移动机器人实时目标跟踪系统设计与实现

针对单目视觉移动机器人目标跟踪的实时性和鲁棒性要求,提出了基于Kalman滤波器的改进Camshift算法检测和定位目标.将Kalman预测值作为目标初始位置,补偿摄像头和目标相对运动导致的目标在图像中的偏移.在系统“跟丢”后判断目标丢失的原因,根据原因自适应拓展搜索窗口作为Cam-shift算法的下一帧初始搜索窗口.为了验证改进算法的有效性,自主研制了一种应用该算法的履带式机器人实时目标跟踪系统.实验结果表明:该系统具有很好的鲁棒性和实时性.     

Parallel implementation of the extended square-root covariancefilter for tracking applications

Parallel implementations of the extended square-root covariance filter (ESRCF) for tracking applications are developed. The decoupling technique and special properties used in the tracking Kalman filter (KF) are employed to reduce computational requirements and to increase parallelism. The application of the decoupling technique to the ESRCF results in the time and measurement updates of m decoupled (n/m)-dimensional matrices instead of one coupled n-dimensional matrix, where m denotes the tracking dimension and n denotes the number of state elements. The updates of m decoupled matrices are found to require approximately m fewer processing elements and clock cycles than the updates of one coupled matrix. The transformation of the Kalman gain which accounts for the decoupling is found to be straightforward to implement. The sparse nature of the measurement matrix and the sparse, band nature of the transition matrix are explored to simplify matrix multiplications     

A hierarchical cyclic pursuit scheme for vehicle networks

The agreement problem is studied whereby a group of mobile agents achieves convergence to a common point. A hierarchical cyclic pursuit scheme is introduced, and it is shown that this scheme yields a very significant increase in the rate of convergence to a common point when compared to traditional cyclic pursuit. A second scheme is introduced in which there are more communication links between vehicles. It is shown that this scheme produces a rate of convergence greater than the traditional scheme but significantly less than the hierarchical scheme.     

面向目标跟踪的混合WMSN设计与实现

设计了一个面向目标跟踪的混合无线多媒体传感器网络,主要实现了低功耗的无线图像传感器节点、无线温度传感器节点和服务器软件。对节点和单Sink下的网络性能进行了测试。结果表明：相比较于Cyclops和MeshEye,无线图像传感器节点的处理速度分别从8 MHz和55 MHz提高到240 MHz;处理器工作在188 MHz时的能耗是52.7 mA,低于Imote在104 MHz时的66 mA工作电流;当错包率接近0时,网络实际带宽约36 kb/s;基于Shape Matching的目标跟踪数据处理策略有效地降低了能量消耗。     

基于CKF 的分布式滤波算法及其在目标跟踪中的应用

针对已有基于Sigma点信息滤波的分布式滤波算法,其性能易受参数影响而导致应用范围受限的问题,以容积卡尔曼滤波(CKF)为基础,利用信息滤波和平均一致性理论提出一种分布式CKF算法。该算法在保持分布式滤波优良特性(即可扩展性和对节点故障强鲁棒性)的同时,兼具CKF的高滤波精度和强稳定性。仿真结果表明了所提出算法的有效性,与分布式Unscented卡尔曼滤波(UKF)算法相比,该算法显著提高了目标跟踪的精度和稳定性。     

粒子滤波理论及其在目标跟踪中的应用

非线性估计领域的经典算法是扩展Kalman滤波（EKF）,它采用了Taylor展开的线性变换来近似非线性模型,因而存在计算量大、实时性差、估计精度低等缺点。而粒子滤波采用一些带有权值的随机样本（粒子）来表示所需要的后验概率密度,而不是采用传统的线性变换,从而得到基于物理模型的近似最优数值解,具有精度高、收敛速度快等特点。对经典的纯方位跟踪问题进行了仿真。仿真结果表明,粒子滤波器的跟踪性能要远优于EKF的性能。     

Decision-aware data suppression in wireless sensor networks for target tracking applications

Target tracking applications of wireless sensor networks (WSNs) may provide a high performance only when a reliable collection of target positions from sensor nodes is ensured. The performance of target tracking in WSNs is affected by transmission delay, failure probability, and nodes energy depletion. These negative factors can be effectively mitigated by decreasing the amount of transmitted data. Thus, the minimization of data transfers from sensor nodes is an important research issue for the development of WSN-based target tracking applications. In this paper, a data suppression approach is proposed for target chasing in WSNs. The aim of the considered target chasing task is to catch a moving target by a mobile sink in the shortest time. According to the introduced approach, a sensor node sends actual target position to the mobile sink only if this information is expected to be useful for minimizing the time in which target will be caught by the sink. The presented method allows sensor nodes to evaluate the usefulness of sensor readings and select those readings that have to be reported to the sink. Experiments were performed in a simulation environment to compare effectiveness of the proposed approach against state-of-the-art methods. Results of the experiments show that the presented suppression method enables a substantial reduction in the amount of transmitted data with no significant negative effect on target chasing time.     

双目视觉模型移动目标跟踪系统

为了使机器人能够对目标进行自主智能的跟踪,基于仿生学原理建立双目视觉模型,设计出四自由度的仿人眼颈跟踪系统,通过上位机与下位机的配合以及2台摄像机与4台直流电机,实现双目视觉移动目标跟踪系统.该系统通过双目摄像机对目标进行图像采集,由PC机对目标进行特征提取以及一系列处理后计算出目标的移动范围,将目标移动数据传输至下位机后通过PID控制算法平滑控制直流电机的运转方向与运转速度,从而对移动目标实现良好的跟踪性能.     

VLSI implementation of star detection and centroid calculation algorithms for star tracking applications

Nowadays, hardware implementation of image and video processing algorithms on application specific integrated circuit (ASIC) has become a viable target in many applications. Star tracking algorithm is commonly used in space missions to recover the attitude of the satellite or spaceship. The algorithm matches stars of the satellite camera with the stars in a catalog to calculate the camera orientation (attitude). The number of stars in the catalog has the major impact on the accuracy of the star tracking algorithm. However, the higher number of stars in the catalog increases the computation burden and decreases the update rate of the algorithm. Hardware implementation of the star tracking algorithm using parallel and pipelined architecture is a proper solution to ensure higher accuracy as well as higher update rate. Noise filtering and also the detection of stars and their centroids in the camera image are the main stages in most of the star tracking algorithms. In this paper, we propose a new hardware architecture for star detection and centroid calculation in star tracking applications. The method contains several stages, including noise smoothing with fast Gaussian and median filters, connected component labeling, and centroid calculation. We introduce a new and fast algorithm for star labeling and centroid calculation that needs only one scan of the input image.     

A dual-kernel-based tracking approach for visual target

A dual-kernel-based tracking approach for visual target is proposed in this paper. The similarity between candidate and target model, and the contrast between candidate and its neighboring background are considered simultaneously when evaluating a target candidate. The similarity is measured by Bhattacharyya coefficient while the contrast is calculated with Jensen-Shannon divergence, and they are adaptively fused into a novel objective function. By maximizing the linear approximation of objective function, a dual-kernel target location-shift relation from current location to a new location is induced. According to the location-shift relation, the optimal target location can be recursively gained in the mean shift procedure. Experimental evaluations on several image sequences demonstrate that the proposed algorithm can gain more accurate target location and better identification power to false target, and it is also robust to deformation and partial occlusion.     

基于WebSocket和Redis的移动目标轨迹跟踪系统设计与实现

针对物联网系统中监控移动目标位置和轨迹信息的需求,设计和实现了一种基于Websocket和Redis移动目标轨迹跟踪系统.该系统主要分为三个部分:首先利用手机App客户端采集移动目标的轨迹信息,然后利用Webocket将轨迹信息传输到远程服务器进行保存,最后服务端将传送的轨迹信息保存在Redis+MySQL数据库中,并...     

Generalization of nonlinear cyclic pursuit

In this paper, some generalizations of the problem of formation of a group of autonomous mobile agents under nonlinear cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i+1 modulo n. Each agent is subjected to a nonholonomic constraint. A necessary condition for equilibrium formation to occur among a group of agents with different speeds and different controller gains is obtained. These results generalize equal speed and equal controller gain results available in the literature.     

A fuzzy decentralized variable structure tracking control with optimal and improved robustness designs: theory and applications

To begin with, each subsystem of a nonlinear interconnected system was approximated by a weighted combination of L linear pulse transfer function systems (LPTFSs). For every nominal LPTFS of the mth subsystem, a dead-beat to its switching surface was first designed. The output disturbance of the mth LPTFS included the interconnections coming from the other subsystems, the approximation error of the mth subsystem, and the interactions resulting from the other LPTFSs. In general, this output disturbance was not small and contains various frequencies. Under this circumstances, the H/sup /spl infin//-norm of the weighted sensitivity function between the mth switching surface and its corresponding output disturbance was minimized. In addition, an appropriate selection of the weighted function for the sensitivity could reject the corresponding mode of the output disturbance. Although the effect of the output disturbance is attenuated and partially rejected, a better performance could be enhanced by a switching control based on the Lyapunov redesign. In addition, the stability of the overall system was verified by Lyapunov stability theory. The simulations for the LPTFSs with different delays or nonminimum phases or unstable features were arranged to evaluate the effectiveness of the proposed control. Finally, the application to the trajectory tracking of the robot arm including the fuzzy modeling was carried out to confirm the practicality of the proposed control.     

Stable polygons of cyclic pursuit

In a companion paper [5] we resolved the question of whether cyclic pursuits can exhibit ‘non-mutual’ captures. Although, as we showed, non-mutual captures can occur, the set of initial conditions which lead to them has Lebesgue measure zero. Thus, generically, cyclic pursuits collapse into a mutual capture. In this paper we consider whether the pursuit configuration can asymptotically approach a regular one for a non-trivial set of initial conditions. More precisely, we study the stability of regular geometries of cyclic pursuit. We show that in all dimensions the only stable regular n-bug shapes are the regular two dimensional n-gons, n≥7, in which each vertex chases its neighboring vertex in some fixed orientation. We also analize the three bug cyclic pursuit in detail, proving that, except for the equilateral initial position, the triangle formed is asymptotically degenerate with the minimum interior angle tending to zero while the vertex at which the minimum is located rotates among the vertices infinitely often. This revised version was published online in August 2006 with corrections to the Cover Date.     

关于UKF方法的新探索及其在目标跟踪方面的应用

在跟踪和控制领域,和被广泛采用的推广卡尔曼滤波(extended Kalman filter)方法相比较,近年发展起来的Unscented卡尔曼滤波(Unscented Kalman filter)具有易于实现、计算量相当而精度较高等诸多优点．本文深入探讨了这一方法,并以目标跟踪为背景,提出了两种基于Unscented变换的新的滤波方法,分别在算法的精确和快速两个方向上进行了尝试,仿真结果表明,这种探索是行之有效的．     

Adaptive compressive sensing for target tracking within wireless visual sensor networks-based surveillance applications

Wireless Visual Sensor Networks (WVSNs) have gained significant importance in the last few years and have emerged in several distinctive applications. The main aim is to design low power WVSN surveillance application using adaptive Compressive Sensing (CS) which is expected to overcome the WVSN resource constraints such as memory limitation, communication bandwidth and battery constraints. In this paper, an adaptive block CS technique is proposed and implemented to represent the high volume of captured images in a way for energy efficient wireless transmission and minimum storage. Furthermore, to achieve energy-efficient target detection and tracking with high detection reliability and robust tracking, to maximize the lifetime of sensor nodes as they can be left for months without any human interactions. Adaptive CS is expected to dynamically achieve higher compression rates depending on the sparsity nature of different datasets, while only compressing relative blocks in the image that contain the target to be tracked instead of compressing the whole image. Hence, saving power and increasing compression rates. Least mean square adaptive filter is used to predicts target’s next location to investigate the effect of CS on the tracking performance. The tracking is achieved in both indoor and outdoor environments for single/multi targets. Results have shown that with adaptive block CS up to 20 % measurements of data are required to be transmitted while preserving the required performance for target detection and tracking.     

Sensor scheduling for target tracking: A Monte Carlo sampling approach

We study the problem of sensor-scheduling for target tracking—to determine which sensors to activate over time to trade off tracking performance with sensor usage costs. We approach this problem by formulating it as a partially observable Markov decision process (POMDP), and develop a Monte Carlo solution method using a combination of particle filtering for belief-state estimation and sampling-based Q-value approximation for lookahead. To evaluate the effectiveness of our approach, we consider a simple sensor-scheduling problem involving multiple sensors for tracking a single target.     

Causal maps: theory, implementation, and practical applications in multiagent environments

Analytical techniques are generally inadequate for dealing with causal interrelationships among a set of individual and social concepts. Usually, causal maps are used to cope with this type of interrelationships. However, the classical view of causal maps is based on an intuitive view with ad hoc rules and no precise semantics of the primitive concepts, nor a sound formal treatment of relations between concepts. We solve this problem by proposing a formal model for causal maps with a precise semantics based on relational algebra and the software tool, CM-RELVIEW, in which it has been implemented. Then, we investigate the issue of using this tool in multiagent environments by explaining through different examples how and why this tool is useful for the following aspects: 1) the reasoning on agents' subjective views, 2) the qualitative distributed decision making, and 3) the organization of agents considered as a holistic approach. For each of these aspects, we focus on the computational mechanisms developed within CM-RELVIEW to support it.