平台的组成部分及协同控制功能,归纳出协同作战所需要解决的关键技术,并且给出了一个在典型作战任务想定下的作战情报指令及控制...     

国外海军水下特种作战研究

水下特种作战是各国海军热点研究的一种作战形式,已研制了多种特种作战装备,并逐步应用于军事斗争实际。可以预见,在未来海上作战中,水下特种作战将成为决定海上作战胜利的关键要素。对国外水下特种作战的作战样式、特点和装备进行了深入分析,研究其水下特种作战的组织指挥,这对发展水下特种作战有着重要的军事意义。     

激光雷达在无人车辆中的应用及关键技术分析

无人车辆是社会发展的重要趋势,利用激光雷达技术弥补视觉技术的不足,提高环境探测的准确度是未来无人车辆进行环境感知的重点发展方向。首先介绍了激光雷达技术在地面无人车辆领域的发展历程与最新进展,阐述了激光雷达的基本组成、原理和特点;然后对激光雷达数据处理过程中的关键技术进行了梳理与总结,对不同数据处理算法在不同应用条件下的性能效果进行分析;最后对激光雷达技术的研究方向和研究重点进行了展望。     

Fuel cells for the long haul, batteries for the spurts [electricvehicles]

Until only a few years ago, when environmentalists, automakers, and other concerned parties spoke about low-emissions vehicles, they were almost always referring to electric vehicles (EVs)-cars, trucks, and buses powered by batteries of one kind or another. Today, having so far failed in their quest for a battery that could make EVs practical, they are looking more and more to hybrid electric vehicles (HEVs), which automakers had hitherto rejected as merely an interim solution. But hybrids based on a combination of electric motors and internal combustion engines are attractive for two main reasons: they require no technology breakthroughs and no new infrastructure. They work with existing batteries since they do not rely on them for primary energy storage; rather, they can obtain fuel at any service station. An alternative to HEVs is fuel cell powered vehicles. The principles of this technology and the associated hydrogen storage issues are discussed. Other alternative fuels are briefly outlined     

Shallow water acoustic networks

Underwater acoustic networks are generally formed by acoustically connected ocean bottom sensor nodes, autonomous underwater vehicles (AUVs), and surface stations that serve as gateways and provide radio communication links to on-shore stations. The quality of service of such networks is limited by the low bandwidth of acoustic transmission channels, high latency resulting from the slow propagation of sound, and elevated noise levels in some environments. The long-term goal in the design of underwater acoustic networks is to provide for a self-configuring network of distributed nodes with network links that automatically adapt to the environment through selection of the optimum system parameters. This article considers several aspects in the design of shallow water acoustic networks that maximize throughput and reliability while minimizing power consumption