一种改进RRT的多机器人编队路径规划算法

多机器人路径规划是机器人领域的一个热点问题,相比于单机器人路径规划,其算法难度和复杂度都有所增加,在规划时需要兼顾多机避障、相互协作等难点问题.本文提出一种改进快速扩展随机树的多机器人编队路径规划算法,用于解决多机器人在复杂环境下的编队路径规划问题.针对多机器人在编队规划中的位置约束问题,定义机器人之间的领航-跟随结构,并对机器人队形建模.针对规划过程中编队朝向变化问题,建立搜索树扩展方向与队形方向之间的联系,通过调整队形方向改变规划时的编队朝向.针对具有质点模型和非完整约束动力学模型两种不同模型的多机器人系统,分别进行了仿真实验.仿真结果表明该算法在处理多机器人编队路径规划问题时可以取得良好的效果.     

基于一致性理论的四旋翼无人机分布式编队控制方法

介绍了图论和群体系统一致性的相关理论,提出一种分布式四旋翼无人机编队控制方法,将四旋翼无人机描述为二阶积分器动力系统,采用相对位置偏差描述编队队形;根据四旋翼无人机之间通信拓扑关系将四旋翼无人机编队建模为图,探索了领航跟随法和基于图论法的融合策略,给出一种有领航者的二阶一致性算法。在该算法下,编队可以完成编队集结和编队机动等行为,最后通过仿真实验验证了该方法的有效性。     

紫外光通信协作编队无人机联盟围捕算法

编队无人机对目标无人机进行围捕是多无人机战场作战中重要且典型的任务之一，本文将无线紫外光通信技术与围捕算法结合，提出了一种紫外光通信协作编队无人机联盟围捕算法。该算法借助无线紫外光辅助无人机编队机间数据保密传输和非直视通信，将联盟生成算法与区域最小化策略进行融合，采用动态规划法对最优联盟结构进行求解，使用区域最小化策略对目标无人机实施空中围捕，完成在复杂场景中无人机编队高效围捕多目标任务。对区域最小化策略和本文提出的紫外光协作编队无人机联盟围捕算法进行了仿真对比，实验结果表明：所提出的紫外光协作编队无人机联盟围捕算法在无人机编队围捕多目标过程中平均降低了12.73%的能耗，算法迭代次数平均降低了27.49%，验证了该算法能耗少、围捕效率高的性能。     

特定领航者模式的多机器人编队控制方法

针对特定领航者模式的多机器人系统稳定性问题,提出了一种基于一致性的编队控制算法。考虑系统的各个状态都能够收敛到期望的定常相对值,利用Lyapunov稳定性理论和矩阵理论,推导出了该类方法使多机器人编队系统达到一致的充分条件,得到设计该条件下系统一致性协议的约束。随机设置了特定领航者模式的通信拓扑关系,利用上述推导获得的充分条件,进而对该算法收敛性进行分析,并针对该模式给出一个满足条件的算法。数值仿真验证了所提算法的有效性。     

基于改进烟花算法的多目标多机器人任务分配

多机器人任务规划是多机器人系统研究的主要问题之一,多目标多机器人任务规划是指同时对多机器人系统的多个指标进行优化。近年来,启发式算法越来越多地被用来解决多目标问题。本文提出了一种基于改进烟花算法的多目标多机器人任务分配方法,并详细讨论了多目标解的排序方法和选择策略。为了验证该方法的性能,对7个实例进行了实验,并对该方法和其他四种多目标算法,Non-dominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm 2 (SPEA2),Pareto Envelope-based Selection Algorithm (PESA ) 和一种改进的Strength Pareto Genetic Algorithm 2 (SPGA2)在S-metric指标上进行了比较。实验结果表明,在解集质量、解集覆盖度方面,基于改进烟花算法的多目标多机器人任务分配方法具有明显的优势。      

纵向打滑状态下的轮式移动机器人编队控制

针对轮式移动机器人车轮纵向打滑时的编队控制问题,提出一种基于滑移率补偿和模糊逻辑的多机器人编队控制器设计方法.首先,利用速度传感器获取机器人的实际速度信息,并进行滤波减少传感器噪声.结合速度输入指令信号得到滑移率估计值,用以描述机器人纵向打滑的程度.然后根据领航跟随法,设计补偿纵向打滑的编队控制策略,并采用模糊逻辑设计控制器参数.最后在Microsoft Robotics Developer Studio 4（MRDS4）中搭建3D物理仿真平台,进行编队控制仿真,验证了领航、跟随机器人发生打滑的情况下所提方法的有效性.     

区域多任务安全隐患排除的机器人调度策略

针对灰狼优化算法易陷入局部最优且单一算法不易解决障碍物空间多机器人隐患搜排的调度问题,提出了一种分步引导式多机器人安全隐患协同排除调度策略。首先引入非线性收敛因子调整策略和静态加权平均权重策略改进灰狼优化算法以避免算法陷入局部最优;随后通过改进的灰狼优化算法先后两次求解遍历顺序,引导机器人规划搜索路径与排除隐患点路径;最后在领航者-跟随者模型的基础上多机器人编队与队形变换避障,逐一到达隐患点位置实现多机器人的调度策略。通过国际通用6个基准函数进行测试,改进的灰狼优化算法在收敛速度、搜索精度及稳定性上均有明显提高,验证了区域多任务安全隐患排除的分步引导式多机器人协同调度策略的有效性。     

预警机指挥多编队作战中的威胁评估算法研究

在预警机指挥下的多编队作战中,态势评估和目标分配是关系到作战结果好坏的重要问题.作为态势评估的一部分,威胁评估是进行合理的目标分配的前提.基于多属性决策的原则,分析了影响目标编队威胁程度的重要因素,建立了预警机指挥多编队作战的威胁评估模型.运用适合多编队多机型作战分析的平均数动力学方法,提出了计算目标编队威胁程度的算法,并验证了模型的有效性.     

基于交互多模型的高机动群目标跟踪技术

针对杂波环境下密集多目标的跟踪问题,首先引入了编队群目标跟踪算法(FGT),并结合交互多模型(IMM)算法,提出了适用于杂波环境下机动群目标跟踪的新算法—基于交互式多模型的编队群目标跟踪算法(IMM-FGT).计算机仿真结果表明,IMM-FGT算法是解决机动群目标跟踪问题的一种有效的方法.     

机器人编队方法解析

随着计算机技术及网络技术的不断发展,机器人学成为专家学者研究的热题。而机器人编队控制是机器人协调合作的基础问题。目前,机器人编队的控制方法主要有行为法、人工势场法、人工协调场法、领航-跟随法和虚拟结构法等。而这些方法往往在进行机器人编队控制过程中,不能独立使用,主要原因是各种方法在使用的时候都存在了缺点,当几种方法结合使用时,无论从稳定性、鲁棒性上都有所提高,可以达到更好的编队效果。本文将对几种常见的编队方法的优缺点加以解析。     

一种基于跟随领航法的多机器人的编队及避障控制方法

主要针对未知环境下多移动机器人的编队及避障问题,设计了基于跟随领航的编队及避障控制算法,使多机器人能保持一定的编队队形且无碰撞,并能使机器人在未知的局部障碍环境下也能够安全躲避障碍物,在通过障碍物之后依然能恢复之前的编队队形。对多机器人系统设计并进行仿真实验,实验结果表明,该方法对于实现多移动机器人的编队和避障控制具有良好的效果。     

基于邻近项目的Slope One协同过滤算法

协同过滤是个性化推荐系统中的常用技术,数据稀疏性是影响协同过滤算法预测准确度的主要因素。提出了改进的Slope One算法,在该算法中,首先根据用户历史评分计算项目间相似性,然后依据项目相似性选取当前活跃用户评价过的k个相似项目记为邻近项目集合,并计算目标项目与其邻近项目的评分偏差,最后以项目间相似性为权重,计算当前活跃用户对目标项目的评分预测值。该算法使用邻近项目进行计算,降低数据的稀疏性,同时减少了计算量。使用标准MovieLens数据集对该算法的预测结果进行验证,结果表明：相对于原算法,该算法提高了预测的准确性,与其他协同过滤算法相比,推荐准确度也有明显的提高。     

A quantitative and comparative analysis of endmember extraction algorithms from hyperspectral data

Linear spectral unmixing is a commonly accepted approach to mixed-pixel classification in hyperspectral imagery. This approach involves two steps. First, to find spectrally unique signatures of pure ground components, usually known as endmembers, and, second, to express mixed pixels as linear combinations of endmember materials. Over the past years, several algorithms have been developed for autonomous and supervised endmember extraction from hyperspectral data. Due to a lack of commonly accepted data and quantitative approaches to substantiate new algorithms, available methods have not been rigorously compared by using a unified scheme. In this paper, we present a comparative study of standard endmember extraction algorithms using a custom-designed quantitative and comparative framework that involves both the spectral and spatial information. The algorithms considered in this study represent substantially different design choices. A database formed by simulated and real hyperspectral data collected by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) is used to investigate the impact of noise, mixture complexity, and use of radiance/reflectance data on algorithm performance. The results obtained indicate that endmember selection and subsequent mixed-pixel interpretation by a linear mixture model are more successful when methods combining spatial and spectral information are applied.     

FPGA实现的视频图像缩放显示

对几种常用的图像缩放算法进行了比较,在权衡了算法复杂度、缩放效果和FPGA逻辑资源等3大因素后,选择了双线性插值算法来实现图像缩放。重点介绍了双线性插值算法和该方法的FPGA硬件实现方法,包括图像数据缓冲单元、插值系数生成单元以及插值计算单元等。应用结果表明,双线性插值算法及其硬件实现模块达到了预期的效果。     

Per-user checkpointing for mobility database failure restoration

This paper studies the failure restoration of mobility database for Universal Mobile Telecommunications System (UMTS). We consider a per-user checkpointing approach for the home location register (HLR) database. In this approach, individual HLR records are saved into a backup database from time to time. When a failure occurs, the backup record is restored back to the mobility database. We first describe a commonly used basic checkpoint algorithm. Then, we propose a new checkpoint algorithm. An analytic model is developed to compare these two algorithms in terms of the checkpoint cost and the probability that an HLR backup record is obsolete. This analytic model is validated against simulation experiments. Numerical examples indicate that our new algorithm may significantly outperform the basic algorithm in terms of both performance measures.     

基于改进混合遗传算法的信道分配研究

用遗传与模拟退火相结合的混合算法对信道分配问题进行研究,并通过加入"寻优式爬山"与大规模基因突变两种优化方法对混合算法进行改进,克服了一般遗传算法收敛速度慢以及易于陷入局部最优解的缺点。给出了算法的实现流程,并针对几个典型信道分配问题对一般遗传算法、遗传与退火混合算法、改进后的混合算法进行仿真。仿真结果证明改进算法较其他2种算法至少节省80%的时间,并具有更好的稳定性,是解决信道分配问题的一种很好的算法。     

红外探测系统线性小目标检测算法研究

通过对红外探测系统成像过程及特点的详细分析,提出了快速线性特征检测算法以及线性目标矩形特征检测算法,用于线性小目标的检测,并给出了算法流程和实验结果.该算法作为辅助算法应用到了低空红外探测系统中,取得了良好的效果.     

Distributed collaborative key agreement and authentication protocols for dynamic peer Groups

We consider several distributed collaborative key agreement and authentication protocols for dynamic peer groups. There are several important characteristics which make this problem different from traditional secure group communication. They are: 1) distributed nature in which there is no centralized key server; 2) collaborative nature in which the group key is contributory (i.e., each group member will collaboratively contribute its part to the global group key); and 3) dynamic nature in which existing members may leave the group while new members may join. Instead of performing individual rekeying operations, i.e., recomputing the group key after every join or leave request, we discuss an interval-based approach of rekeying. We consider three interval-based distributed rekeying algorithms, or interval-based algorithms for short, for updating the group key: 1) the Rebuild algorithm; 2) the Batch algorithm; and 3) the Queue-batch algorithm. Performance of these three interval-based algorithms under different settings, such as different join and leave probabilities,is analyzed. We show that the interval-based algorithms significantly outperform the individual rekeying approach and that the Queue-batch algorithm performs the best among the three interval-based algorithms. More importantly, the Queue-batch algorithm can substantially reduce the computation and communication workload in a highly dynamic environment. We further enhance the interval-based algorithms in two aspects: authentication and implementation. Authentication focuses on the security improvement, while implementation realizes the interval-based algorithms in real network settings. Our work provides a fundamental understanding about establishing a group key via a distributed and collaborative approach for a dynamic peer group.     

An Integrated Approach for Achieving Multirobot Task Formations

In this paper, a problem, called the initial formation problem, within the multirobot task allocation domain is addressed. This problem consists in deciding which robot should go to each of the positions of the formation in order to minimize an objective. Two different distributed algorithms that solve this problem are explained. The second algorithm presents a novel approach that uses cost means to model the cost distribution and improves the performance of the task allocation algorithm. Also, we present an approach that integrates distributed task allocation algorithms with a behavior-based architecture to control formations of robot teams. Finally, simulations and real experiments are used to analyze the formation behavior and provide performance metrics associated with implementation in realistic scenarios.     

Robust object tracking based on adaptive templates matching via the fusion of multiple features

Moving object tracking under complex scenes remains to be a challenging problem because the appearance of a target object can be drastically changed due to several factors, such as occlusions, illumination, pose, scale change and deformation. This study proposes an adaptive multi–feature fusion strategy, in which the target appearance is modeled based on timed motion history image with HSV color histogram features and edge orientation histogram features. The variances based on the similarities between the candidate patches and the target templates are used for adaptively adjusting the weight of each feature. Double templates matching, including online and offline template matching, is adopted to locate the target object in the next frame. Experimental evaluations on challenging sequences demonstrate the accuracy and robustness of the proposed algorithm in comparison with several state-of-the-art algorithms.