基于PI自适应卡尔曼滤波的无人机姿态解算算法

针对无人机姿态解算过程中,机载加速度计噪声时变,导致姿态估计值出现较大误差的问题,提出了一种基于PI自适应卡尔曼滤波的姿态解算算法,通过监视残差方差的理论值与实际值的差值,利用PI控制算法对观测噪声协方差矩阵进行在线修正,来解决由于噪声估计不准而导致滤波发散的问题。实验结果表明,即使是在无人机的姿态发生剧烈变化时,该算法依然具有良好的精度,鲁棒性较好。     

改进Allan方差的自适应滤波在姿态解算中的应用

对低成本的惯性导航系统精度不足从而导致姿态解算容易发散的问题,提出一种改进Allan方差的自适应卡尔曼滤波算法。在滤波之前,先用四元数改进型PID的互补滤波来融合数据,以抑制数据的波动,同时也加快了运算速率,在对噪声进行分析时,运用Allan方差的分析方法,并组合高斯牛顿优化算法,提高了姿态解算的精度,能够对姿态角实现短时间内的稳定以及精确的跟踪。实验结果表明,使用自适应Sage-Husa算法处理两种噪声时比标准卡尔曼滤波算法的精度提高了30%左右,使用改进的Allan方差自适应滤波比使用自适应 Sage-Husa滤波算法精度提高了40%左右,该算法也可用于精确单点定位与伪距定位。     

互补滤波和卡尔曼滤波的融合姿态解算方法

针对捷联惯性测量单元(IMU)噪声大、精度低的缺点和常规的姿态解算算法精度不高等问题,提出了一种互补滤波和卡尔曼滤波相结合的融合算法.该算法基于姿态角微分方程建立系统的状态方程模型,利用互补滤波后的姿态角作为系统的观测量,再应用扩展卡尔曼滤波(EKF)算法融合了陀螺仪、加速度计和电子罗盘的测量数据.为验证该算法有效性,用带有传感器的开发板依次进行静态和动态测试,实验结果表明:结合了互补滤波和卡尔曼滤波的融合算法,在静态时能够抑制姿态角漂移和滤出噪声,在动态时能够快速跟踪姿态的变化,提高了姿态角的解算精度.     

基于视觉/惯导的无人机组合导航算法研究

目前视觉惯性组合导航系统多采用优化紧/松耦合以及滤波紧/松耦合算法,应用误差状态卡尔曼滤波能够将较低频率的视觉位姿信息提升到与惯性信息同步的频率;提出一种基于自适应卡尔曼滤波的视觉惯导组合导航算法,首先考虑到系统建模与传感器测量误差,采用自适应渐消卡尔曼滤波进行导航解算,通过实时计算遗忘因子,以调节历史数据的权重,可抑制建模误差,提高组合导航系统性能,然后针对视觉SLAM解算过程造成的视觉位姿信息滞后于惯导信息的问题,提出一种延时补偿方法;仿真实验表明,采用延时补偿的自适应渐消卡尔曼滤波算法能够有效抑制建模误差,并降低视觉位姿信息滞后带来的影响,提高无人机组合导航的解算精度,姿态、速度、位置解算精度分别达到5°、0.5m/s、0.4m以内。     

基于预估测量值的EKF在手臂测姿中的应用

针对载体线性加速度以及周围局部磁干扰对姿态测量精度的影响,基于已有的惯性测量单元,设计了一个基于四元数的实时估计手臂姿态的扩展卡尔曼滤波器(EKF)。提出利用四元数引入加速计和磁强计的预估测量值构造自适应测量噪声协方差阵的方法,结合QUEST算法,来判定姿态角解算对陀螺仪、加速计和磁强计输出信息的依赖程度,以此来提高测量精度。文末通过实验仿真对该方法进行了验证,并对实验结果和电磁跟踪系统采集到的数据进行了比较,结果表明,本文提出的方法能显著提高手臂姿态测量精度,可有效满足应用要求。     

基于扩展卡尔曼滤波的球形机器人姿态解算

针对球形机器人在姿态解算的过程中,惯性测量元件精度不高、稳定性差和易受噪声干扰从而导致无法精确控制其运动姿态的问题,提出一种通过扩展卡尔曼滤波融合IMU(Inertial Measurement Unit)惯性测量元件数据来进行姿态解算的方法,利用多传感器测量数据进行融合,并使用扩展卡尔曼滤波得到精确的姿态信息。通过相关实验充分验证了基于扩展卡尔曼滤波的姿态解算方法的精度和鲁棒性明显提高,抗噪声干扰能力更强。实验表明,该姿态解算方法相比于互补滤波的姿态解算,全姿态角均方根误差和平均误差分别下降了0.0601和0.1984,可见其对于球形机器人的运动控制具有良好的适用性。     

基于卡尔曼滤波的航姿参考系统设计

针对传统的航姿参考系统AHRS（Attitude and Heading Reference System）中姿态角精度不高的问题,设计了一种新型的基于卡尔曼滤波的姿态检测系统。该系统采用了三轴磁传感器、三轴陀螺仪及三轴加速度计,用四元数的方法来描述载体运动的姿态,通过陀螺仪测姿态四元数,卡尔曼滤波算法融合加速度计和磁传感器数据,对姿态四元数进行修正,从而提高姿态解算精度。实验数据表明,系统能够较好修正陀螺仪漂移,且三个角度的均方根误差均优于0.25°,具有良好的噪声抑制能力。     

小型无人机姿态解算方法研究

姿态解算是小型多旋翼无人机研究的核心问题之一.为进一步提高姿态反馈数据的准确度和实时性,设计了低成本姿态解算系统,根据不同姿态传感器的信号特点,结合卡尔曼滤波融合算法和改进型互补滤波融合算法的优势,提出了一种基于前置卡尔曼滤波器的互补滤波融合姿态解算方法,并进行了飞行姿态解算实验.结果表明,代码的运行周期比改进型互补滤波融合算法增加了0.253 ms,比基于加权滑动方差的卡尔曼滤波融合算法减少了0.246 ms;姿态更新时间提前了约1 ms.悬停状态下,俯仰角和翻滚角的解算误差控制在±0.2°以内;航向角的解算误差控制在±0.6°以内.该方法集合了卡尔曼滤波算法和互补滤波算法的优势,准确度更高,实时性更强.     

低成本无人机姿态解算研究

针对小型四旋翼无人机姿态解算数据精度低、缺少余度控制、易发散等问题,提出一种基于GPS、三轴陀螺仪加速度计、三轴磁力计的随机加权自适应滤波算法估计无人机姿态;建立四旋翼无人机姿态旋转矩阵,搭建加速度计和磁力计获取无人机姿态信息的模型,以及采用四元数解算法的陀螺仪定姿解算模型;采用随机加权自适应估计法,依据多元函数求极值定理,在保证总体均方差最小的情况下导出最优随机加权因子,进而解算出姿态角信息,提高四旋翼无人机姿态解算滤波精度与稳定性;仿真与试验结果表明:随机加权自适应滤波与平均值滤波算法相比解算精度更高,输出结果更平稳,且无人机各项预期功能均能正常实现,能够满足四旋翼无人机自主飞行的需要。     

GPS失效时组合导航系统修正方法研究

针对采用低成本惯性元件的MEMS-IMU/GPS组合导航系统在GPS信号长时间失效后系统趋于发散的问题,在研究捷联航姿解算算法、加速计测量姿态角算法和磁传感器解算航向角算法的基础上,提出将航姿辅助修正算法引入组合导航系统中,一旦系统检测到无效信号出现,则能自动切换到辅助修正状态,使导航结果被抑制在0.5°左右;通过半实物仿真实验,证明了该方法能够有效解决GPS信号长时间失效后系统发散问题,满足了在低成本MEMS惯性元件基础上的高精度导航要求。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.