一种动态环境下的移动机器人避障策略

以激光雷达作为主要的环境感知传感器,针对动态环境设计了一种移动机器人避障策略.根据激光雷达采集的实时环境信息,检测动静态障碍物并建立障碍物链表.采用底层反应式避障和高层动态避障相结合的策略,实现了动态环境下的避障.使用分布式的软件设计方法,提高了系统的实时性.通过自行研制的移动机器人MORCS-1进行了实验,实验结果验证了该策略的有效性.     

基于多传感器信息融合的机器人障碍物检测

针对单一传感器在机器人避障过程中不能全面且准确定位障碍物的缺点,提出基于多传感器信息融合的障碍物检测方法。第一阶段使用视觉传感器检测未知环境中的障碍物,通过Zernike矩边缘检测方法提取障碍物图像边缘,然后采用Hough变换原理提取障碍物的直线特征,获得障碍物大概位置;第二阶段使用超声波传感器和红外传感器对障碍物进行检测,获得障碍物准确位置;最后使用联合卡尔曼滤波对3种传感器获得的信息进行融合,得出融合后的障碍物位置信息。实验结果表明:该方法克服视觉传感器、超声波传感器和红外传感器的局限性,可以精确感知机器人周围的未知环境信息,并能够检测和定位机器人路径上的障碍物,定位误差6 cm,满足机器人避障的实时性和可靠性需求。     

基于多特征提取的越野智能车辆环境探测

为实时获取越野智能车辆前方的地形信息并有效检测出可能存在的障碍物,本文提出一种基于立体视觉传感器的环境探测方法.该方法首先对图像进行局部对比度增强,以减弱光照变化对立体匹配的影响并保证角点特征提取的均匀性.其次研究图像中障碍物的边缘特征提取方法,以避免障碍物的漏检.然后提出基于多特征提取的立体匹配流程,其中采用了随机采样序列方法计算基础矩阵,将基于边缘的匹配与基于角点的匹配独立进行以避免干扰,并引入连续性约束来剔除误匹配.最后,通过不同光照越野场景的环境重构实验验证算法的鲁棒性.     

移动目标检测技术的研究

在人所感知到的环境信息中,视觉信息占了非常大的比重,其中动态视觉信息更是其主要组成部分.感知环境中的这些动态视觉信息已成为计算机视觉的一个重要的研究方向.移动目标检测是计算机视觉领域中最活跃的研究课题之一,在许多领域有着广泛的应用.论文中提出了对背景减除等运动目标检测方法和对帧差法等运动目标检测的算法进行了研究和改进,使之能更精确的检测出移动目标.     

基于自适应观测模型的移动机器人室内蒙特卡罗动态定位系统研究

针对存在玻璃门、动态行走的行人的环境时,传统的蒙特卡罗移动机器人定位算法因环境噪声的增大致使观测信息剧烈变化导致定位性能下降的问题,提出了一种基于改进的观测模型的蒙特卡罗定位(MCL)算法。该算法通过在观测模型中引入测量失败误差和动态误差提高激光传感器测量数据的有效性,利用激光传感器测得数据匹配已创建的占用栅格地图,检测已知环境是否发生变化,从而改变随机误差、测量失败误差、动态误差对应的权重,降低噪声对测量值的影响,提高在复杂环境下的定位准确性。基于机器人操作系统(ROS)进行了实验,实验结果表明该算法具有较好的有效性。     

温湿度对蜂窝纸板静力学性能影响及有限元分析

目的 针对目前定制家具打包运输过程AGV避障方法中,对障碍物信息辨识度较低、难以做到精准避障等问题,提出一种采用视觉传感器基于改进目标检测算法的AGV避障策略。方法 利用Mobilenet模型改进传统SSD目标检测算法,以AGV工作环境数据对训练后的SSD-Mobilenet模型进行迁移学习,结合视觉、超声波等多个模块实现避障原理,搭建以树莓派3B+为控制核心的实验平台进行相关实验研究。结果 实验证明该方法的检测精度达到94%,能够精准辨别障碍物类型;目标检测避障方法的避障通过时间比传统方法减少了15.8%～27.3%。结论 该方法有效提高了AGV避障的准确率与效率,可广泛应用在AGV避障控制中。     

基于有限状态机的足球机器人行为设计与综合

介绍了一个面向动态环境作业的全自主移动机器人系统。该机器人系统集成了包括视觉、激光雷达、声纳环、里程仪在内的多传感器系统,双轮独立驱动的移动小车以及高速无线局域网,并通过车载控制系统进行实时决策。控制系统采用递阶的混合式结构,在上层利用基于有限状态机的行为选择方法实现行为规划,在低层采用基于行为的控制技术。通过对指定任务的分解,该方法实现了动态环境下多行为的协调,使机器人具有较高的决策智能,同时又保证了快速的反应能力。动态环境下的实验和比赛结果证明了该方法的有效性。     

基于动态描述逻辑的Web服务自动组合技术

提出了一种利用动态描述逻辑(DDL)的动态推理自动组合Web服务的方法.DDL是描述逻辑(DL)的一种动态扩展,它结合本体提供的静态信息与Web服务提供的计算,统一地描述和推理Web环境中静态信息与动态知识.该方法充分利用Web服务组合中涉及的静态知识(如描述逻辑知识库刻画的领域公理、具体环境和用户需求等)和动态知识(...     

基于线结构光-机器视觉的CHN钢轨轨距动态检测方法

针对有轨电车传统轨距检测方法存在检测成本高、标定抗干扰能力弱等缺点,提出一种基于线结构光-机器视觉的轨距动态检测方法,通过线结构光照射左右铁路轨道,形成钢轨轮廓信息。首先通过标定,建立并融合左右轨道的空间姿态坐标系,获取轨距的计算公式。接着通过机器视觉中的灰度滤波、高斯滤波、开运算、骨架提取算法对轨道轮廓图像进行处理。然后将处理后的轮廓图像通过标定的空间姿态坐标系计算出轮廓的实际空间坐标,即可得到轨距。该方法不仅只用2组线结构激光摄像式传感器降低检测成本,且通过机器视觉算法能够大大提升环境干扰下轨距动态测量的鲁棒性,保证测量的精度。最后通过实验室平台以及轨检车试验场验证该方法的可行性和有效性。     

基于最小二乘支持向量机的传感器非线性动态系统辨识

讨论了一种基于最小二乘支持向量机的非线性动态传感器系统辨识方法,并给出了相应的推导过程和学习算法.首先,将传感器的非线性动态系统分解为静态非线性子环节和动态线性子环节串联--Hammerstein模型;然后,建立类似线性的中间模型,通过该模型能将Hammerstein模型的非线性传递函数转换为等价的类线性形式;再通过LS-SVM线性回归算法求取中间模型参数;最后推导出中间模型参数与Hammerstein模型参数之间的关系,并通过该关系反演出原传感器系统的Hammerstein模型参数,实现传感器非线性动态辨识.仿真与实际传感器系统辨识的实验结果均表明该方法可行.     

Generating B-Scans of the Environment With a Conventional Sonar

This paper examines the task of displaying more information about the environment using a conventional ranging sonar than is available in standard time-of-flight (TOF) maps. A conventional ranging sonar forms an environmental image that displays the information in the echo envelope, similar to a medical ultrasound image. The sonar performs rotational sector scans of simple objects and two complex environments containing various reflecting structures. In acquiring sonar data, we repeatedly reset the conventional sonar to generate a point process whose density relates to the echo amplitude. This point process is displayed as a grayscale image, called a brightness scan (B-scan), analogous to B-scans in medical ultrasound. We compare the information content of sonar B-scans to TOF maps for object classification and show B-scans to be richer. B-scan textures produced by rough surfaces and volumes containing random scatterers exhibit statistical invariance, similar to some organs within the body, suggesting the feasibility of automated classification. Image artifacts and means for their identification are discussed. The qualitative information present in sonar B-scans should lead to improved quantitative techniques for classifying objects.     

Improving backing-up manoeuvre safety with vision-based movement detection

Every year, backing-up crashes are responsible for hundreds of casualties in the world. In order to reduce this number, many automotive suppliers now provide ways for drivers to monitor the rear of their vehicle using sonar - or radar-based systems or wide angle cameras. Yet these systems still do not offer the performance required to consequently reduce the number of fatalities. To overcome the limitations of these systems, we have developed a real-time static obstacle detection system using a wide angle camera. We now propose to add moving obstacle detection and localisation to our camera-based system. Such system is the perfect candidate for next generation of automatic anti-collision systems. Our approach is based on camera movement compensation using inverse perspective mapping and probabilistic reasoning for movement detection. Using shape filtering, our approach can even limit detection to specific types of moving objects (pedestrians, cars etc.). We present the algorithms developed and the evaluation protocol used. We also show results of the system in typical urban situations, some in hard conditions (worst cases), and conclude on which future developments will bring performance improvements     

A dynamic mesh strategy applied to the simulation of flapping wings

A robust and efficient dynamic grid strategy based on an overset grid coupled with mesh deformation technique is proposed for simulating unsteady flow of flapping wings undergoing large geometrical displacement. The dynamic grid method was implemented using a hierarchical unstructured overset grid locally coupled with a fast radial basis function (RBF)‐based mapping approach. The hierarchically organized overset grid allows transferring the grid resolution for multiple blocks and overlapping/embedding the meshes. The RBF‐based mapping approach is particularly highlighted in this paper in view of its considerable computational efficiency compared with conventional RBF evaluation. The performance of the proposed dynamic mesh strategy is demonstrated by three typical unsteady cases, including a rotating rectangular block in a fixed domain, a relative movement between self‐propelled fishes and the X‐wing type flapping‐wing micro air vehicle DelFly, which displays the clap‐and‐fling wing‐interaction phenomenon on both sides of the fuselage. Results show that the proposed method can be applied to the simulation of flapping wings with satisfactory efficiency and robustness. Copyright © 2016 John Wiley & Sons, Ltd.     

Biomimetic Sonar and Neuromorphic Processing Eliminate Reverberation Artifacts

A biomimetic sonar is configured using two conventional sensors that generate point processes related to echo waveform intensity, resembling biological action potential spikes. The sensors point slightly outward from the sonar axis, similar to pinnae in some bats, to acquire slightly different views of the environment during a rotational scan. Artifacts in sonar maps are points that do not relate to actual object locations. Physical criteria identify artifacts by applying echo strength, azimuthal extent, and binaural coincidence criteria. Neuromorphic processing implements these criteria with thresholding, delays, and short-term memories. Artifacts are deleted to produce robust sonar maps. Multiple resolution maps, generated by using two thresholds, illustrate improvements over conventional sonar maps and tradeoffs between resolution and stability     

基于声呐历程累积图像的弱回波目标检测方法

针对浅海随机噪声与混响背景下蛙人等弱回波强度、慢速小目标的检测问题,提出一种基于声呐历程累积图像的目标检测方法。首先根据声呐图像时域、空域相关性,采用背景空时归一化处理技术,抑制声呐背景中的静态混响、突发性噪声等强回波干扰。声呐历程累积图像集成了多帧声呐图像的信息,目标回波亮点由于运动连续性形成亮线特征,利用该特征,采用Radon恒虚警率(Radon Constant False Alarm Rate,Radon-CFAR)检测声呐历程累积图像中的目标短时运动轨迹,能够检测到低信噪比的目标。分析了空时归一化处理和检测算法的性能,并通过海试数据验证了该算法的有效性,可以检测到低信噪比的蛙人目标回波。     

基于声呐历程累积图像的弱回波目标检测方法

针对浅海随机噪声与混响背景下蛙人等弱回波强度、慢速小目标的检测问题,提出一种基于声呐历程累积图像的目标检测方法.首先根据声呐图像时域、空域相关性,采用背景空时归一化处理技术,抑制声呐背景中的静态混响、突发性噪声等强回波干扰.声呐历程累积图像集成了多帧声呐图像的信息,目标回波亮点由于运动连续性形成亮线特征,利用该特征,采...     

一种非结构环境下多机器人构建地图的方法

提出了一种多移动机器人在非结构环境下构建地图的新方法.该方法让各机器人独立探索环境并对不同的局部栅格地图予以融合.在地图融合过程中,无需考虑机器人相对位置的先验信息,而是以栅格地图相似度为度量标准,利用距离变换和改进的遗传算法高效、快速地搜索各局部地图之间的最大重叠部分,进而予以融合.实验结果表明,与常规方法相比,该方法能够较为精确地实现非结构环境下多机器人地图构建,且限制条件少,更适合于实际应用中的各种复杂情况.     

RBF_TFI结构动网格技术在风洞静气动弹性修正中的应用

面向风洞模型静气动弹性修正发展了一种基于RBF(Radial Basis Function, RBF)和TFI(Transfinite Interpolation, TFI)插值方法的高效高质量结构动网格生成技术,即利用精简径向基基点后的RBF方法对结构网格块的棱线节点坐标进行更新,然后通过TFI方法重新生成变形后的面网格、体网格。翼型旋转变形动网格实例说明该方法可以生成高质量的变形网格。结合该动网格方法和风洞实验模型变形数据开展的F6翼身组合体模型静气动弹性修正计算,结果表明,模型变形对气动力系数的影响量远超风洞实验允许的误差极限,开展风洞静气动弹性修正对于提高风洞实验数据准度具有重要的工程价值。     

Processing and Analysis of Underwater Acoustic Images Generated by Mechanically Scanned Sonar Systems

The processing and analysis of images generated by mechanically scanned sonar systems have received poor attention despite their widespread application. In this paper, some efficient methods for acoustic image enhancement and automatic object detection are presented and assessed using a large set of experimental data collected at sea with commercial sonar systems. Specifically, a set of methods for increasing the quality of the gray-level images produced by a fan-shaped-beam sonar is introduced. Such a set includes a dynamic brightness assignment, a precise interpolation, a speckle-reduction filter, and a contrast-enhancement block. Two versions of a template-matching-based method that allows the automatic detection of a simple object contained in a region scanned with a pencil-beam sonar are also proposed and assessed. The main difficulty to be coped with in this field is related to the sparseness of the binary maps generated by this sonar system. The performance and robustness of the proposed techniques have been evaluated using real data that provided satisfactory results for both the image-enhancement and the object-detection tasks. Moreover, the computational burden of most of the proposed techniques turned out to be quite limited, and their real-time implementation with a standard computer architecture could be estimated.      

Quantitative NIR chemical imaging in heritage science

Until recently, applications of spectral imaging in heritage science mostly focused on qualitative examination of artworks. This is partly due to the complexity of artworks and partly due to the lack of appropriate standard materials. With the recent advance of NIR imaging spectrometers, the interval 1000-2500 nm became available for exploration, enabling us to extract quantitative chemical information from artworks. In this contribution, the development of 2D NIR quantitative chemical maps of heritage objects is discussed along with presentation of the first quantitative image. Further case studies include semiquantitative mapping of plasticiser distribution in a plastic object and identification of historic plastic materials. In the NIR imaging studies discussed, sets of 256 spatially registered images were collected at different wavelengths in the NIR region of 1000-2500 nm. The data was analyzed as a spectral cube, both as a stack of wavelength-resolved images and as a series of spectra, one per each sample pixel, using multivariate analysis. This approach is only possible using well-characterized reference sample collections, as quantitative imaging applications need to be developed, thus enabling spatial maps of damaged and degraded areas to be visualized to a level of chemical detail previously not possible. Such quantitative chemical mapping of vulnerable areas of heritage objects is invaluable, as it enables damage to historic objects to be quantitatively visualized.