一种弧焊机器人实时激光扫描视觉系统

研制了一种小型高精度弧焊机器人实时激光扫描视觉系统，对其各项性能进行了测试，并进行了抗电弧光干扰试验，结果表明，此系统精度高，抗干扰能力强，检测范围宽，能广泛地应秀于机器人和自动化焊接中。     

Real-time accurate hand path tracking and joint trajectory planning for industrial robots (I)

Previously, researchers raised the accuracy for a robot’s hand to track a specified path in Cartesian space mainly through increasing the number of knots on the path and the number of the path’s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot’s hand and does not change the number of the path’s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots. Foundation item: Foundation of the Robotics Laboratory, Chinese Academy of Sciences (No. RL200002) Biography of the first author: TAN Guan-zheng, Dr., professor, born in Oct. 1962, majoring in artificial intelligence, robotics and automation.     

Ranking with uncertain labels and its applications

The techniques for image analysis and classification generally consider the image sample labels fixed and without uncertainties. The rank regression problem studied in this paper is based on the training samples with uncertain labels, which often is the case for the manual estimated image labels. A core ranking model is designed first as the bilinear fusing of multiple candidate kernels. Then, the parameters for feature selection and kernel selection are learned simultaneously by maximum a posteriori for given samples and uncertain labels. The provable convergency Expectation Maximization (EM) method is used for inferring these parameters in an iterative manner. The effectiveness of the proposed algorithm is finally validated by the extensive experiments on age ranking task and human tracking task. The popular FG-NET and the large scale Yamaha aging database are used for the age estimation experiments, and our algorithm outperforms those state-of-the-art algorithms ever reported by other interrelated literatures significantly. The experiment result of human tracking task also validates its advantage over conventional linear regression algorithm. A short version of this paper appeared in ICME07.     

Mutual information based registration of multimodal stereo videos for person tracking

Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and robustly for relatively close range surveillance applications. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the developed algorithm. Using calibrated stereo imagery, we employ maximization of mutual information in sliding correspondence windows that inform a disparity voting algorithm to demonstrate successful registration of objects in color and thermal imagery. Extensive evaluation of scenes with multiple objects at different depths and levels of occlusion shows high rates of successful registration. Ground truth experiments demonstrate the utility of the disparity voting techniques for multimodal registration by yielding qualitative and quantitative results that outperform approaches that do not consider occlusions. A basic framework for multimodal stereo tracking is investigated and promising experimental studies show the viability of using registration disparity estimates as a tracking feature.     

一种识别薄板对接接头的视觉方法

对薄板紧密对接接头的识别问题进行了深入的分析，提出了由照明、自适应局部特征提取、全局特征识别和验证融合在一起的视觉识别方法。它克服了电弧光的干扰，识别结果可靠，可以有效地解决薄板紧密对接接头识别这一难题。     

多坐标系下目标跟踪的联合滤波

针对雷达目标观测和处理在不同的坐标系下完成，本文提出了联合滤波算法来跟踪机动目标。该算法以卡尔曼滤波器为基础，直角坐标系下和极坐标系下的算法相联合，不仅克服了两种坐标系下滤波算法的不足，而且对机动目标有很好的跟踪效果。仿真实验结果表明了该算法的有效性。     

基于奇异值分解的特征跟踪方法

在传统的基于模板匹配的跟踪方法中，均是给定一个模板，然后从图像中各个位置取出一个个与模板大小一致的区域进行相似性度量，找出与模板距离最小的一个区域作为当前模板，以便进行下一步的匹配跟踪工作。在景象匹配和相关跟踪过程中，由于所面临的大多数是变化的场景，实时获取的图像与预存模板之间存在比较大的差异，传统相关匹配方法的应用就会受到限制；而且在跟踪过程中，随时更新模板会造成跟踪性能对扰动过分敏感，从而产生漂移。首先拍摄目标不同角度的图像（尽可能包含目标可能出现的所有情况），构成目标图像训练集合，抽取出特征矩阵，对它进行奇异值分解，构成一个关于目标的多维空间。然后再用匹配方法在全局范围搜索，找出目标的大致位置，并利用收敛方法在确定的大致位置内进行搜索，确定目标的仿射变换系数，从而得到一个目标位置的确切描述。     

强激光热斑形成及其稳定性研究

在论述热点跟踪及其传热机理时将靶材的比热溶、热传导系、在激光的热藕合系数均考虑成温度和时间的函数，又考虑靶材在运动时将激光辐照物体时热点的建立及其稳定情况作一动态数值模拟，为热点跟踪作准备。     

基于模糊聚类的半自动跟踪技术研究

现有半自动跟踪系统将操作员等效为准线性环节,增大了训练的难度和成本,不适应复杂战场环境下多个快速机动目标的选取和跟踪.利用特征提取方法得到视场的“潜在目标”集,引入模糊聚类方法,通过对操作响应进行分类,建立操控意图与目标运动特征之间的关系模型.通过充分的仿真试验,对比研究了跟踪平稳性、快速性、准确性等指标,结果说明该方法能够有效提升整体跟踪性能.     

基于反步自适应神经网络的船舶航迹控制

针对欠驱动船舶在稳定航速条件下轨迹跟踪问题,提出了一种基于自适应神经网络与反步法相结合的控制算法.该算法将实际的欠驱动船舶视为模型完全未知的非线性系统,利用神经网络的函数逼近特性实现控制器中非线性部分的在线估计,采用同时调整输入层-隐层、隐层-输出层间的权值阵的方法进行神经网络权值调整.通过选取积分型Lyapunov函数证明了闭环系统的稳定性.仿真实验表明该控制策略具有良好的跟踪特性,可以实现对期望航迹的精确跟踪.