Bayes理论在机器人信息融合中的应用

移动机器人的自动能力中实时避障和导航是一个很关键的技术,研究的主要问题是：机器人在运动时需要充分的环境信息,而且处理这些信息的速度要快,同时也要满足实时性的要求。文章介绍了将Bayes经典推理理论应用于机器人对未知环境的探索、感知过程,确定了具体的实验方案和实现步骤,完成了一个简化的仿真算例,并通过仿真结果对该方法的有效性和性能进行了验证和评估。     

城市街区空间引导系统的设计思考

城市街区空间引导系统与人们的日常生活息息相关,为人们的出行提供了便捷的标识引导,同时它也是城市形象的重要组成部分之一。本文分析总结了该系统的设计原则,并从视觉传达学科入手分析其视觉元素的设计。为了设计无语言障碍和有个性、地域化的城市街区空间引导系统,从符号、文字、色彩三方面对其进行设计思考。     

D-S证据理论在移动机器人信息融合中的应用

移动机器人的自动能力中实时避障和导航是一个很关键的技术,研究中主要的问题是：机器人在运动时需要充分的环境信息,而且处理这些信息的速度要快,同时也要满足实时性的要求。详细介绍了将D-S证据理论应用于移动机器人对未知环境的探索、感知过程,并通过仿真结果对D-S证据融合方法的性能进行研究与改进,确定了D-S证据融合方案的具体实现步骤,并完成了一个简化的仿真算例,得出了相关结论。     

一种序贯Unscented卡尔曼滤波在微小型无人直升机导航系统中的应用

对于应用到微小型无人直升机上的低成本捷联惯导（SINS）/GPS组合导航系统来说,SINS Ψ角误差模型在描述低精度惯性器件误差时对误差项的忽略,使其无法满足SINS误差估计的要求.为了克服Ψ角误差模型的不足,本文建立了基于四元数的SINS非线性误差模型.该误差模型无需对失准角进行小角度假设.为了对组合导航系统中的SINS误差进行估计,提出一种序贯Unscented卡尔曼滤波方法.该滤波方法对观测向量进行序贯处理以降低算法的计算量.仿真结果表明,该滤波方法能有效提高低成本SINS/GPS组合导航系统的性能.     

微机械陀螺在组合导航系统中的应用

介绍了基于iMEMS技术的速率陀螺芯片ADXRS300,研究了以ARM处理器为核心的GPS/SINS组合导航系统的结构及其各部分功能,给出了基于角速度测量、加速度测量和GPS定位的组合导航系统设计方案。     

The Rayleigh-Taylor instability in the spherical pinch

The spherical pinch (SP) concept is an outgrowth of the inertial confinement model (ICF). Unlike the ICF, where instabilities, especially the Rayleigh-Taylor instability, have been studied extensively, the instability study of the spherical pinch has just begun. The Rayleigh-Taylor instability is investigated for the first time in the SP in the present work. By using the simple condition for the Rayleigh-Taylor instability p·<0 (density and pressure gradients have opposite direction), we have qualitatively identified the regions for development of instabilities in the SP. It is found that the explosion phase (central discharge) is stable and instabilities take place in the imploding phase. However, the growth rate for the instability is not in exponential form, and the appearance of the Rayleigh-Taylor instability does not prevent the main shock wave from converging to the center of the sphere.     

直流微电网的储-荷虚拟直流电机优化控制技术

为提升虚拟直流电机（VDCM）控制对直流微电网的电压惯性与阻尼支持能力,并改善负荷侧的电压响应,提出了储-荷VDCM优化控制技术。通过类比直流电机的外特性建立储能侧和负荷侧VDCM动态模型。对VDCM控制进行改进,在储能侧对系统提供惯性支持,在负荷侧对系统施加阻尼控制,从而消除储能侧VDCM中电压惯性和阻尼的冲突,为系统母线提供足够的动态支撑。在此基础上,设计负荷侧惯性灵敏度控制环节,使储-荷VDCM能够为负荷提供灵活可控的电压惯性。根据李雅普诺夫稳定理论,分析所提VDCM优化控制对系统的稳定支持作用,根据分析提出参数优化方案,并利用时域仿真分析,验证所提控制策略的有效性。     

基于GNSS多通道跟踪接收机的阵列反欺骗方法

近年来,基于阵列天线的空域处理方法被认为是最有效的欺骗检测和抑制手段之一。提出了一种基于卫星导航接收机多通道跟踪能力的阵列反欺骗方法。多通道跟踪接收机对每一个捕获到的导航信号在所有阵元通道后均进行跟踪处理并提取信号幅度和载波相位观测量,首先计算载波相位双差平方和进行欺骗检测,然后利用载波相位单差和信号幅度比估计信号导引矢量,从而进行基于子空间投影的欺骗信号抑制或基于波束形成的真实卫星信噪比提升。理论分析和仿真试验证明,该方法可有效检测并消除同一来向的欺骗信号且不影响真实卫星信号质量。由于前端非理想因素带来的幅度和相位偏移都已包含在接收机跟踪通道提取的观测量内,实际应用时对阵列天线校准和射频通道均衡的要求明显降低。     

测量噪声方差未知的多传感器组合导航集中融合算法

目前,多传感器组合导航系统的信息融合方法是建立在测量噪声方差已知的基础上,然而测量噪声方差会随着内部及外部的干扰而发生变化。为此,本文首先将基于变分贝叶斯逼近的自适应卡尔曼滤波(variational Bayesian approximation based adaptive Kalman filter, VB-AKF)从单一组合导航系统扩展到多传感器组合导航系统;然后,提出了多传感器组合导航系统的两种集中融合算法,即基于VB-AKF的增广式集中融合算法及基于VB-AKF的序贯式集中融合算法,以解决测量噪声方差未知情况下的多传感器组合导航的信息融合问题;最后,通过SINS/GNSS/CNS/ADS多传感器组合导航系统对上述算法进行了仿真验证。实验结果表明,本文所提两种算法滤波精度相同、且接近于测量噪声方差已知情况下的理想集中融合算法(ICKF)。在整个仿真时段内,相对于传统集中式卡尔曼滤波器(TCKF)及具有容错功能的联邦卡尔曼滤波算法(FT-FKF),本文算法可提高位置精度分别为32%和90%、提高速度精度分别为38%和71%。     

Improving pedestrians’ navigation safety at night by enhancing legibility of foreground and background information on the display

Traffic intersections are dangerous areas for pedestrians at night, primarily when people use their mobile phones while walking; pedestrians’ line of sight switches between their phones and the environment, which causes inattentional blindness during emergencies. The salience of the foreground and background information is different by the lightness conditions; therefore, identifying the lightness level of the foreground and background is critical. In this study, the brightness of urban traffic intersection scenes in the nighttime was analyzed, and improved color tones of the navigation interface for enhancing information recognition were identified. Moreover, identify the balance of visual attention by adjusting lightness and color treatment between foreground and background information. A glance legibility experiment indicated that a warm color tone with contrast and gamma correction under a lighting value of 65 in the LAB color mode is the optimal recognition combination. The results of this study indicated that low gamma under high lighting effectively reduced glare-related distractions and resulted in the lowest error rate in background information recognition. This paper proposes increasing the visual attention of urban pedestrians during nighttime navigation through the balancing of the lighting of the foreground interface and the color treatment of the background. Navigating at nighttime can be safer when their attention toward the environment increases and decreases attention distraction.