认知无线电网络中基于检测概率的主用户定位算法

为了解决认知无线电网络中次用户对主用户进行定位的问题,提出了一种加权最小二乘的迭代定位算法。采用两状态马尔可夫模型作为主用户头像模型,能量检测作为次用户的感知模型。该算法可以在不干扰主用户正常工作的情况下,利用次用户之间的合作感知结果进行定位,并估计出主用户的三维地理位置位置信息。提出了一种可以降低定位算法复杂度的简化算法。通过对定位问题进行了理论分析,求出了均方误差的Cramer-Rao理论下界。仿真结果表明,算法的均方误差非常接近理论下界,能有效地估计主用户的三维位置信息,提高定位精度。     

基于点线特征融合的视觉惯性SLAM算法

针对目前视觉SLAM方法鲁棒性差、耗时高,使系统定位不够精确的问题,提出了一种基于点线特征融合的视觉惯性SLAM算法。首先通过短线剔除和近似线段合并策略改进LSD（line segment detection）提取质量,以提高线特征检测的速率和准确度;然后在后端优化中有效融合了点、线和IMU数据,建立最小化目标函数进行优化,得到更精确的相机位姿;最后在EuRoC数据集和现实走廊场景进行了实验验证。实验表明,所提算法可以有效提升线特征提取的质量和速度,同时有效提高了SLAM系统的定位精度,获得更为丰富的点线结构地图。     

基于IMU与激光雷达紧耦合的混合匹配算法

针对线、面特征匹配的激光雷达测距与地图构建算法(Lightweight and Ground-Optimized Lidar Odometry And Mapping,LeGO-LOAM)在自动导引运输车(Automated Guided Vehicle,AGV)室内室外实时建图与定位时,易出现激光里程计累积误差大和旋转估计不准确等问题,本工作采用惯性测量单元(Inertial Measurement Unit,IMU)与激光雷达紧耦合的LeGO-LOAM算法,通过IMU为激光雷达提供的初始位姿信息,构建IMU与激光雷达联合误差函数,实现位姿共同迭代优化.其中,对于室外结构化信息较少时,在点对点的迭代最近点算法(Iterative Closest Point,ICP)较高定位精度的基础上,结合LeGO-LOAM算法和ICP算法互补性,进一步提出基于IMU与激光雷达紧耦合的混合匹配算法:当环境中结构信息较多时,激光里程计采用LeGO-LOAM算法,而当环境中结构化信息较少时采用ICP算法.实验结果表明,基于IMU与激光雷达紧耦合的混合匹配算法可有效降低激光里程计相对位姿误差和累积误差,提高AGV小车定位精度以消除部分地图重影.     

What localizes beneath: A metric multisensor localization and mapping system for autonomous underground mining vehicles

Robustly and accurately localizing vehicles in underground mines is particularly challenging due to the unavailability of GPS, variable and often poor lighting conditions, visual aliasing in long tunnels, and airborne dust and water. In this paper, we present a novel, infrastructure‐less, multisensor localization method for robust autonomous operation within underground mines. The proposed method integrates with existing mine site commissioning and operation procedures and includes both an offline map‐building process and an online localization algorithm. The approach combines the strengths of visual‐based place recognition, LIDAR‐based localization, and odometry in a particle filter fusion process. We provide an extensive experimental validation using new large data sets acquired in two operational Australian underground hard‐rock mines (including a 600m‐deep multilevel mine with approximately 33 km of mapping data and 7 km of vehicle localization) by actual mining vehicles during production operations. We demonstrate a significant increase in localization accuracy over prior state‐of‐the‐art SLAM research systems and real‐time operation, with processing times in the order of 10 Hz. We present results showing a mean error of 0.68 m from the Queensland Mine data set and 1.32 m from the New South Wales Mine data set and at least 86% reduction in error compared with prior state of the art. We also analyze the impact of the particle filter parameters with respect to localization accuracy. Together this study represents a new approach to positioning systems for currently deployed autonomous vehicles within underground mine environments.     

网络中多节点故障定位的探测路径选择算法

针对现有故障定位技术不能满足多节点故障定位的要求,尤其当网络中存在大量故障节点时,提出了一种基于主动探测的探测路径选择算法。该算法主要包括用于故障检测的贪婪路径选择算法和用于故障定位的禁忌链路搜索算法。在故障检测阶段,使用贪婪路径选择算法迭代地选择具有最小权重的探测路径覆盖网络中的节点。在故障定位阶段,使用禁忌链路搜索算法多次生成候选路径集以选择最合适的探测路径来解决多节点故障定位问题。在随机网络拓扑和真实网络拓扑上的仿真结果表明,与现有的节点故障定位算法相比,探测路径选择算法具有更高的成功定位率和更低的探测成本。     

Multi-Dimensional Pedestrian System on the New Campus of University of Macau

The Multi-dimensional Pedestrian System( MPS) is an integral part of the new campus of University of Macau. It observes the principle of "pedestrian first " and features a pedestrian-vehicle dividing system.Based on a comprehensive analysis of the location,climate,ecology and other factors of the project site,the conception of the idea of MPS and the related researches are illustrated. The transportation features of the MPS,as summarized,include multi-dimensions,short-distance and weather-resistance. Its features for the sake of livability include integration of nature, respect for the environment and sharing of landscape. Upon the completion of the project, the effects on its users were tested. Finally, some constructive rules for the construction of similar campus pedestrian systems were proposed.     

基于传声器阵列的机器人声源定位系统

随着计算机技术和信号处理技术的发展,各种具有特殊功能的机器人应用到人们的生产生活中。听觉系统可以弥补机器人视觉系统存在的不足,使机器人在黑暗或有障碍物遮挡的环境中,利用声音信息感知环境中存在的目标,并对其定位,辅助机器人工作,尤其在灾难现场搜救、军事等领域,声源定位系统具有独特的优势。针对机器人声源定位系统进行研究,设计了基于传声器阵列的机器人声源定位系统,采用平面四元传声阵列,利用广义互相关算法,实现对声源的定位,具有较高的实用价值。     

对一类代理盲签名的攻击与改进

为了解决XUE-CAO代理盲签名方案的可伪造性问题,首先对XUE-CAO方案进行了安全性分析,在此基础上,提出一种改进的抗伪造攻击的代理盲签名方案。新方案克服了原方案中两处设计缺陷,防止了广泛伪造和原始签名者的伪造攻击,而且还保留了原方案的可验证性、强不可否认性、强可注销性和不可连接性等安全特性,从而可以用于构造安全的代理盲签名系统。     

Analytical and experimental study of shear localization in chip formation in orthogonal machining

A simplified theory of instability of plastic flow is applied to analyze the formation of shear localized chips in orthogonal machining. A flow localization parameter is expressed in terms of associated cutting conditions and properties of the workpiece material. The analysis, which indicates the important parameters in the cutting process, is used to investigate the effect of cutting conditions on the onset of shear localization and the formation of adiabatic shear banding in metal cutting. Comparisons are made between the analysis and experiments in which the flow localization parameter is obtained for several workpiece materials. The results of this investigation seem to support the analysis and its potential benefits in analyzing and/or remedying problems associated with chip formation and temperature generated in metal cutting. Presently at Advanced Technology Center, Valenite, Inc., Madison Heights,MI 48071, USA     

巧编数控电火花加工的定位程序

阐述了模具电火花加工的定位工艺方法，通过巧妙编程实现了模具数控电火花加工的定位．对灵活使用数控电火花加工机床具有实用的参考价值。