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。     

A variational method for contour tracking via covariance matching

This paper presents a novel formulation for contour tracking.We model the second-order statistics of image regions and perform covariance matching under the variational level set framework.Specifically,covariance matrix is adopted as a visual object representation for partial differential equation(PDE) based contour tracking.Log-Euclidean calculus is used as a covariance distance metric instead of Euclidean distance which is unsuitable for measuring the similarities between covariance matrices,because the matrices typically lie on a non-Euclidean manifold.A novel image energy functional is formulated by minimizing the distance metric between the candidate object region and a given template,and maximizing the one between the background region and the template.The corresponding gradient flow is then derived according to a variational approach,enabling partial differential equations(PDEs) based contour tracking.Experiments on several challenging sequences prove the validity of the proposed method.     

Joint spatial registration and multi-target tracking using an extended PM-CPHD filter

An extended product multi-sensor cardinalized probability hypothesis density (PM-CPHD) filter for spatial registration and multi-target tracking (MTT) is proposed. The number and states of targets and the biases of sensors are jointly estimated by this method without the data association. Monte Carlo (MC) simulation results show that the proposed method (i) outperforms, although computationally more expensive than, the extended multi-sensor PHD filter which has been proposed for joint spatial registration and MTT; (ii) outperforms the multi-sensor joint probabilistic data association (MSJPDA) filter which is also extended in this study for joint spatial registration and MTT when the clutter is relatively dense.