水下声自导武器目标跟踪方法研究

水下声自导武器采用主动方式检测、跟踪目标时,目标跟踪过程表现为一个动基座时变过程,难以直接运用卡尔曼滤波进行目标跟踪。利用水下声自导武器导航定位及航行姿态参数和水下声自导武器检测到的目标信息,通过坐标变换将目标坐标从水下声自导武器坐标系变换到大地坐标系解决了观测基座运动的问题,通过每次观测时间实时计算每次观测的采样时间解决了观测时变问题,建立了基于自适应衰减记忆卡尔曼滤波的水下声自导武器目标跟踪模型,给出了滤波初值选取的工程方法,仿真实验证明该模型正确,跟踪算法能够在10次观测内实现对目标的跟踪,具有较强的机动目标跟踪能力,算法收敛速度较快。     

Efficient visual homing based on Fourier transformed panoramic images

We present a fast and efficient homing algorithm based on Fourier transformed panoramic images. By continuously comparing Fourier coefficients calculated from the current view with coefficients representing the goal location, a mobile robot is able to find its way back to known locations. No prior knowledge about the orientation with respect to the goal location is required, since the Fourier phase is used for a fast sub-pixel orientation estimation. We present homing runs performed by an autonomous mobile robot in an office environment. In a more comprehensive investigation the algorithm is tested on an image data base recorded by a small mobile robot in a toy house arena. Catchment areas for the proposed algorithm are calculated and compared to results of a homing scheme described in [M. Franz, B. Schölkopf, H. Mallot, H. Bülthoff, Where did I take that snapshot? Scene based homing by image matching, Biological Cybernetics 79 (1998) 191–202] and a simple homing strategy using neighbouring views. The results show that a small number of coefficients is sufficient to achieve a good homing performance. Also, a coarse-to-fine homing strategy is proposed in order to achieve both a large catchment area and a high homing accuracy: the number of Fourier coefficients used is increased during the homing run.     

An Orientation Invariant Visual Homing Algorithm

Visual homing is the ability of an agent to return to a goal position by comparing the currently viewed image with an image captured at the goal, known as the snapshot image. In this paper we present additional mathematical justification and experimental results for the visual homing algorithm first presented in Churchill and Vardy (2008). This algorithm, known as Homing in Scale Space, is far less constrained than existing methods in that it can infer the direction of translation without any estimation of the direction of rotation. Thus, it does not require the current and snapshot images to be captured from the same orientation (a limitation of some existing methods). The algorithm is novel in its use of the scale change of SIFT features as an indication of the change in the feature’s distance from the robot. We present results on a variety of image databases and on live robot trials.     

翼伞系统在较大风场中的归航控制

翼伞系统是一类特殊的柔翼飞行器,由于其飞行速度较低,容易受到风场的影响.针对翼伞系统在较大风场中难以准确跟踪归航轨迹、实现精确着陆,因此将风场中平均风的影响在轨迹规划中予以考虑,采用一种改进的粒子群算法(particle swarm optimization,PSO)优化分段归航轨迹;将紊流的影响作为外界的干扰,由线性自抗扰控制器(linear active disturbance rejection controller,LADRC)进行修正.仿真结果表明,该归航控制方法对提高翼伞系统在较大风场环境下的抗风性能和归航精度有重要意义.     

基于全景视觉的机器人回航方法

提出一种使用全景视觉系统引导机器人回航的方法.利用全景视觉装置采集出发位置(Home位置)的全景图像,使用SURF(Speeded-Up Robust Feature)算法提取全景图像中的特征点作为自然路标点.机器人回航过程中,将当前位置获得的全景图像与Home位置的全景图像进行特征匹配,确定白然路标点之间的对应关系....     

Path Integration Mechanism with Coarse Coding of Neurons

Many animals can return home accurately after exploring for food using their own homing navigation algorithm. Path integration plays a critical role in homing navigation. It is believed that animals are able to recognize their relative location from the nest by accumulating both distance and direction experienced during their travel. We tested possible patterns of neuronal organization for a path integration mechanism. The neural networks consisted of a circular array of neurons, following population coding. We describe here a neural model of path integration involving a relatively small number of neurons and discuss how well the model operates for homing navigation. Robotic simulations suggest that a neural structure with only a few sensor neurons can successfully handle the path integration needed for homing navigation.     

一种求解N阶数码问题的通用算法

提出一种求解N阶数码问题的通用算法,可以在多项式时间内求出一个有确定上限的解。该算法将整个棋盘分为4个区域,对于归属不同区域的数码分别采用“单码归位”和“双码归位”子算法,最终使所有数码归位。分析和测试表明：该算法的时间复杂度为O（n^6）,而所得解决方案移动步数的上限为O（n^3）。     

翼伞系统动力学建模与分段归航设计

翼伞回收系统具有精确、定点、无损等特点,已成为当前回收领域的一个研究热点,首先建立了含附加质量的翼伞系统的六自由度动力学模型,然后将其带入翼伞系统的动力学方程中得到了运动轨迹以及三个姿态角随不同操纵方式变化的时间曲线,对翼伞系统的基本运动特性进行了分析.其次采用分段归航策略对翼伞系统的轨迹规划进行了设计,并利用遗传算法...     

基于VXI总线的鱼雷声自导系统仿真信号源设计

仿真信号源模拟鱼雷声呐基阵接收到的目标回波,是检测声自导系统性能的有效工具;介绍了鱼雷声自导系统仿真信号源的工作原理,给出了仿真信号源系统的总体设计方案,详细讨论了系统中VXI总线接口和信号源模块的硬件设计方案,最后对仿真信号源系统的软件设计进行了分析;仿真信号源的开发成功,为我国鱼雷声自导系统的研制提供了.必要的技术条件,对改善声自导系统的制导能力,提升鱼雷的作战效能有着极其重要的作用.     

基于像素时域剖面分析的序列图像中弱点目标检测算法

序列图像中弱点目标的实时检测算法,是光学精确制导信息处理系统中的关键算法之一。首先对现有基于像素时域剖面分析的检测算法进行了简要的综述,然后根据不同像素的时域剖面模型对其时域方差变化特性进行了详细分析,提出了一种基于自适应递归方差滤波器的检测算法。对仿真时域序列与真实图像数据进行实验,结果表明该算法可实现检测弱点目标。考虑到该算法可并行、递归计算,因此它在实时制导系统中有良好的应用潜力。     

Collision Detection and Safe Reaction Algorithm for Non-backdrivable Manipulator with Single Force/Torque Sensor

The paper presents a robust control law for homing of an autonomous robot. The proposed work aims to solve this problem for practical conditions such as random errors in commanded velocities and unknown distance sensor characteristics. The proposed steering control aligns the robot’s orientation with homing vector using arbitrary real valued distance function providing the capability to work in changing environment conditions. Finite time convergence to the equilibrium using proposed control law is achieved in the presence of bounded random velocity errors regardless of the initial position and orientation. Just the sign information as feedback supports applicability of proposed control law with any distance function. A matching parameter between panoramic images obtained at home and current positions is a function of distance between home and current positions. However, explicit relation between distance and image matching parameter is unknown. This work demonstrates the application of proposed method for visual homing based on image distance function rendering the benefit of minimal image processing. Various simulation and experimental results are presented for visual homing to support the theory presented in this paper. Advantage of proposed visual homing is also explored in changing environment conditions.     

基于LabVIEW的水下航行器制导系统建模与仿真

要在整合实际物力模块的仿真中更完美地利用LabVIEW对硬件支持的强大能力,最佳的解决方案必然是在纯Lab-VIEW环境下构筑完整的仿真模型。针对完全独立使用LabVIEW进行水下航行器制导系统仿真研究面临的动态系统建模和求解困难,提出了基于LabVIEW仿真模组建立和解算动态数学模型的方法。以水平面声自导系统采用自动调整提前角导引算法的制导仿真为例,给出了制导系统的数学模型,并详尽叙述了仿真系统的LabVIEW实现步骤,并给出了主要的仿真结果。结果表明,所述仿真方法简易可行,为可扩展的半物理仿真提供了有力的软件保障。     

自主水下航行器的回坞导引和入坞控制算法

针对军事侦察和海洋环境监测领域中对自主水下航行器（AUV）水下自主回收能力的需求,研究了AUV自主回收过程中回坞和入坞的导引和控制问题。将水下自主回收过程分为回坞导引和入坞控制两个连续的阶段,其中回坞阶段采用经典的视线（LOS）导引法,使AUV到达回收器正前方的回坞航路点;入坞阶段则采用非线性横向跟踪控制方法,使AUV精确跟踪沿回收器中轴线的入坞直线航路航行并最终进入回收器。采用REMUS AUV的模型参数对水下回收进行了仿真研究,结果表明该方法是有效的,具有良好的工程应用前景。     

鱼雷声自导检测目标过程的建模与实时仿真

在研究某型声自导鱼雷自导弹道仿真时,对鱼雷声自导检测目标的过程进行建模与仿真：应用牛顿迭代法求解自导作用距离,给出了迭代初值的域及选取原则;考虑声线传播受特定海域海水盐、温、压力梯度等因素影响,采用折线近似法计算自导接收声束空间范围。依此进行仿真建模,利用WISE仿真软件及Visual C 编制仿真应用程序,并利用Vega视景仿真软件实现弹道仿真数据的三维町视化。结果表明上述方法在鱼雷声自导弹道实时仿真中是可行和有效的。     

Metric embedding of view-graphs

Most recent robotic systems, capable of exploring unknown environments, use topological structures (graphs) as a spatial representation. Localization can be done by deriving an estimate of the global pose from landmark information. In this case navigation is tightly coupled to metric knowledge, and hence the derived control method is mainly pose-based. Alternative to continuous metric localization, it is also possible to base localization methods on weaker constraints, e.g. the similarity between images capturing the appearance of places or landmarks. In this case navigation can be controlled by a homing algorithm. Similarity based localization can be scaled to continuous metric localization by adding additional constraints, such as alignment of depth estimates. We present a method to scale a similarity based navigation system (the view-graph-model) to continuous metric localization. Instead of changing the landmark model, we embed the graph into the three dimensional pose space. Therefore, recalibration of the path integrator is only possible at discrete locations in the environment. The navigation behavior of the robot is controlled by a homing algorithm which combines three local navigation capabilities, obstacle avoidance, path integration, and scene based homing. This homing scheme allows automated adaptation to the environment. It is further used to compensate for path integration errors, and therefore allows to derive globally consistent pose estimates based on “weak” metric knowledge, i.e. knowledge solely derived from odometry. The system performance is tested with a robotic setup and with a simulated agent which explores a large, open, and cluttered environment. This work is part of the GNOSYS (FP6-003835-GNOSYS) project, supported by the European Commission.     

基于随机搜索的快速变形视觉归巢算法

提出一种用于求解机器人视觉归巢问题的改进变形算法。针对原始变形算法需要对参数空间进行穷尽搜索从而导致算法计算量大、应用范围窄等问题,文中采用一种基于随机选取起始点的梯度下降算法来获取目标点,大大减小需搜索的参数空间,提高算法的时间效率。对多个实际场景的实验表明,该算法在保持原变形算法良好性能的基础上,可将运算速度提高一个数量级。     

65米射电望远镜副面调整系统姿态精度监测与回零策略

上海天文台65米射电望远镜的副面调整机构为Stewart型并联机器人,为了及时发现该并联机器人因机械磨损或误差累积造成的精度下降问题,使用倾角传感器对并联机器人动平台姿态进行检测,求得动平台姿念均方根误差并将其与设计指标进行比较,从而用户可以判断是否需要进行维修或回零操作.为了提高并联机器人的易维护性,设计了光电传感器回零和磁尺(磁致伸缩位移传感器)回零两种回零方式,分析了两种回零方式以及通过回零操作对光电传感器和磁尺精度进行检测的原理.总结了该并联机器人需要进行回零操作的不同状况,并给出了相应的回零控制策略.实验证明本文提出的回零控制策略是解决并联机器人回零问题的一种有效方法.     

Chromatic adaptation for robust visual navigation

This paper analyzes the effects of the application of visual adaptation mechanisms on snapshot-based guidance methods. The guidance principle of the visual homing is proven to be a visual potential function with an equilibrium point located at the goal position. The presence of a potential function means that classical control theory principles based on the Lyapunov functions can be applied to assess the robustness of the navigation strategy. The Retinex algorithm, a blind chromatic equalization pre-filtering that performs color constancy with no a priori information about the illuminant, is proposed as an unsupervised visual adaptation mechanism. It increases the visual information similarity under changes in the illuminant, thus increasing the robustness of the visual guidance. Tests and comparisons are presented.     

Hippocampal neural network model performing navigation by homing vector field adhesion to sensor map

We propose an artificial neural network model for autonomous agents, i.e., mobile robots, to learn maps of environments and acquire the ability to perform home-navigation autonomously. The networks consists of two subnetworks, each of which has a similar structure with hippocampal lamellar neuronal circuits. Hebbian learning procedures self-organize the first subnetwork to output the distributed sinusoidal activity of the cells by accumulating motor information generated during movement, and the second subnetwork to output localized activity by prototyping sensory information. These patterns represent a homing vector providing the relative coordinates of the agent from a starting point, and a place code corresponding uniquely to a point of the environment. By attaching homing vectors to the sensor map, the homing vector is associated with the sensory stimuli. Then the agents can perform home-navigation autonomously by this association. This work was presented, in part, at the Second International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1997     

Aggregation in robot swarms using odometry

Aggregation is a useful building block behaviour that can allow a swarm of robots to interact with each other or a user more easily. Previous work on swarm robot aggregation has assumed that the capabilities of individual robots are quite limited. We test whether incorporating odometry as an additional capability is helpful and make the argument that odometry is both realizable and biologically plausible. We propose an algorithm called ODOCLUST which takes inspiration from the BEECLUST algorithm but uses a continuously active odometry-based homing process to achieve more tightly packed robot aggregates more quickly than BEECLUST. Initial results in simulation suggest that high-fidelity odometry is not required in order to see these gains.