Automatic UAV Positioning with Encoded Sign as Cooperative Target

In order to achieve the goal that unmanned aerial vehicle(UAV)automatically positioning during power inspection,a visual positioning method which utilizes encoded sign as cooperative target is proposed.Firstly,we discuss how to design the encoded sign and propose a robust decoding algorithm based on contour.Secondly,the Adaboost algorithm is used to train a classifier which can detect the encoded sign from image.Lastly,the position of UAV can be calculated by using the projective relation between the object points and their corresponding image points.Experiment includes two parts.First,simulated video data is used to verify the feasibility of the proposed method,and the results show that the average absolute error in each direction is below 0.02 m.Second,a video,acquired from an actual UAV flight,is used to calculate the position of UAV.The results show that the calculated trajectory is consistent with the actual flight path.The method runs at a speed of 0.153 sper frame.

Function of Cooperative Learning in Developing Positive Affect

This paper focus on the function of cooperative learning in developing positive affect,Including reducing anxiety,increasing motivation,facilitating the development of positive attitudes toward learning and language learning,promoting self-esteem,as well as supporting different learning styles and encouraging perseverance in the difficult and confusing process of learning a foreign language.

Improved GNSS Cooperation Positioning Algorithm for Indoor Localization

For situations such as indoor and underground parking lots in which satellite signals are obstructed,GNSS cooperative positioning can be used to achieve highprecision positioning with the assistance of cooperative nodes.Here we study the cooperative positioning of two static nodes,node 1 is placed on the roof of the building and the satellite observation is ideal,node 2 is placed on the indoor windowsill where the occlusion situation is more serious,we mainly study how to locate node 2 with the assistance of node 1.Firstly,the two cooperative nodes are located with pseudo-range single point positioning,and the positioning performance of cooperative node is analyzed,therefore the information of pseudo-range and position of node 1 is obtained.Secondly,the distance between cooperative nodes is obtained by using the baseline method with double-difference carrier phase.Finally,the cooperative location algorithms are studied.The Extended Kalman Filtering(EKF),Unscented Kalman Filtering(UKF)and Particle Filtering(PF)are used to fuse the pseudo-range,ranging information and location information respectively.Due to the mutual influences among the cooperative nodes in cooperative positioning,the EKF,UKF and PF algorithms are improved by resetting the error covariance matrix of the cooperative nodes at each update time.Experimental results show that after being improved,the influence between the cooperative nodes becomes smaller,and the positioning performance of the nodes is better than before.

A whole-net cooperative positioning method based on CDGNSS and inter-vehicle ranging

Relative positioning is recognized as an important issue for vehicles in urban environments.Multi-vehicle Cooperative Positioning(CP)techniques which fuse the Global Navigation Satellite System(GNSS)and inter-vehicle ranging have attracted attention in improving the performance of baseline estimation between vehicles.However,current CP methods estimate the baselines separately and ignore the interactions among the positioning information of different baselines.These interactions are called’information coupling’.In this work,we propose a new multivehicle precise CP framework using the coupled information in the network based on the Carrier Differential GNSS(CDGNSS)and inter-vehicle ranging.We demonstrate the benefit of the coupled information by deriving the Cramer-Rao Lower Bound(CRLB)of the float estimation in CP.To fully use this coupled information,we propose a Whole-Net CP(WN-CP)method which consists of the Whole-Net Extended Kalman Filter(WN-EKF)as the float estimation filter,and the Partial Baseline Fixing(PBF)as the ambiguity resolution part.The WN-EKF fuses the measurements of all baselines simultaneously to improve the performance of float estimation,and the PBF strategy fixes the ambiguities of the one baseline to be estimated,instead of full ambiguity resolution,to reduce the computation load of ambiguity resolution.Field tests involving four vehicles were conducted in urban environments.The results show that the proposed WN-CP method can achieve better performance and meanwhile maintain a low computation load compared to the existing methods.

Robot Position Control Using Force Information for Cooperative Work in Remote Robot Systems with Force Feedback

This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface device while observing work of the robot with a video camera. We also investigate the effect of the proposed control by experiment. As cooperative work, we deal with work in which two robots carry an object together. The robot position control using force information finely adjusts the position of the robot arm to reduce the force applied to the object. Thus, the purpose of the control is to avoid large force so that the object is not broken. In our experiment, we make a comparison among the following three cases in order to clarify how to carry out the control effectively. In the first case, the two robots are operated manually by a user with his/her both hands. In the second case, one robot is operated manually by a user, and the other robot is moved automatically under the proposed control. In the last case, the object is carried directly by a human instead of the robot which is operated by the user in the second case. As a result, experimental results demonstrate that the control can help each system operated manually by the user to carry the object smoothly.

Cooperative localization against GPS signal loss in multiple UAVs flight

Based on multiple unmanned aerial vehicles（UAVs） flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system（GPS） signal loss due to GPS receiver malfunction is proposed.Contrast to the traditional means with single UAV,the proposed method is based on the use of inter-UAV relative range measurements against GPS signal loss and more suitable for the small-size and low-cost UAV applications.Firstly,for re-localizing an UAV with a malfunction in its GPS receiver,an algorithm which makes use of any other three healthy UAVs in the cooperative flight as the reference points for re-localization is proposed.Secondly,by using the relative ranges from the faulty UAV to the other three UAVs,its horizontal location can be determined after the GPS signal is lost.In order to improve an accuracy of the localization,a Kalman filter is further exploited to provide the estimated location of the UAV with the GPS signal loss.The Kalman filter calculates the variance of observations in terms of horizontal dilution of positioning（HDOP） automatically.Then,during each discrete computing time step,the best reference points are selected adaptively by minimizing the HDOP.Finally,two simulation examples in Matlab/Simulink environment with five UAVs in cooperative flight are shown to evaluate the effectiveness of the proposed method.

Global asymptotic stability of positive equilibrium in a 3-species cooperating model with time delay

The asymptotic behavior of the time-dependent solution for a 3-species cooperating model was investigated with the effects of both diffusion and time delay taken into consideration. We proved the global asymptotic stability of a positive steady-state solution to the model problem by using coupled upper and lower solutions for a more general reaction-diffusion system that gives a common framework for 3-species cooperating model problems. The result of global asymptotic stability implies that the model system coexistence is permanent. Some global asymptotic stability results for 2-species cooperating reaction-diffusion systems are included in the discussion, and some known results are extended.

基于车路协同技术的超高速公路虚拟轨道系统研究

为保障超高速公路行车安全,论证虚拟轨道系统在超高速公路上应用的可行性,以车路协同技术为基础,搭建了超高速公路虚拟轨道系统模型。通过建立实时车辆动态坐标系,结合车辆偏离安全区域,计算出车辆横向偏转角度阈值;利用定位系统和路侧单元检测系统,研究了微波测距模块采样频率和安装间距随车速变化的情况。结果表明:在虚拟轨道单侧安全区域为10 cm时,小型两厢车、小型三厢车、中型车、中大型车、大型车车辆横向偏转的最大安全角度范围分别是1.43°~1.59°、1.30°~1.40°、1.22°~1.33°、1.17°~1.25°、1.10°~1.20°;当车辆行驶速度为180 km/h时,路侧单元传感器的采样频率高于27.72 Hz,传感器的安装距离小于6.87 m时可满足要求。

基于多元融合的企业技术创新合作预测方法研究

合理的技术创新合作预测方法是企业寻找合适的技术创新合作伙伴以提升技术创新绩效的有效手段。论文基于企业专利数据,构建专利所有权人共现网络,应用Katz指标计算企业之间的路径相似性,应用TF-IDF算法构建企业关键词向量,结合余弦相似性计算企业之间的内容相似性,应用社会网络分析方法中的中心性指标计算企业的位置相似性,将三者进一步融合得到企业之间合作的潜在可能性。通过对石墨烯领域企业专利数据分析预测企业间合作的可能性,证实该方法有效,AUC指标值为0.7242,优于单一指标相似性推荐方法,能够提升合作推荐中合适匹配的精确度。

超网络中心性度量的υ-Position值方法

利用合作博弈理论的分配规则如Shapley值、Banzhaf值等来度量政治、经济和社会网络中节点的中心性或者重要性是识别网络中关键节点的一类重要方法。考虑到在超网络中代表各类组织的超边在网络中发挥的作用不同,本文研究了超网络博弈上一类广义Position值的分配规则,被称为υ-position值。它可以作为网络中度值测度的一类推广,以此来度量网络中参与者的中心性和相对重要性。其次,证明了超网络结构上类Shapley-position值可由分支超边指数和局部平衡超边贡献两个性质所唯一刻画。最后,举例分析了υ-position值在超网络中心性测度中的应用。

非合作线谱声源分布式定位方法

非合作目标定位是水声定位领域的研究热点。为充分挖掘并利用各类可观测参数,提高非合作目标定位能力,提出一种基于目标频率变化信息的非合作目标定位方法。该方法针对匀速直线运动目标的定位问题,首先根据多普勒频移原理,建立观测频率与目标辐射频率、目标运动速度、位置之间的函数映射关系,利用最小均方准则建立目标函数,通过优化算法估计分布式定位系统中各个测量单元与目标运动轨迹的致近点距离,最后综合各观测节点的测距结果,构建几何定位模型,求得目标运动轨迹的解析解。通过仿真分析,证明了该方法的有效性,并指出了该方法需要目标通过与各测量单元的致近点才能获得较好的距离估计能力。文中分析了不同频率估计精度对定位精度的影响,结果表明,提出的定位方法对测频精度具有一定的容限,是一种高精度的非合作线谱声源定位方法。

非合作式双基地雷达系统设计与验证

非合作双基地雷达在目标探测的安全稳健等方面展现了优越的性能。本文首先从双基地雷达同步这一关键问题出发,分析合作和非合作双基地雷达的差异,推导非合作双基地雷达目标定位原理。进一步设计非合作双基地雷达系统,解决时空同步问题,提取直达波和目标散射波的特征参数,解析两者路径差、接收方位、俯仰等信息,最终求解目标接收距离,实现目标定位。雷达协同探测试验采用实测数据验证了非合作双基地技术体制的可行性,为目标探测定位提供了有效的方法。

基于5G信号异步时钟误差补偿的多无人机协同定位方法

5G信号可为多无人机(UAV)提供精确的相对测距/测角信息,进而提升其在卫星接收机故障时的协同定位精度。然而,协同网络中各节点的5G通讯时钟往往是异步的,这会对测距/测角信息的精度产生较大影响,进而降低融合性能。针对上述问题,提出了一种基于5G信号异步时钟误差补偿的多无人机协同定位方法。首先,构建了基于5G信号异步时钟误差的相对测距模型,并利用相对测距/测角信息以及高度计信息建立了从机的位置观测方程。在此基础上,通过设计迭代扩展卡尔曼滤波器(IEKF)实现了对从机惯导系统(INS)误差以及异步时钟误差的联合最优估计,提高了从机定位精度。仿真结果表明,相比于传统方法,所提方法将从机的水平定位精度提高了25.3%。

基于SpringMVC的农机具服务系统设计与实现

针对农机合作社等农机服务单位在农机管理中面临的工作效率低、信息不透明及维修保养难等问题,结合SpringMVC框架、JSP页面交互技术和持久层MyBatis框架,设计了Biz数据接口层、BizImplements业务层、Controller控制层和View视图层4层结构保证高内聚低耦合特性,并开发了农机具信息、库存管理、行驶轨迹、用户信息、维修管理和补贴政策等模块。这些模块旨在全面优化农机具管理,提升维修效率,获取政策信息,从而有效解决当前存在的问题,推动农机服务的高效运作,为农业生产提供有力支持。

顾及通信延迟的车路协同高精度定位

近几年,随着智能交通和通信技术的发展,智能车路协同系统引起了广泛的关注。车辆的位置特征是智能交通中的基本元素。车路协同环境下,车辆可通过通信设备接收路侧端的定位信息进行自车定位。本文旨在解决车路协同环境中不稳定的通信延迟带来的定位误差的问题,提出了一种基于因子图的考虑通信延迟的车辆高精度定位模型。在GNSS的情况下,基于路侧激光雷达点云LiDAR聚类方法识别和定位目标车辆,通过4G通信网络将目标定位结果发送至车辆,采用因子图将当前时刻的车载惯性测量单元IMU测量信息与滞后的路侧目标定位结果直接融合,基于增量平滑推理方法,实现车辆位置、速度和姿态的最优估计。最后,结合实测和仿真数据,利用实车试验验证了本文方法,与传统处理时间延迟的外推法对比分析,结果表明本文方法可提高车辆的定位和测速精度,并消除了高度不稳定的通信延迟对定位的影响。

具有超图合作结构的赋权Position值

具有超图交流结构的可转移效用合作对策,也称为超图对策,它由一个三元组(N,v,H)所组成,其中(N,H)是一个可转移效用对策(简称TU-对策),而(N,H)是一个超图(超网络)。在超图对策中,除Myerson值(Myerson)外,Position值(Meessen)是另一个重要的分配规则。该模型要求把超图结构中每条超边Shapley的值平均分配给它所包含的点,而不考虑每个点的交流能力或合作水平。本文引入超图结构中点的度值来度量每条超边中每个点的交流能力或合作水平,并结合Haeringer提出用于推广Shapley值的权重系统,并由此定义了具有超图合作结构的赋权Position值。我们证明了具有超图合作结构的赋权Position值可以由“分支有效性”、“冗余超边性”、“超边可分解性”、“拟可加性”、“弱积极性”和“弱能转换”六个性质所唯一确定,并且发现参与者获得的支付随其度值的增加而增加,参与者分摊的成本随其度值的增加而降低。

基于关节双位置反馈的柔性协作机械臂零力控制

零力控制是协作机械臂实现拖动示教的核心问题之一,目前方法多依赖于附加力/力矩传感器,其虽能保证测量精度,但会增加系统复杂程度及成本。提出一种基于关节双位置反馈的柔性协作机械臂零力控制方法,该方法可在无外加传感器条件下实现机械臂零力控制。首先,基于波发生器与柔轮柔性特性,建立了谐波传动关节的动力学模型;其次,基于谐波传动关节刚度辨识方法,建立了基于双位置反馈的柔性关节力矩估测方法;再次,建立了简化重力矩补偿模型,并考虑关节转动过程中的粘滞摩擦和Stribeck库伦摩擦,完善了关节摩擦力矩模型,基于此,实现对关节重力矩和摩擦力矩补偿,实现机械臂零力控制;最后,搭建谐波传动一体化关节和机械臂样机平台,并进行了实验研究,结果表明,所提方法可有效实现无附加力/力矩传感器条件下的谐波传动机械臂零力控制。

双缓动平台时延下的纯方位定位测角误差分析

水下双缓动平台协同探测可实现对水声目标纯方位定位和跟踪。针对双探测平台接收目标信号因传播时延导致探测时间未配准、方位测量偏差的问题,根据缓动平台的实际应用场景,建立目标运动模型和二维探测空间几何分布,构建一种基于不同时延条件的方位测量误差分析模型,并详细分析得出目标和双平台不同分布场景下的最大测角误差结果,该模型物理意义明确、直观简单,仿真和实测实验结果验证测角误差模型的准确性,并得出双平台探测时延下目标方位测角的误差分布规律。