强噪声下压力传感器触觉信号的提纯算法设计

压力传感器触觉信号提纯时，易受强噪声干扰，影响信号提纯效果。为解决上述问题，提出基于局域波分解的强噪声下压力传感器触觉信号提纯方法。利用局域波分解对压力传感器中的局部均值特征，排除触觉信号降干扰，避免噪声对信号提纯过程产生影响，并设计校正算法对触觉信号处理，提取频域特征。利用小波变换法分解压力传感器触觉信号，得到信号频域成分。利用阈值重构频域成分，完成强噪声下压力传感器触觉信号的提纯。仿真结果表明，所提方法的提纯时间在2 s上下波动，平均信噪比为14.13 dB，平均均均方根误差为0.63。     

机器人触觉传感器的理论模型

本文从理论上探讨了机器人触觉传感器理论设计参数和实际制造参数的选择,给出了几种典型触觉传递矩阵,还讨论了触觉信号在计算机中的表示形式,最后对触觉传感器的噪声信号进行了简单的分析。     

触觉传感器及其图象识别

本文讨论了两种触觉传感器,系统地阐述了这两种触觉传感器的数据采集系统和图象二值化的有关算法。     

RBF神经网络在柔性触觉传感器解耦中的应用

针对柔性触觉传感器模型高度非线性、解耦难度大等问题,提出一种有效的方法来模拟柔性触觉传感器在实际应用中含噪声的情形。首先在理想条件下的传感器模型上添加不同幅度的高斯白噪声并建立其数学模型,之后通过K-均值和递归最小二乘法优化RBF神经网络,并利用优化后的RBF神经网络算法逼近受噪声干扰的传感器阻值与形变之间的高维非线性映射关系,最后基于不同的展开幅度通过行列阻值解耦出传感器三维形变信息,获得了较好的解耦精度。解耦结果表明,RBF神经网络算法具有较强的鲁棒性和抗噪声能力,能够很好地逼近含噪声的传感器高维非线性数据之间的映射关系。     

机器人触觉传感器发展概述

触觉是机器人感知外部环境的重要信息来源。近10年来，随着触觉感知技术和交互技术的广泛应用，机器人触觉传感技术得到了机器人研发人员的高度关注。首先简要回顾了近50年来机器人触觉传感器技术研究的发展情况，特别是我国在机器人触觉传感器技术领域的研究历程；然后，对现有机器人触觉传感技术进行了分类总结；接着，对当前触觉传感技术研发的前沿即电子触觉皮肤的研究做了分析和阐述，指出了机器人触觉传感技术研发亟待解决的关键问题，并对未来的发展趋势提出了一些见解。     

机器人传感器(上)

一、概述1.机器人传感器的功能及其作用由于传感器电子学的发展,机器人由重复型过渡到智能型,智能机器人通过外部传感器控制行动。机器人传感器有多种分类法,表1是分类法之一。表中外部传感器和人的感觉对应,故亦称感觉传感器。机器人传感器主要是视觉、触觉和近接觉。表2列出机器人视觉传感器及其应用情况,表3列出触觉传感器及其应用情况。这里将近接觉作为触觉看待,故将近接觉传感器亦列在3表中。     

基于数字图像的台阶斜率提取

机器人的姿态是机器人自主爬楼的前提.为了获得机器人与台阶棱线的夹角,对视觉传感器拍摄的数字图像进行处理.首先对图像一阶微分后按"录取线"取阈值二值化,凸现台阶棱线的像;其次采用聚类分析的办法,提取出像上台阶斜率,该方法能滤除噪声且逼近真实值;最后根据几何成像原理,列出了像上斜率与真实斜率之间关系的表达式并对式中参数进行了标定.经实验验证得出误差不超过5°.     

机器人触觉临场感电触觉反馈技术研究

本文对机器人触觉临场感电触觉反馈技术进行了实验性研究。设计出了电触觉反馈装置和触觉反馈手套,结合我们已经研制出的指形触觉传感器和数据手套构成了遥操作机器人触觉临场感系统。联机实验结果表明,该触觉反馈装置能够给操作者提供有效的触觉反馈。     

机器人触觉研究现状与发展浅析

本文主要综述了触觉传感器技术、触觉控制与规划方法和触觉信息处理技术等机器人触觉主要研究内容的发展现状和发展趋势,同时指出了我国在机器人触觉研究方面的近期目标和远期目标.     

虚拟触觉传感器的仿真模型研究

本文根据真实触觉传感器的原理,对虚拟触觉传感器的仿真模型进行了研究,以便 在机器人手抓拾取操作中揭示与材料特性相关的触觉信息瞬态特性,进而为在虚拟环境中从 事基于传感信息的机器人柔性操作、精密装配操作等提供良好的研究平台．     

Design of a discrete Kalman filter for a tactile sensor in a feedback control system

This paper presents a design methodology for the optimum linear filter and predictor applied to robot sensor signals, as well as a sensitivity analysis of the kalman algorithms for uncertainties in the estimation of signal and noise parameters. Simulation of the filtration and prediction processes was made assuming a first-order spectrum of a pure signal and white measurement noise. Calculations of the algorithm errors, dependent on the accuracy of the signal and noise parameter estimation, were done for various spectra of the signal and for various signal-to-noise ratios. Furthermore, the sensitivity curves of the Kalman filter and predictor are presented. The outlined considerations might be helpful for designers when synthesizing optimum linear digital filters applied to sensor signals. Although that particular procedure has been designed for a robot tactile sensor application, the conclusions are more general, and applications may be found elsewhere.     

Realizing whole-body tactile interactions with a self-organizing,multi-modal artificial skin on a humanoid robot

In this paper, we present a new approach to realize whole-body tactile interactions with a self-organizing, multi-modal artificial skin on a humanoid robot. We, therefore, equipped the whole upper body of the humanoid HRP-2 with various patches of CellulARSkin – a modular artificial skin. In order to automatically handle a potentially high number of tactile sensor cells and motors units, the robot uses open-loop exploration motions, and distributed accelerometers in the artificial skin cells, to acquire its self-centered sensory-motor knowledge. This body self-knowledge is then utilized to transfer multi-modal tactile stimulations into reactive body motions. Tactile events provide feedback on changes of contact on the whole-body surface. We demonstrate the feasibility of our approach on a humanoid, here HRP-2, grasping large and unknown objects only via tactile feedback. Kinesthetically taught grasping trajectories, are reactively adapted to the size and stiffness of different test objects. Our paper contributes the first realization of a self-organizing tactile sensor-behavior mapping on a full-sized humanoid robot, enabling a position controlled robot to compliantly handle objects.     

High precision intelligent flexible grasping front-end with CMOS interface for robots application用于智能机器人精细抓握的高灵敏度柔性抓握前端

This paper presents a high-precision intelligent flexible robot grasping front-end with an integrated capacitive tactile sensor array and a conditioning chip. The capacitive tactile sensor is the primary part of the front-end, it determines the overall performance. The micro-needle array sandwich structure in the tactile sensor increases the repeatability and stability, and ensures the sensitivity. The assembled sensor exhibits a saturation at 10.53 N (421 kPa) with a sensitivity of 1.9%/kPa. Furthermore, a conditioning chip is utilized in a custom readout interface to achieve better performance by reducing signal attenuation, and to increase the compatibility of the front-end. The chip is optimized for the parasitic shunt capacitance in the capacitor array. A dual bidirectional charge-discharge conversion method and a two-port detection method are matched to achieve the goal of reducing the shunting influence, and attenuating the offset voltage or the noise input effects. A prototype of the interface has been fabricated using 180-nm CMOS technology. Sensor with the value of 0.5 pF shunted by capacitors of 47 pF has been detected with an error of 1% within 100 μs.     

焊接机器人图像传感器噪声分析

焊接机器人获取焊缝的计算机视觉信息过程中,由于工件表面的反光系数,光学镜头性能的非线性,光电转换时叠加了随机噪声;信号电荷的存储、传输和输出存在暗电流等噪声;视频信号传输时存在噪声;视频信号模数转换存在量化噪声,导致获取的二维数字图像信号有一定的误差。为了减小此误差对后续的图像处理的影响,对图像传感器的图像噪声进行了分析,并得到了一个经验的图像噪声模型,实验结果表明:该模型有效且实用。     

用PVDF制作的机器人传感器

在分析PVDF敏感特性的基础上，阐述了用核材料研制的三维腕力传感器、阵列压力传感器及热觉传感器，给出了三种传感器的结构及相应信号处理方法．     

基于PVDF的三维力机器人触觉传感器的设计

当机器手抓取时物体受力信息检测是抓取过程顺利进行的基础,检测三维方向上的力便可充分反映物体的受力信息。当前用于抓取过程中三维力检测的触觉传感器还存在着一些不足,基于此,论文拟设计一种基于PVDF的三维力机器人触觉传感器。论文展示了传感器的结构设计,建立了压电薄膜及传感头结构的数学模型,设计了调理电路并对传感器进行测试和验证,结果表明该传感器能有效检测机器手抓取过程中的三维力信息。     

Development of soft and distributed tactile sensors and the application to a humanoid robot

This paper describes a comprehensive tactile sensor system which can cover wide areas of full-body robots. Based on design criteria which are introduced from requirements, we develop two types of tactile sensor elements. One is a multi-valued touch sensor which has multi-level pressure thresholds. It is capable of covering wide areas of robot surfaces. The other is made of soft, conductive gel, which has the advantage of compliance compared with other sheet-type tactile sensors. With these two types sensors, we develop the tactile sensor system on the full-body robot 'H4'. Details of the sensor system on the robot and some experiments using tactile information are described.     

柔性触觉传感技术及其在医疗康复机器人的应用

柔性触觉传感器易于贴合皮肤等不规则表面,相比刚性传感器具有更强的信号感知能力、更高的精度和更佳的穿戴舒适性,在人机交互、医疗设备、可穿戴设备、健康监测等领域发挥着重要作用.鉴于此,从传感器不同工作原理出发,对柔性触觉传感器进行系统地介绍和对比,从结构优化的角度分析传感器性能优化方法,整理出微结构、结构疏松化、多模态测量...