Autonomous tactile perception: A combined improved sensing and Bayesian nonparametric approach

In recent years, autonomous robots have increasingly been deployed in unknown environments and required to manipulate or categorize unknown objects. In order to cope with these unfamiliar situations, improvements must be made both in sensing technologies and in the capability to autonomously train perception models. In this paper, we explore this problem in the context of tactile surface identification and categorization. Using a highly-discriminant tactile probe based upon large bandwidth, triple axis accelerometer that is sensitive to surface texture and material properties, we demonstrate that unsupervised learning for surface identification with this tactile probe is feasible. To this end, we derived a Bayesian nonparametric approach based on Pitman–Yor processes to model power-law distributions, an extension of our previous work using Dirichlet processes Dallaire et al. (2011). When tested against a large collection of surfaces and without providing the actual number of surfaces, the tactile probe combined with our proposed approach demonstrated near-perfect recognition in many cases and achieved perfect recognition given the right conditions. We consider that our combined improvements demonstrate the feasibility of effective autonomous tactile perception systems.     

用于高速旋转载体的惯性导航系统设计

针对高速旋转载体的实际应用情况,采用了无陀螺捷联惯性导航技术方案,快速精确测量载体的姿态、速度和位置信息。无陀螺捷联惯导系统采用加速度计来解算载体相对惯性系的角速度,从而代替角速度陀螺仪,提高了系统的高过载的适应能力。首先推导了一种基于六加速度计配置方式力学编排方程,分析了加速度计精度、杆臂长度以及时间等因素对角速度误差产生影响,最后仿真分析了加速度计精度对惯导系统的定位精度的影响,为系统设计提供理论依据。     

基于六轴MEMS器件姿态测量系统

为了解决噪声和漂移等原因造成的误差不断累积的问题,针对陀螺仪的静态性能以及加速度计的动态性能,提出了一种利用六轴MEMS器件对照相机三脚架的稳定测量系统,介绍了MEMS器件的工作原理,介绍硬件系统和软件系统,完成了基于ADXR450陀螺仪和ADXL355加速度计的检测硬件系统设计,通过传感器获取角速度加速度信息,采用不同的滤波方式对输出结果进行了分析,比较卡尔曼滤波和一阶RC数字滤波;经比较,卡尔曼滤波实时性更好,一阶RC滤波动态响应更好;实验证明,系统静态下更适用于一阶滤波,计算出姿态测量角度误差在0.104°以内,得到理想的姿态信息,能有效地提高检测目标姿态的精度。     

基于双路加速度计的空间手写输入识别模型

针对三维空间手写过程中采样装置横滚角变化较小的特点,提出一种基于双路MEMS加速度计的无陀螺硬件编排方案及相应的角速度、线加速度解算方法;根据解算得到的线加速度,同步计算得到笔画数量、笔画走向和归一化长度、总的笔画归一化长度等手势特征,并表示为手势特征码;手势特征模式库基于手势特征码集合定义,并基于手势特征码与不同模式间的差异化度量值实现用于手势识别的分类器。基于手势特征码的手写模式识别方法能够较全面描述字符的时域特征,且对无效笔画有较好的适应能力,仿真实验验证了该方法的可行性和有效性。     

中国微米纳米-----梳齿式加速度传感器敏感结构等效并联电阻对输出的影响分析

梳齿式加速度传感器敏感结构间感应电容的测量会受到结构间等效电路参数的影响。多层瓷片电容的结构与梳齿式加速度传感器敏感结构类似。本文类比多层瓷片电容中等效电路参数的研究,分析了梳齿式加速度传感器敏感结构间等效电路参数对感应电容测试结果产生的影响。     

Comparative study on classifying human activities with miniature inertial and magnetic sensors

This paper provides a comparative study on the different techniques of classifying human activities that are performed using body-worn miniature inertial and magnetic sensors. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, the least-squares method (LSM), the k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector machines (SVM), and artificial neural networks (ANN). Human activities are classified using five sensor units worn on the chest, the arms, and the legs. Each sensor unit comprises a tri-axial gyroscope, a tri-axial accelerometer, and a tri-axial magnetometer. A feature set extracted from the raw sensor data using principal component analysis (PCA) is used in the classification process. A performance comparison of the classification techniques is provided in terms of their correct differentiation rates, confusion matrices, and computational cost, as well as their pre-processing, training, and storage requirements. Three different cross-validation techniques are employed to validate the classifiers. The results indicate that in general, BDM results in the highest correct classification rate with relatively small computational cost.     

在横向气流中螺旋管管阵动态响应的研究

对螺旋管管阵在横向气流冲刷下的振动响应进行了实验研究，所获得管子的加速度、速度和位移信号为螺旋管流弹不稳定性的研究提供了数据基础     

Technological aspects on the fabrication of silicon-based optical accelerometer with ARROW structures

The fabrication and characterization of an optical accelerometer based on silicon technology and using BESOI wafers is presented. Instead of the standard total internal reflection (TIR) waveguides, AntiResonant Reflecting Optical Waveguides (ARROW) have been used. On the basis of a quad beam accelerometer design, a sensing waveguide has been placed on the seismic mass. Its misalignment with the waveguides located at the frame allows measuring the acceleration. The mechanical structure has been designed so as to have a span of 2 μm, that should provide with a sensitivity of 4.6 dB/g. Reference waveguides measured by end-fire coupling have low radiation and insertion losses (0.3 and 2.5 dB, respectively). High insertion losses are observed due to imperfections in polishing when V-grooves with glass anodic bonding are used. This fact causes the reduction of its sensibility to 2.3 dB/g.     

基于等效电路法的微加速度计系统建模研究

讨论一类硅微闭环电容式加速度计系统级动态模型的建模过程与方法.MEMS（micro-electro-mechanical system）快速有效的系统级模拟依赖于准确简洁的器件宏模型的建立.文中首先针对一种基本机电换能器件进行研究,利用二元函数的Taylor公式,建立器件偏置点附近增量信号间的线性关系,进而建立可用等效电路形式描述的器件宏模型.以此为基础,分别探讨传感器中检测和加力两类差动电容模型的建立方法及其与外部环境的联接,得到可利用电路模拟软件进行分析的系统级等效电路.通过仿真实例验证模型的正确性,并简要讨论系统的主要动态特性.这些工作为进一步的系统仿真和全局优化提供可靠的模型基础.     

Design and Analysis of MEMS Comb Drive Capacitive Accelerometer for SHM and Seismic Applications

This work presents the design of a MEMS accelerometer that is specifically intended for Structural Health Monitoring (SHM) applications where sensing low frequency low amplitude accelerations with high resolution is essential. The surface micromachined comb drive capacitance accelerometer structure has been considered in this design. The simulation experiments conducted on these devices using IntelliSuite MEMS design tool show that it has excellent displacement sensitivity of 21.39 μm/g, a capacitive sensitivity of 1.22 pF/g and voltage sensitivity of 1783 mV/g/V when it is designed to measure 0–0.1 g. Further, it is seen that it has a very low noise floor of 1.32 μg/√Hz and therefore high resolution. Since the accelerations can be as low as 0.04 g in SHM applications, excellent resolution is the primary goal in this design. Further, one more sensor specifically meant for strong motion seismic application has also been reported. This device has a bandwidth of 0–250 Hz and a noise floor of 5.612 μg/√Hz in addition to a sensor level voltage sensitivity of 97.9 mV/g/V. Finally, the comparison of these results with other similar devices reported in the past clearly illustrates the comparable performance of the present devices. Further, these devices, unlike the commercial low frequency accelerometers and other similar devices reported in the past can be fabricated by surface micromachining and CMOS compatible processes.