Robotic interception of moving objects using an augmented idealproportional navigation guidance technique

Presents an approach to online, robot-motion planning for moving-object interception. The proposed approach utilizes a navigation-guidance-based technique, that is robust and computationally efficient for the interception of fast-maneuvering objects. Navigation-based techniques were originally developed for the control of missiles tracking free-flying targets. Unlike a missile, however, the end-effector of a robotic arm is connected to the ground, via a number of links and joints, subject to kinematic and dynamic constraints. Also, unlike a missile, the velocity of the robot and the moving object must be matched for a smooth grasp, thus, a hybrid interception scheme, which combines a navigation-based interception technique with a conventional trajectory tracking method is proposed herein for intercepting fast-maneuvering objects. The implementation of the proposed technique is illustrated via numerous simulation examples     

Proportional navigation guidance for robotic interception of moving objects

Two novel navigation‐guidance‐based methods are presented for on‐line‐robotic‐interception of fast‐maneuvering objects. For the first method, an ideal proportional navigation‐guidance (IPNG) technique is used during phase I of the two‐phase robot trajectory planning and control strategy. For the second method, an augmented form of the IPNG (AIPNG) technique is suggested for phase I, when a reliable estimation of the acceleration of the target can be provided to the interceptor. Both techniques are modified to reflect the greater mobility of a robotic manipulator over an airborne interceptor. The convergence analyses of both methods are detailed and compared to that of a conventional moving‐object tracking method. Computer simulations clearly illustrate the effectiveness of the IPNG‐based interception methods over pure tracking‐based techniques proposed in the cited literature. © 2000 John Wiley & Sons, Inc.     

Navigation-Guidance-Based Robotic Interception of Moving Objects in Industrial Settings

An important task for autonomous industrial robotic systems is the interception of moving objects. In order to achieve this objective, an on-line robot-motion planning technique that utilizes real-time sensory feedback about the object's motion is needed. In this paper, an Ideal Proportional Navigation Guidance (IPNG) based technique is utilized for on-line robot-motion planning. One must note, however, that navigation-guidance techniques were originally developed for bringing the interceptor into a collision course with (hostile) airborne targets. Therefore, in our case, a conventional tracking technique must be utilized as a subsequent phase to an initial IPNG-based robot-motion planning phase in order to ensure smooth interception.The implementation of the hybrid scheme in industrial settings, where one may not have access to the robot's dynamic model nor to the joints' controllers, is discussed. Real-time experimental results using an industrial robot and a computer-vision system are presented, confirming the (interception-time) superiority of our proposed scheme over conventional tracking techniques.     

Proportional navigation guidance using predictive and time delay control

A new formulation of the proportional navigation guidance law using the continuous time nonlinear predictive control approach is proposed. The guidance law needs information about the target acceleration for its implementation, which is generally not available. In this paper, this problem is addressed by estimating the target acceleration using the time delay control (TDC). The effectiveness of the guidance law and the estimation of the target acceleration is demonstrated by simulation in a realistic scenario against a highly maneuvering target.     

Modeling and querying moving objects in networks

Moving objects databases have become an important research issue in recent years. For modeling and querying moving objects, there exists a comprehensive framework of abstract data types to describe objects moving freely in the 2D plane, providing data types such as moving point or moving region. However, in many applications people or vehicles move along transportation networks. It makes a lot of sense to model the network explicitly and to describe movements relative to the network rather than unconstrained space, because then it is much easier to formulate in queries relationships between moving objects and the network. Moreover, such models can be better supported in indexing and query processing. In this paper, we extend the ADT approach by modeling networks explicitly and providing data types for static and moving network positions and regions. In a highway network, example entities corresponding to these data types are motels, construction areas, cars, and traffic jams. The network model is not too simplistic; it allows one to distinguish simple roads and divided highways and to describe the possible traversals of junctions precisely. The new types and operations are integrated seamlessly into the ADT framework to achieve a relatively simple, consistent and powerful overall model and query language for constrained and unconstrained movement.     

A scalable constraint-based Q-hash indexing for moving objects

In this paper, we develop a Q-hash index structure to efficiently store the position of moving objects. An environment of moving objects contains continuously changing locations which are hard to index using traditional index structures such as R-trees, QuadTrees and their variants. In order to answer the queries accurately, one of the problems faced in storing these positions is the number of updates that have to be made to the database whenever locations change. The high maintenance overhead on updates leads to performance degradation of these index structures; additionally, it makes the database very bulky which results in very poor performance in terms of query execution time. One of the main objectives of the structure we propose is to minimize the number of updates to the database to an optimal number so that the accuracy and response time of the query result are not compromised and at the same time the number of wireless communications can be reduced. The indexing is done using a hashing technique where the hashing function makes use of a region based QuadTree structure. To improve the efficiency of the query processing our index structure helps us define constraints over speed, direction and location of the moving object at the device level which controls the number of updates. In addition, in order to answer different query types efficiently at all levels we propose a three-tier (moving object, regional server, central repository) architecture. Our extensive performance evaluation and comparison of the proposed technique concludes that our scheme outperforms existing Q + R-tree and QuadTree in terms of range query execution time by a high order of magnitude.     

An adaptive hashing technique for indexing moving objects

Although hashing techniques are widely used for indexing moving objects, they cannot handle the dynamic workload, e.g. the traffic at peak hour vs. that in the night. This paper proposes an adaptive hashing technique to support the dynamic workload efficiently. The proposed technique maintains two levels of the hashes, one for fast moving objects and the other for quasi-static objects. A moving object changes its level adaptively according to the degree of its movement. We also present the theoretical analysis and experimental results which show that the proposed approach is more suitable than the basic hashing under the dynamic workload.     

An efficient location encoding method for moving objects using hierarchical administrative district and road network

Due to the rapid development in mobile communication technologies, the usage of mobile devices such as cell phone or PDA has increased significantly. As different devices require different applications, various new services are being developed to satisfy the needs. One of the popular services under heavy demand is the location-based service (LBS) that exploits the spatial information of moving objects per temporal changes. In order to support LBS well, in this paper, we investigate how spatio-temporal information of moving objects can be efficiently stored and indexed. In particular, we propose a novel location encoding method based on hierarchical administrative district information. Our proposal is different from conventional approaches where moving objects are often expressed as geometric points in two-dimensional space, (x, y). Instead, in ours, moving objects are encoded as one-dimensional points by both administrative district as well as road information. Our method becomes especially useful for monitoring traffic situation or tracing location of moving objects through approximate spatial queries.     

Efficient tracking of moving objects using a relational database

Tracking uncooperative moving objects by means of radar is a complex task due to clutter and association problems in multi-target scenarios. An approach to solve this problem is probabilistic multiple hypothesis tracking (PMHT). This method combines classical track filtering with a likelihood ratio test for the estimation of the plot-to-track association. The basics of PMHT and similar algorithms have gained much attention recently. However, the efficient implementation of real world applications of this technique still represents a challenging task. Since a common requirement in this context is the reliable storage of track data in a database, an implementation of the tracker's calculation inside a database management system (DBMS) using SQL views is desirable. A naive implementation of PMHT using a commercial DBMS, however, usually leads to performance problems because of the high frequency of measurement updates. In this paper, we propose possible optimizations for solving these performance problems. Their usage leads to a dramatic run-time improvement in our sample case and makes the implementation of PMHT in a database context feasible.     

移动闭塞系统列车组合定位导航技术研究

首先,分析了移动闭塞系统及其定位导航技术的研究现状,建立了基于网络实时动态测量(RTK)技术的GPS/INS/MM的定位导航组合方案;然后,提出了用伪距差分计算用户站概略位置和用载波相位差分计算整周模糊度单差值的快速差分算法.并讨论了有助于列车导航和控制的列车信息移动管理和基于GPRS的数据通信等;最后,对网络RTK快速差分算法进行了仿真分析,其结果验证了该算法对实现列车实时精确定位导航的可行性.     

欧美电子监听技术标准研究

根据欧洲电信标准委员会（ETSI）及美国《通讯协助法》（CALEA）关于电子监听标准的研究和规定,本文分析了在电子监听中执法机构对电信服务提供者的要求、监听的相关数据类型以及交接接口标准等问题。对规范我国电子监听标准、开展电子监听工作有一定的借鉴和帮助。     

A method of real-time recognition of moving objects and its application

A simple method of real-time recognition of moving objects, as well as its theoretical basis are described. This method utilizes a TV camera to pick up image signals from an object moving in the horizontal scan direction. The shape and position of the object are detected at every vertical scanning period by using the information from a few window-like image portions each consisting of four sub-areas. This method is succesfully applied as an electronic eye to a bolting robot used for concrete pile/pole manufacture.     

利用FPGA实现视频移动目标的有效检测

利用FPGA实现了一个视频移动目标检测系统,算法的基础是背景差分法。为了准确检测和定位移动目标,利用了灰度漂移算法和多颜色空间信息融合算法。灰度漂移算法是课题组最近在研究高斯混合模型的过程中提出的一种消除背景差分法检测的移动目标存在过多噪声杂点的算法,可以非常有效地消除由于微震动、空气扰动等原因导致的像素灰度在邻近区域发生漂移的现象;多颜色空间信息融合就是利用多个颜色空间中的一些互补分量共同确定移动目标。利用FPGA实现了上述两种算法,在移动目标的实时检测和跟踪中取得了很好的效果,对于丰富和增强监控系统功能有重要意义。     

Optimal motion planning using navigation measure

We introduce navigation measure as a new tool to solve the motion planning problem in the presence of static obstacles. Existence of navigation measure guarantees collision-free convergence at the final destination set beginning with almost every initial condition with respect to the Lebesgue measure. Navigation measure can be viewed as a dual to the navigation function. While the navigation function has its minimum at the final destination set and peaks at the obstacle set, navigation measure takes the maximum value at the destination set and is zero at the obstacle set. A linear programming formalism is proposed for the construction of navigation measure. Set-oriented numerical methods are utilised to obtain finite dimensional approximation of this navigation measure. Application of the proposed navigation measure-based theoretical and computational framework is demonstrated for a motion planning problem in a complex fluid flow.     

Field testing of a rover guidance, navigation, and control architecture to support a ground-ice prospecting mission to Mars

This paper provides an overview of a rover guidance, navigation, and control (GN&C) architecture being developed to support a ground-ice prospecting mission to Mars. The main contribution of this paper is to detail an integrated field campaign that demonstrates the viability of the key rover GN&C techniques needed to carry out this mission. Tests were conducted on Devon Island in the Canadian High Arctic during the summer of 2009, wherein a large field robot was driven on real polygonal terrain (a landform of interest on Mars). Lessons learned and recommendations for future work are provided.     

基于运动点团的鱼眼图像中多目标检测方法研究

采用运动点团模式对鱼眼视频序列中的目标检测方法进行了研究和探讨。运动点团模式的运动目标检测分为三个层次,每个层次对应一个具体的检测算法,即基于像素层的背景提取和更新、运动点团层的点团检测和判定及运动目标层的目标标记和跟踪。对三个算法的原理进行了探讨,并结合鱼眼图像的特点进行了算法改进和优化。实验结果表明,以运动点团作为中间检测过程的方法能有效对圆形鱼眼视频序列中的多个运动目标进行检测,特别是图像边缘的大畸变、低分辨率目标,相比传统的检测方法具有更好的检测稳定性和准确性,在大范围智能视频监控中具备很好的实际应用价值。     

Update-efficient indexing of moving objects in road networks

Recent advances in wireless sensor networks and positioning technologies have boosted new applications that manage moving objects. In such applications, a dynamic index is often built to expedite evaluation of spatial queries. However, the development of efficient indexes is a challenge due to frequent object movement. In this paper, we propose a new update-efficient index method for moving objects in road networks. We introduce a dynamic data structure, called adaptive unit, to group neighboring objects with similar movement patterns. To reduce updates, an adaptive unit captures the movement bounds of the objects based on a prediction method, which considers road-network constraints and the stochastic traffic behavior. A spatial index (e.g., R-tree) for the road network is then built over the adaptive unit structures. Simulation experiments, carried on two different datasets, show that an adaptive-unit based index is efficient for both updating and querying performances.

基于帧间差分的自适应运动目标检测方法*

本文提出了一种基于帧间差分的自适应运动目标检测算法。算法利用直方图统计各像素点处最大概率灰度的方法提取出连续视频的背景图像;相邻帧利用帧差法得到运动区域图像;利用运动区域图像与背景图像差分的方法提取出运动目标。实验结果表明,该算法能在多个不确定性因素的序列视频中较好的提取背景图像,能及时响应实际场景变化,提高运动目标检测的质量。