Use of non-linear localization for isolating structures from earthquake-induced motions

The dynamic response due to earthquake-induced excitations of multi-storey buildings simulated by a cantilever (with attached concentrated masses) supported on a flexible foundation, is reconsidered when stiffness non-linearities are included. To this end, a suitable non-linear spring-mass device is placed between the ground and the mass of the foundation, which under certain conditions can absorb a significant amount of seismic energy over a large frequency range, thus drastically reducing the seismic response of the foundation. This is achieved by the stiffness non-linearity that gives rise to a localization phenomenon, according to which motions generated by external disturbances remain passively localized close to the point of seismic excitation instead of ‘spreading’ to the entire structure. The implications of these findings to the design of earthquake-resistant structures are discusssed. Copyright © 1999 John Wiley & Sons, Ltd.     

基于SUT-EKF的DGPS/DR 组合定位算法

针对基于DGPS/DR的移动机器人组合定位问题,采用一种尺度无迹变换扩展卡尔曼滤波(SUT-EKF)算法,由于组合定位系统中的状态方程是非线性的,并且观测方程是线性的特点,将SUT预测移动机器人位姿,利用EKF融合最新观测值更新机器人位姿,该算法在状态预测阶段避免了计算Jacobian矩阵,从而有效地减小了线性化对非线性系统误差的影响。仿真结果表明,该算法具有较好的滤波精度和稳定性,为实现DGPS/DR组合定位系统提供了一种有效可靠的途径。     

全球化下的“生产消费者”——分布式生产系统研究评述

经济全球化背景下,日益精细的劳动分工和跨地域生产协作带来生产片段化和地方专业化集聚。这种生产模式加剧了生产与消费的割裂,并将消费主义作为驱动生产不断扩大的途径。近年来,基于智能电网、可再生能源、3D打印等新兴技术的应用,生产与消费活动紧密联系的分布式生产模式受到可持续发展领域的关注,其中分布式可再生能源的利用和推广成为最主要的驱动力。论文以“生产消费者(Prosumer)”这一概念为切入点,从地理条件、技术基础、市场协作关系和可持续性表现4个方面,探讨分布式生产系统中生产与消费关系的重构。结论指出：以分布式生产为特征的“产消一体”生产模式并非是一种全球化脱钩策略,而是在开放条件下,生产与消费更紧密联系的地方化过程,这种生产模式转型有可能为更多样化的可持续发展实践开辟空间,值得进一步开展以行动为导向的扎根研究和区域比较分析。     

特征法视觉SLAM逆深度滤波的三维重建

针对现有特征法视觉SLAM只能重建稀疏点云、非关键帧对地图点深度估计无贡献等问题,本文提出一种特征法视觉SLAM逆深度滤波的三维重建方法,可利用视频序列影像实时、增量式地构建相对稠密的场景结构.具体来说,设计了一种基于运动模型的关键帧追踪流程,能够提供精确的相对位姿关系;采用一种基于概率分布的逆深度滤波器,地图点通过多帧信息累积、更新得到,而不再由两帧三角化直接获取;提出一种基于特征法与直接法的后端混合优化框架,以及基于平差约束的地图点筛选策略,可以准确、高效解算相机位姿与场景结构.试验结果表明,与现有方法相比,本文方法具有更高的计算效率和位姿估计精度,而且能够重建出全局一致的较稠密点云地图.     

不确定海洋环境中基于贝叶斯理论的多声源定位算法

环境参数失配导致定位性能大幅度下降是匹配场定位所面临的难题之一。应用贝叶斯理论对环境聚焦,是当前解决该难题的研究热点。环境聚焦方法的实质是将未知环境参数和声源位置联合优化估计,当出现多个目标时,估计的参数会随着声源个数成倍增加,因此不得不利用有限的观测信息来实现众多参数的估计。本文采用最大似然比方法,获得信号源谱和误差项的最大似然估计,实现这些敏感性较弱参数的间接反演,有效降低了反演参数维数和定位算法复杂度。针对遗传算法的早熟和稳定性差的问题,改进了似然函数的经验表达式。将多维后验概率密度在参数起伏变化范围内积分,得到反演参数的一维边缘概率分布,求解最优值的同时进行反演结果的不确定性分析。本文仿真了位于相同距离、不同深度的两个声源,使用仿真实验验证了提出算法的有效性。     

An approach to evaluate ground surface rupture caused by reverse fault movement

An approach for estimating ground surface rupture caused by strong earthquakes is presented in this paper, where the finite element （FE） method of continuous and discontinuous coalescent displacement fields is adopted. The onset condition of strain localization is introduced to detect the formation of the slippage line. In the analysis, the Drucker-Prager constitutive model is used for soils and the rate- and state-dependent friction law is used on the slippage line to simulate the evolution of the sliding. A simple application to evaluate the ground surface rupture induced by a reverse fault movement is provided, and the numerical simulation shows good agreement with failure characteristics observed in the field after strong earthquakes.     

Camera localization for augmented reality and indoor positioning: a vision-based 3D feature database approach

ABSTRACT

The recent fast development in computer vision and mobile sensor technology such as mobile LiDAR and RGB-D cameras is pushing the boundary of the technology to suit the need of real-life applications in the fields of Augmented Reality (AR), robotics, indoor GIS and self-driving. Camera localization is often a key and enabling technology among these applications. In this paper, we developed a novel camera localization workflow based on a highly accurate 3D prior map optimized by our RGB-D SLAM method in conjunction with a deep learning routine trained using consecutive video frames labeled with high precision camera pose. Furthermore, an AR registration method tightly coupled with a game engine is proposed, which incorporates the proposed localization algorithm and aligns the real Kinetic camera with a virtual camera of the game engine to facilitate AR application development in an integrated manner. The experimental results show that the localization accuracy can achieve an average error of 35?cm based on a fine-tuned prior 3D feature database at 3?cm accuracy compared against the ground-truth 3D LiDAR map. The influence of the localization accuracy on the visual effect of AR overlay is also demonstrated and the alignment of the real and virtual camera streamlines the implementation of AR fire emergency response demo in a Virtual Geographic Environment.     

深海季节性环境变化对半会聚区尺度水面声定位影响分析

针对深海声定位受海洋环境变化影响明显、需考虑测量系统的环境适应性和宽容性设计问题,提出一种评估海水环境变化对定位性能影响的仿真分析方法,将声场计算、误差传播与交会解算联合建模,以西太平洋中纬度海域夏季和冬季环境为代表性场景讨论了季节性环境变化对定位性能的影响方式和影响程度。仿真结果表明,当接收器位于海洋近表层时,在夏季和冬季呈现出两种不同的声信道样式,夏季季节性温跃层影响下的定位精度较差,冬季表面波导影响下的定位精度相对较好,两者均方根误差(RMSE)相差超过50 m;当接收器位于海洋中上层时,直达波有效作用范围的季节性变化引起定位性能差异,冬季定位精度优于夏季,两者RMSE相差15～20 m;当接收器位于海洋近底层时,利用可靠声路径定位精度较高,定位性能季节性变化不明显。研究认为,海水的季节性环境变化能够改变半会聚区尺度水面声定位的声信道特性以及到达声信息、误差传播、交会求解等测量因素,进而对接收深度位于海洋上层的声定位性能产生明显影响。