融入注意力机制的多模特征机械臂抓取位姿检测

针对机械臂抓取检测任务中对未知物体抓取位姿检测精度低、耗时长等问题,提出一种融入注意力机制多模特征抓取位姿检测网络.首先,设计多模态特征融合模块,在融合多模态特征同时对其赋权加强;然后,针对较浅层残差网络提取重点特征能力较弱的问题,引入卷积注意力模块,进一步提升网络特征提取能力;最后,通过全连接层对提取特征直接进行回归拟合,得到最优抓取检测位姿.实验结果表明,在Cornell公开抓取数据集上,所提出算法的图像拆分检测精度为98.9%,对象拆分检测精度为98.7%,检测速度为51FPS,对10类物体的100次真实抓取实验中,成功率为95%.     

基于多尺度特征融合的抓取位姿估计

抓取目标多样性、位姿随机性严重制约了机器人抓取的任务适应性,为提高机器人抓取成功率,提出一种融合多尺度特征的机器人抓取位姿估计方法.该方法以RGD信息为输入,采用ResNet-50主干网络,融合FPN(feature pyramid networks)获得多尺度特征作为抓取生成网络的输入,以生成抓取候选框;并将抓取方向...     

基于多重几何约束的未知物体抓取位姿估计

针对机器人在非结构化环境下面临的未知物体难以快速稳定抓取的问题,提出一种基于多重几何约束的未知物体抓取位姿估计方法.通过深度相机获取场景的几何点云信息,对点云进行预处理得到目标物体,利用简化的夹持器几何形状约束生成抓取位姿样本.然后,利用简化的力封闭约束对样本进行快速粗筛选.对抓取位姿的抓取几何轮廓进行力平衡约束分析,将稳定的位姿传送至机器人执行抓取.采用深度相机与6自由度机械臂组成实验平台,对不同姿态形状的物体进行抓取实验.实验结果表明,本文方法能够有效应对物体种类繁多、缺乏3维模型的情况,在单目标和多目标场景均具有良好的适用性.     

基于RGB-D融合的密集遮挡抓取检测

针对当前抓取检测模型对密集遮挡物体的检测效果差以及人工数据标注工作量大的问题,提出基于RGB-D图像融合的目标检测与抓取检测分步骤进行的改进方案.新方案支持将单物体图像训练的抓取检测模型直接应用于密集遮挡的多物体图像场景中.首先,考虑到密集遮挡场景下抓取物具有多尺度的特点,提出子阶段路径聚合(SPA)的多尺度特征融合模块,用于丰富RGB-D特征级别融合的目标检测模型SPA-YOLO-Fusion的高维语义特征信息,以便于检测模型定位所有的抓取物;其次,使用基于RGB-D像素级别融合的GR-ConvNet抓取检测模型估计每个物体的抓取点,并提出背景填充的图像预处理算法来降低密集遮挡物体的相互影响;最后,使用机械臂对目标点进行抓取.在LineMOD数据集上对目标检测模型进行测试,实验结果表明SPA-YOLO-Fusion的mAP比YOLOv3-tiny与YOLOv4-tiny分别提高了10%与7%.从实际场景中采集图像制作YODO_Grasp抓取检测数据集并进行测试,结果表明增加背景填充预处理算法的GR-ConvNet的抓取检测精度比原模型提高了23%.     

基于上下文聚合策略的轻量级编/解码抓取位姿检测

针对多样性目标在非结构化环境中的抓取位姿难以估计的问题，提出一种基于上下文聚合策略的轻量级编/解码抓取位姿检测网络。首先，以编/解码网络架构为基础，利用深度可分离卷积层与混洗单元构建目标特征深度分离-融合提取块，减少编码网络参数量，增强网络对抓取区域特征的提取能力；其次，利用双线性插值法和深度可分离卷积层建立深度分离-重构块，在恢复高层特征丢失信息的同时，有效减少解码网络的参数量；最后，针对可抓取区域像素点与目标物体全貌之间的非一致性问题，基于交叉熵辅助损失和自注意力机制，提出一种抓取区域上下文聚合策略，引导网络增强可抓取目标区域特征的表征能力，抑制非抓取像素点的冗余特征。实验结果表明，所提网络在Cornell数据集的图像拆分与对象拆分子集上抓取检测准确率分别可达97.8%与93.8%，单张图像检测速度可达64.93张/秒；在Jacquard数据集上抓取检测准确率可达95.1%，单张图像检测速度可达60.6张/秒。与对比网络相比，所提网络不仅计算量与参数量较小，而且抓取检测的准确率与速度均有明显提升，在真实场景下对9种物体的抓取检测验证中，抓取成功率达到93.3%。     

基于多层级特征的机械臂单阶段抓取位姿检测

针对机械臂对尺寸变换、形状各异、任意位姿的未知物体抓取,提出一种基于多层级特征的单阶段抓取位姿检测算法,将物体抓取位姿检测问题视为抓取角度分类和抓取位置回归进行处理,对抓取角度和抓取位置执行单次预测.首先,利用深度数据替换RGB图像的B通道,生成RGD图像,采用轻量型特征提取器VGG16作为主干网络;其次,针对VGG16特征提取能力较弱的问题,利用Inception模块设计一种特征提取能力更强的网络模型;再次,在不同层级的特征图上,利用先验框的方法进行抓取位置采样,通过浅层特征与深层特征的混合使用提高模型对尺寸多变的物体的适应能力;最后,输出置信度最高的检测结果作为最优抓取位姿.在image-wise数据集和object-wise数据集上,所提出算法的评估结果分别为$95.71$%和$94.01$%,检测速度为58.8FPS,与现有方法相比,在精度和速度上均有明显的提升.     

基于像素分配的文本检测方法研究

针对现有方法在场景文本检测上的不足,提出一种基于像素分配方的场景文本检测方法,并采用了交叉注意力模块和多尺度特征自适应模块来分别在空间和和通道上优化特征提取。为了丰富不同尺度的特征表示,采用多尺度特征自适应模块进行自动分配不同尺度特征的权重。为了有效获取上下文信息,将特征网络提取到的特征送入交叉注意力模块。对每个像素,在其所在的水平路径和垂直路径上收集上下文信息。再通过循环操作,每一个像素便可以在全图范围内获取上下文信息。通过全卷积网络方法,使用多任务学习框架学习文本实例的几何特征,结合多任务学习的结果完成像素到文本框的分配,经过简单处理后重建文本实例的多边形边界框。在任意形状公开数据集Total-text上进行测试,本文方法的召回率、精确率、F值分别为75.71%、89.15%、81.89%,在多方向公开数据集ICDAR2015上也表现良好,经实验得召回率、精确率、F值分别为79.06%、89.24%、83.84%,证明了本文方法的有效性。     

面向目标检测的尺度增强特征金字塔网络

基于特征金字塔网络的目标检测算法没有充分考虑不同目标间的尺度差异以及跨层特征融合过程中高频信息损失问题,使网络无法充分融合全局多尺度信息,导致检测效果不佳.针对这些问题,提出了尺度增强特征金字塔网络.该方法对特征金字塔网络的侧向连接和跨层特征融合方式进行了改进,设计具有动态感受野的多尺度卷积组作为侧向连接来充分提取每一个目标的特征信息,引入基于注意力机制的高频信息增强模块来促进高层特征与底层特征融合.基于MS COCO数据集的实验结果表明,该方法能有效提高各尺度目标的检测精度,整体性能优于现有方法.     

基于未知物体三维点云特征的机器人六自由度抓取

针对非结构化环境中任意位姿的未知物体,提出了一种基于点云特征的机器人六自由度抓取位姿检测方法,以解决直接从点云中获取目标抓取位姿的难题.首先,根据点云的基本几何信息生成抓取候选,并通过力平衡等方法优化这些候选;然后,利用可直接处理点云的卷积神经网络ConvPoint评估样本,得分最高的抓取将被执行,其中抓取位姿采样和评估网络都是以原始点云作为输入;最后,利用仿真和实际抓取实验进行测试.结果表明,该方法在常用对象上实现了88.33%的抓取成功率,并可以有效地拓展到抓取其他形状的未知物体.     

面向交通标志检测的尺度感知双向特征金字塔网络

实时精准的交通标志检测是实现自动驾驶和智能交通的重要技术之一.针对真实智能驾驶场景中背景复杂且交通标志尺度较小,现有的检测方法容易出现错检和漏检等问题,提出一种尺度感知的双向特征金字塔网络,实现复杂交通场景中实时、精准的交通标志检测.首先,为解决微小标志在传统金字塔网络中尺度丢失的问题,通过构建自底向上和自顶向下的双向金字塔网络,循环地学习尺度感知的融合特征;然后引入前景注意力模块和尺度感知损失函数,学习和优化不同尺度下的前景显著特征和关联,实现多尺度前景目标分离;最后,引入轻量级和非轻量级主干卷积网络,可以同时提高模型效率和精度.在真实复杂场景的交通标志数据集TT100K和STSD中的实验结果表明,该方法的检测精度达到了66.7%和60.9%,同时实时检测速率达到了30帧/s.     

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.