Intelligent UUVs: Some issues on ROV dynamic positioning

Intelligent unmanned underwater vehicles (UUVs) fall under two main group categories: the remotely operated vehicles (ROVs), which are characterized by remote operation and presence of a tether cable; and the autonomous underwater vehicles (AUVs), which are characterized by their autonomous behavior and absence of a tether cable. One fundamental issue of the UUV design is the dynamic position control system. This system plays a crucial role together with the sensor architecture in the degree of system autonomy that can be achieved. This paper is concerned with a few issues when dynamically positioning remotely operated underwater vehicles (ROVs). By restricting the operating regime of ROVs to slow velocity requirements the paper investigates the implementation of a few decentralized control strategies and compare their performance measures, which are assessed by simulating a nonlinear ROV system model for each control strategy. Issues concerning input tracking, disturbance rejection, and plant variations are discussed. The evaluations consider the use of linear PID feedback and feedforward variants, and a robust nonlinear control strategies applied to a full order, fully coupled, and nonlinear vehicle model. These evaluations consider a vehicle undertaking standard mission activities where the tether cable dynamics, with load estimates obtained from a lumped mass cable model, and the vehicle actuator system are present. The paper shows that much of the performance deterioration may be attributed mainly due to cable inertia. The authors also verify that the nonlinear robust control strategy does not necessarily allow for better performance over the linear feedback control strategies implemented when vehicle motions are confined to slow velocity profiles. These and other partial results will aid the design of the control system for an underwater vehicle currently under construction     

基于ARM下VxWorks的嵌入式车载图形系统设计

为了实现嵌入式车载系统设计,采用软硬件协同设计技术路线。研究了基于ARM9的S3C2410处理器为核心的嵌入式车载软件的运行机制,包括系统硬件初始化,VxWorks操作系统内核的配置与装载,Vxworks下的LCD显示技术和触摸屏控制技术的应用实现车载仪表信息的显示与交换功能,并通过VxWorks多任务的进行控制。通过实验测试,系统随时进行车载娱乐、自主导航、信息查询等功能。方案实时性好,操作方便。     

多临近空间拦截器编队拦截自主协同制导控制技术研究

分析了目前高超声速飞行器的发展现状和发展趋势,指出高超武器已经给现有的防空反导武器系统带来极大威胁和挑战。针对高超声速飞行器的拦截问题,分析梳理了相关的技术难点。为保证拦截成功,采用多枚拦截器编队拦截高超声速目标是目前高效可行的技术途径,而多临近空间拦截器自主协同制导控制技术则是关键技术。针对多临近空间拦截器编队攻击自主协同制导控制技术,分别从建模、决策规划、感知、制导、控制以及评估6个方面提出需要解决的关键技术问题。最后对多临近空间拦截器编队拦截自主协同制导控制技术进行了总结与展望。     

地面无人平台视觉导航定位技术研究

地面无人平台实现自动驾驶等功能的核心难题在于如何感知其所处环境并获得自身在环境中的实时状态。机器视觉作为地面无人平台在复杂环境下实现自主导航及定位的重要手段,近年来得到了快速发展。系统性地分析了视觉定位与地图构建系统的基本架构,并对该架构包含的图像信息预处理、视觉里程计、回环检测、全局优化和地图构建模块分别进行了详细介绍。针对各模块所涉及的关键技术,总结了近些年来国内外主流的研究成果,对比分析了各个关键技术中主流方法的性能,并展望了地面无人平台视觉导航定位技术的发展方向。     

无人机自主防撞关键技术与应用分析

无人机与有人机在多机种和不同合作程度下共享空域飞行是未来的发展趋势,防撞问题成为制约无人机飞出隔离空域的关键挑战。结合现有飞机防撞体系,从无人机防撞特殊性出发分析无人机自主防撞需求,提出无人机自主防撞系统的框架,归纳分析两大主要关键技术——感知探测技术和防撞算法,以及二者的不同应用范围和主要问题,在此基础上提出无人机自主防撞管理体系架构,总结探讨无人机自主防撞关键技术的发展趋势。     

Navigation system design using time-varying complementary filters

A new methodology for the design of navigation systems for autonomous vehicles is introduced. Using simple kinematic relationships, the problem of estimating the velocity and position of an autonomous vehicle is solved by resorting to special bilinear time-varying filters. These are the natural generalization of linear time-invariant complementary filters that are commonly used to properly merge sensor information available at low frequency with that available in the complementary region. Complementary filters lend themselves to frequency domain interpretations that provide valuable insight into the filtering design process. This work extends these properties to the time-varying setting by resorting to the theory of linear differential inclusions and by converting the problem of weighted filter performance analysis into that of determining the feasibility of a related set of linear matrix inequalities (LMIs). Using this set-up, the stability of the resulting filters as well as their "frequency-like" performance can be assessed using efficient numerical analysis tools that borrow from convex optimization techniques. The mathematical background that is required for complementary time-varying filter analysis and design is introduced. Its application to the design of a navigation system that estimates position and velocity of an autonomous vehicle by complementing position information available from GPS with the velocity information provided by a Doppler sonar system is described.     

水下重力匹配定位算法综述

随着重力测量和水下导航技术的发展,惯性/重力匹配导航技术因其精度高、自主性强和航时长等优点,已成为水下自主导航的重要研究方向。惯性/重力匹配导航系统主要由惯性导航系统、重力实时测量、海洋重力场背景图和重力匹配定位算法构成。重力匹配定位算法通过将实时测量的重力异常值与构建的重力场背景图进行匹配,得到水下运载体当前时刻的位置信息,是惯性/重力匹配导航技术的核心。本文详细介绍了重力匹配算法的技术发展现状,重点分析了具有代表性的ICCP算法、SITAN算法、矢量匹配算法及其衍生算法,并对惯性/重力匹配水下自主导航技术的未来发展进行了展望。     

Autonomous airborne navigation in unknown terrain environments

We address the issue of autonomous navigation, that is, the ability for a navigation system to provide information about the states of a vehicle without the need for a priori infrastructure such as GPS, beacons, or a map. The algorithm is known as simultaneous localisation and mapping (SLAM) and it is a terrain aided navigation system (TANS) which has the capability for online map building, and simultaneously utilising the generated map to bound the errors in the navigation solution. Since the algorithm does not require any a priori terrain information or initial knowledge of the vehicle location, it presents a powerful navigation augmentation system or more importantly, it can be implemented as an independent navigation system. Results are first provided using computer simulation which analyses the effect of the spatial density of landmarks as well as the quality of observation and inertial navigation data, and then finally the real time implementation of the algorithm on an unmanned aerial vehicle (UAV).     

合作环境下基于惯性/里程计/Lidar融合的UGV导航方法

近年来，无人车在巡检、探测等方面的应用愈发广泛,且应用环境愈发复杂。在这些应用中，无人车必须对自身的位姿进行准确估计，以确保作业安全、高效完成。其中，可在复杂环境下适用的自主导航能力是核心关键技术。提出了一种基于惯性/里程计/激光雷达的地面无人车导航方法，区别于传统的激光雷达SLAM方法，该方法根据已知的几何结构特征进行定位，避免了因有效点数量稀少而导致的匹配误差。同时对惯性/里程计/激光雷达的融合算法进行了研究，提高了自主导航系统的鲁棒性和准确性。最后，在Gazebo中搭建了相应的仿真环境，并进行了算法验证。仿真结果表明，该方法能够实现无人车在巡检过程中实时可靠的自主导航，具有较好的工程应用价值。     

Robotic Air Vehicle: A Pilot's Perspective

This paper focuses on concepts and technologies required to develop a robotic air vehicle (RAV). A vehicle of this type has the capability to be a launch and forget weapon system. The authors are engineers and pilots so they view both the technical approach and piloting issues with equal importance. RAV must have the machine intelligence to make decisions within the mission and battlefield constraints. This requires a piloting expert system and route planner to perform passive terrain following, terrain avoidance, obstacle avoidance, and autonomous navigation based on low cost sensor inputs such as a multifunction FLIR, digital terrain map, and directional reference systems. RAV is a cost effective way to fight in a threat environment where aircrew loss rates would be unacceptable. RAV provides the Air Force a means to expand its combat capabilities.     

A system for obstacle detection during rotorcraft low altitudeflight

An airborne vehicle such as a rotorcraft must avoid obstacles like antennas, towers, poles, fences, tree branches, and wires strung across the flight path. Automatic detection of the obstacles and generation of appropriate guidance and control actions for the vehicle to avoid these obstacles would facilitate autonomous navigation. The requirements of an obstacle detection system for rotorcraft in low-altitude Nap-of-the-Earth (NOE) flight based on various rotorcraft motion constraints is analyzed here in detail. It is argued that an automated obstacle detection system for the rotorcraft scenario should include both passive and active sensors to be effective. Consequently, it introduces a maximally passive system which involves the use of passive sensors (TV, FLIR) as well as the selective use of an active (laser) sensor. The passive component is concerned with estimating range using optical flow-based motion analysis and binocular stereo. The optical flow-based motion analysis that is combined with on-board inertial navigation system (INS) to compute ranges to visible scene points is described. Experimental results obtained using land vehicle data illustrate the particular approach to motion analysis     

美国陆军PNT能力发展趋势分析

针对当前全球定位系统(GPS)易受干扰和攻击的影响,定位、导航与授时(PNT)系统需灵活应对多种复杂战场环境。分析了美国陆军未来发展先进PNT技术的背景,重点分析了美国陆军PNT能力的发展趋势,其中主要包括了伪卫星系统、车辆导航系统、惯性导航、定位、导航系统辅助传感器、导航传感器融合、导航仿生技术、授时、PNT建模与仿真、导航战技术应用、自主与人工智能在PNT中的应用等11个方面的发展趋势。最后给出了简要总结,认为美陆军将注重改进单兵和车辆态势感知能力,以提高未来支持战场指挥官的任务指挥和决策能力,同时重点关注了开放式系统架构、SWaP-C优化、自主技术和人工智能技术,以提升PNT的整体能力。     

无人机自动着陆中的机器视觉辅助技术

设计了一套辅助无人机自动着陆的机器视觉系统。该系统由机载硬件设备和用户开发软件共同组成,用以完成数字图像处理任务和无人机运动参数估计任务。系统传感器包括一个单目摄像机和机载惯性陀螺;数字图像处理使用的主要算法有图像的轮廓提取、角点检测和模版匹配。基于角点处各个方向上灰度差变化较大的特征,依据最小核值相似(SUSAN)算法和角点几何结构分析,提出一种改进的角点特征提取算法;根据任务开发的位置参数估计算法依据摄像机透视投影理论,运用摄像机成像标定方法导出了一种高精度的位置测量模型。通过计算机仿真表明,所提出的计算机视觉位置参数估计算法可以达到无人机着陆过程的精度要求。     

无人机空中加油自主会合的制导与控制

针对无人机空中加油的自主会合问题,进行了相应制导律和非线性控制器的设计。通过改进的带角度约束的三维比例制导律实现对航向角的控制,以协调转弯的方式将航迹角指令转化为姿态角指令。基于无人机六自由度的动力学模型,针对无人机的姿态控制,采用时标分离的方法设计了慢子系统和快子系统,并对这两个子系统分别进行动态逆控制设计。同时,基于滑模控制的方法设计了满足自主会合要求的速度控制律。在保证无人机飞行稳定的基础上,实现了对控制和制导指令的精确跟踪。仿真结果表明,所设计的制导律和控制律能够实现无人机空中加油的自主会合,具有良好的动态特性。     

有人/无人机混合编队有限干预式协同决策

针对Leader-Follower异构型有人/无人机混合编队协同决策系统具有递阶分布式决策结构、决策信息分散以及通信约束等特点,在智能体模糊认知图(ABFCM)和动态模糊认知图(DFCM)的理论基础上,提出了一种有限干预式协同决策机制。通过构建层次化的Follower平台自主决策模型,实现了该平台与外部系统良好的交互能力,体现了自主决策的"动态性"。通过设计Leader平台的3种干预策略,满足了不同层次的决策需求,体现了干预过程的"有限性"。仿真结果表明:有限干预协同决策模型能够适应外部环境的动态变化,充分发挥Follower平台的自主决策能力;而不同层次的有限干预介入既减轻了Leader平台的控制负荷,又保证了决策的有效性和可行性,可为解决其他同类复杂系统的协同决策问题提供理论依据和方法参考。     

Near term approach to data relay for satellites under test

The increasing need for a continuous communications link with U.S. Department of Defense (DoD) spacecraft during test missions in low Earth orbit (LEG) has resulted in greater interest in geosynchronous data relay services. This may be a more economical alternative to building additional remote tracking stations for the Air Force Satellite Control Network (AFSCN), and avoids tying up operational assets for a test mission. A low-cost near-term approach for such a space-based data relay system would utilize two existing Defense Satellite Communication System III spacecraft, two existing ground terminals, and a small, standardized terminal using autonomous antenna pointing for the space vehicle under test. Such a system design is presented     

空天飞行器建模分析与自主重构

空天飞行器(ASV)跨临近空间飞行,具有高超声速、大飞行包线、参数时变等特征,必须应对故障、环境变化等高度不确定因素进行自主重构。研究和建立了ASV运动学模型,分析了时域、频域特性以及参数变化和运动特性,研究了纵向静稳定性、舵面操纵特性等与高度、马赫数的关系;提出了自主重构方案,给出了一种控制效益在线估计算法,提出并证明了可估计的充分条件;提出了基于模糊逻辑的线性规划重构算法,根据控制效益的实时估计结果对冗余异类效应器智能地进行控制分配。数值仿真验证了估计算法的稳定性和鲁棒性,说明该方案能够实现飞行器自主适应性重构,可应用于临近空间飞行器自适应控制等领域。     

法国高超声速冲压发动机技术研究(英文)

法国正在致力于发展高超声速吸气式推进系统和推阻平衡预测能力所需要的技术。通过地面试验研究完成其大部分技术开发,目前正在对燃烧室进行攻关研究,以确保燃烧效率和结构热力强度满足要求。另一方面,为了掌握推阻平衡技术,必须进行飞行试验。因此,MBDA和ONERA正在推进LEA飞行试验计划。此计划始于2003年1月,准备在后续几年内完成马赫数4到8的若干次飞行试验。在2009年中期,通过关键设计评估完成了LEA飞行器推进系统的验证。将确定在2011年春季通过一系列自由射流试验验证飞行器的推阻平衡。此外,系统地开展了可重复使用运载器和高速民用飞行器的可行性和可实现的工作性能研究。     

A Dual-Mode Routing Algorithm for an Autonomous Roving Vehicle

A dual-mode algorithm for routing an unmanned autonomous roving vehicle designed to explore the uncertain terrain of other planets is presented. The algorithm consists of a global mode, which uses dynamic programming and terrain information available from photo reconnaissance data to determine a nominal optimal path, and a local mode, which routes the vehicle around obstacles whose presence, location, and extent are not known in advance. Gaussian probability density functions are used to simulate terrain for examples that illustrate the performance of the algorithm.     

无人机空中加油过程中基于机器视觉的相对位姿估计(英文)

本文主要研究了在无人机空中自主加油过程中,利用安装在无人机上的摄像机得到的视觉图像确定无人机与加油机之间相对位置关系的算法。本文以经典的OI算法为基础展开研究,文章主要分为三个部分:首先简要介绍了OI算法的基本实现方法,指出了在OI算法中,旋转矩阵R的初值的选择对于位姿估计的精度有一定的影响。其次主要介绍了一种线性算法用于获取R初值的方法,同时针对空中加油过程中无人机与加油机之间的相对姿态角变化较小的特点,提出了可以将旋转矩阵R的初值设为单位矩阵。论文最后在仿真环境下对相关算法展开实验研究,同时研究了在高斯噪声环境下特征点在加油机表面的分布对位姿估计结果的影响,论文得到如下的结论:1、针对空中加油过程中无人机与加油机之间的相对姿态角变化较小的特点,在高斯噪声环境下,以单位矩阵作为旋转矩阵的初值得到的位姿估计的结果好于以线性算法为初值的结果。2、在相同的高斯噪声环境下,特征点之间的距离越大时得到的位姿估计结果的精度越高。3、特征点的数量对相对位姿估计的精度没有明显影响。