Singularity loci of planar parallel manipulators with revolute actuators

The determination of the singularity loci of planar parallel manipulators is addressed in this paper. The inverse kinematics of two kinds of planar parallel manipulators (a two-degree-of-freedom manipulator and a three-degree-of-freedom manipulator) are first computed and their velocity equations are then derived. At the same time, the branches of the manipulators are distinguished by the introduction of a branch index K_i. Using the velocity equations, the singularity analysis of the manipulators is completed and expressions which represent the singularity of the manipulators are obtained. A polynomial form of the singularity loci is also derived. For the first type of singularity of parallel manipulators, the singularity locus is obtained by finding the workspace limits of the manipulators. For the second type of singularity, the loci are obtained through the solution of nonlinear algebraic equations obtained from the velocity analysis. Finally, the graphical representation of the complete singularity loci of the manipulators is illustrated with examples. The algorithm introduced in this paper allows the determination of the singularity loci of planar parallel manipulators with revolute actuators, which has been elusive to previous approaches.     

Singularity and Slow Convergence of the EM algorithm for Gaussian Mixtures

Singularities in the parameter spaces of hierarchical learning machines are known to be a main cause of slow convergence of gradient descent learning. The EM algorithm, which is another learning algorithm giving a maximum likelihood estimator, is also suffering from its slow convergence, which often appears when the component overlap is large. We analyze the dynamics of the EM algorithm for Gaussian mixtures around singularities and show that there exists a slow manifold caused by a singular structure, which is closely related to the slow convergence of the EM algorithm. We also conduct numerical simulations to confirm the theoretical analysis. Through the simulations, we compare the dynamics of the EM algorithm with that of the gradient descent algorithm, and show that their slow dynamics are caused by the same singular structure, and thus they have the same behaviors around singularities.     

A robust dynamic programming algorithm for motion detection and estimation

A new robust algorithm for motion detection and precise evaluation of the motion vectors of moving objects in a sequence of images is presented. It is well known that the accuracy of estimating motion vectors estimation is limited by smoothness constraints and mutual occlusions of motion segments. The proposed method is a fusion of block-matching motion estimation and global optimization technique. It is robust to motion discontinuity and moving objects occlusions. To avoid some contradictions between global optimization techniques and piece-wise smooth values of sought motion vectors, a hidden segmentation model is utilized. Computer simulation and experimental results demonstrate an excellent performance of the method in terms of dynamic motion analysis. This article was translated by the authors. Mikhail Mozerov received his MS degree in Physics from the Moscow State University in 1982 and his PhD degree in Image Processing from the Institute of Information Transmission Problems, Russian Academy of Sciences, in 1995. He works at the Laboratory of Digital Optics of the Institute of Information Transmission Problems, Russian Academy of Sciences. His research interests include signal and image processing, pattern recognition, digital holography. Vitaly Kober obtained his MS degree in Applied Mathematics from the Air-Space University of Samara (Russia) in 1984, and his PhD degree in 1992 and Doctor of Sciences degree in 2004 in Image Processing from the Institute of Information Transmission Problems, Russian Academy of Sciences. Now he is a titular researcher at the Centro de Investigación Científica y de Educación Superior de Ensenada (Cicese), México. His research interests include signal and image processing, pattern recognition. Iosif A. Ovseyevich graduated from the Moscow Electrotechnical Institute of Telecommunications. Received candidate’s degree in 1953 and doctoral degree in information theory in 1972. At present, he is Emeritus Professor at the Institute of Information Transmission Problems of the Russian Academy of Sciences. His research interests include information theory, signal processing, and expert systems. He is a Member of IEEE, Popov Radio Society.     

Singularity avoidance in robotic manipulators: A differential form approach

We examine the avoidability property of singular configurations in redundant robot kinematics. Using a differential form approach a collection of so-called reduced self-motion dynamical systems is attributed to singular configurations distinguished by coranks. The problem of detecting avoidability/unavoidability is transformed to a stability study of the reduced self-motion systems. Sufficient conditions for avoidability and unavoidability are derived.     

小波变换在信号奇异性检测中的应用

利用小波变换具有良好的时频局部化特征 ,在特定尺度下 ,求解信号小波变换的模极大值 ,从而找到信号奇异点。该方法应用到输油管道的泄漏检测中 ,结果表明 ,能够排除工况干扰 ,识别有用信号 ,及时准确地检测出管道的泄漏故障。     

Optimal design for robust control of uncertain flexible joint manipulators: a fuzzy dynamical system approach

A novel fuzzy dynamical system approach to the control design of flexible joint manipulators with mismatched uncertainty is proposed. Uncertainties of the system are assumed to lie within prescribed fuzzy sets. The desired system performance includes a deterministic phase and a fuzzy phase. First, by creatively implanting a fictitious control, a robust control scheme is constructed to render the system uniformly bounded and uniformly ultimately bounded. Both the manipulator modelling and control scheme are deterministic and not IF-THEN heuristic rules-based. Next, a fuzzy-based performance index is proposed. An optimal design problem for a control design parameter is formulated as a constrained optimisation problem. The global solution to this problem can be obtained from solving two quartic equations. The fuzzy dynamical system approach is systematic and is able to assure the deterministic performance as well as to minimise the fuzzy performance index.     

Task decoupling in robot manipulators

Task decoupling in robotic manipulators implies that there is a subset of joints primarily responsible for the completion of a subset of the manipulator task. In this paper, we take a novel and general view of task decoupling in which we identify link subsystems primarily responsible for completion of a subset of the manipulator task components, which is not necessarily position or orientation. Our analysis leads to the discovery of other decoupled manipulator geometries never identified before, wherein the decoupled system is responsible for a subset of degress-of-freedom involving a hybrid combination of both position and orientation. Closed-form inverse kinematic solutions for these manipulator geometries are therefore guaranteed. Task decoupling also implied singularity decoupling wherein singularities of decoupled subsystems are equivalent to the manipulator singularities. The analysis leads to a novel and efficient method for identifying the singularities and solving the inverse kinematics problem of six-axes manipulators with decoupled geometries. The practicality of the concepts introduced is demonstrated through an industrial robot example involving a hybrid position and orientation decoupling.     

l1鲁棒辨识:最小二乘算法及试验设计

现有的l^1鲁棒辨识方法依赖于观测数据窗的起始时刻因而不能用来辨识时变系统,针对该问题基于最小二乘法提出了一种l^1鲁棒辨识算法．该算法与观测窗的起始时刻无关,可用于时变系统的辨识．证明了当试验输入为持续激励信号时所提出的算法为本质最优算法,进一步证明了周期持续激励序列为最优试验信号,并给出了辨识误差紧界的计算公式．最后利用提出的算法研究了慢时变系统的l^1鲁棒辨识问题．     

A robust algorithm for solution of the fuzzy clustering problem on the basis of the fuzzy joint points method

The approach called the method of Fuzzy Joint Points (FJP) is considered in which the fuzziness of clusterization lies in the detailedness of taking into account properties of elements in forming sets of similar elements. Based on this approach, a new robust variant of the FJP algorithm is proposed. The properties of this FJP algorithm are analyzed and a sufficient condition for the correct recognition of the hidden structure of clusters is proved. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 10–22, January–February 2008.     

An approach to automatic generation of dynamic equations of elastic joint manipulators in symbolic language

This paper describes an approach for automatic generation of the equations of motion of elastic joint manipulators in symbolic language. It is based on a vector-parametrization of the Lie groupSO(3) and uses the Lagrange's formalism to derive the dynamical equations, the final forms of which are like the equations generated by a recursive Newton-Eulerian algorithm. These characteristics together increase the computational efficiency of the algorithm and give a very good insight into the dynamical structure of the system. In addition to this, the inertia matrix is explicitly given in the final equations, which is very important for the applicability of a mathematical model in different fields of control and simulation. The suggested algorithm is therefore quite appropriate for the purposes of robot modeling, identification as well as for the applications in real time simulations and control.     

Vehicle positioning in cell manufacturing systems via robust optimization

Numerous manufacturing companies are taking advantage of material handling systems due to their flexibility, reliability, safety and contribution to the increase of productivity. However, several uncertain parameters such as types of cost, availability of vehicle etc., influence the performance of the material handling system greatly. In recent years, robust optimization has proven to be an effective methodology permitting overcoming uncertainty in optimization models. Robust optimization models work well even when probabilistic knowledge of the phenomenon is incomplete. This paper thus proposes two new zero-one programming (ZOP) models for vehicle positioning in multi-cell automated manufacturing system. Uncertain parameters in these models include cost parameters, travel time between each pair of centers of cells and location of machines, average time required for performing all transports from location of machines and availability of the vehicle. Then, the robust counterpart of the proposed ZOP models is presented by using the recent extensions in robust optimization theory. Eventually, to verify the robustness of the solutions obtained by the novel robust optimization model, they are compared to those generated by the deterministic ZOP model for different test problems.     

小波域中的鲁棒性盲水印算法

提出了自适应的鲁棒性图像水印方案。用密钥选择嵌入的位置,增加水印的安全性,并只对有嵌入要求的图像块进行离散小波变换,这样算法的计算复杂度只与水印容量有关,与宿主图像无关,相对减少了计算的复杂度。在水印嵌入过程中,对相应的有嵌入要求的图像块进行分类来决定不同的嵌入强度,达到了自适应的嵌入要求。为了更好地增加方案的鲁棒性,采用基因算法对阈值进行了优化。实验结果表明,此方案具有很好的透明性,对通常的图像处理具有很好的鲁棒性。     

人体跌倒识别算法研究

为快速有效地获取老人跌倒信息,提出了一种人体跌倒识别算法,以深度序列为基础,通过Kinect提供的骨架关节数据构建人体动作表示模型,将人体动作看作关节运动曲线和速度曲线的集合,引入离散Fréchet距离作为关节运动曲线和速度曲线的相似性测度,使用最近邻(KNN)分类器对动作样本进行分类.在公开数据集SDUFall上进行了实验,结果表明,方法优于已有方法.     

Efficient hyperlink analysis using robust Proportionate Prestige Score in PageRank algorithm

Existing PageRank algorithm exploits the Hyperlink Structure of the web with uniform transition probability distribution to measure the relative importance of web pages. This paper proposes a novel method namely Proportionate Prestige Score (PPS) for prestige analysis. This proposed PPS method is purely based on the exact prestige of web pages, which is applicable to Initial Probability Distribution (IPD) matrix and Transition Probability Distribution (TPD) matrix. This proposed PPS method computes the single PageRank vector with non-uniform transition probability distribution, using the link structure of the web pages offline. This non-uniform transition probability distribution has efficiently overcome the dangling page problem than the existing PageRank algorithm. This paper provides benchmark analysis of ranking methods: PageRank and proposed PPS. These methods are tested with real social network data from three different domains: Social Circle:Facebook, Wikipedia vote network and Enron email network. The findings of this research work propose that the quality of the ranking has improved by using the proposed PPS method compared with the existing PageRank algorithm.     

Effects of restrictive clothing on lumbar range of motion and trunk muscle activity in young adult worker manual material handling

The objective of this study was to examine the effect of wearing restrictive trousers on lumbar spine movement, trunk muscle activity and low back discomfort (LBD) in simulations of manual material handling (MMH) tasks. Twenty-eight young adults participated in the study performing box lifting, liquid container handling while squatting, and forward reaching while sitting on a task chair when wearing tight pants (sizes too small for the wearer) vs. fit pants (correct size according to anthropometry). Each task was repeated three times and video recordings were used as a basis for measuring lumbar range of motion (LRoM). The response was normalized in terms on baseline hip mobility. Trunk muscle activity of rectus abdominis (RA) and erector spinae (ES) muscles were also measured in each trial and normalized. At the close of each trial, participants rated LBD using a visual analog scale. Results revealed significant effects of both pants and task types on the normalized LRoM, trunk muscle activity and subjective ratings of LBD. The LRoM was higher and trunk muscle (ES) activity was lower for participants when wearing tight pants, as compared to fit pants. Discomfort ratings were significantly higher for tight pants than fit. These results provide guidance for recommendations on work clothing fit in specific types of MMH activities in order to reduce the potential of low-back pain among younger workers in industrial companies.     

An EDBoost algorithm towards robust face recognition in JPEG compressed domain

In this paper, we describe a novel multiclass boosting algorithm, EDBoost, to achieve robust face recognition directly in JPEG compressed domain. In comparison with existing boosting algorithms, the proposed EDBoost exploits Euclidean distance (ED) to eliminate non-effective weak classifiers in each iteration of the boosted learning, and hence improves both feature selection and classifier learning by using fewer weak classifiers and producing lower error rates. When applied to face recognition, the EDBoost algorithm is capable of selecting the most discriminative DCT features directly in JPEG compressed domain to achieve high recognition performances. In addition, a new DC replacement scheme is also proposed to reduce the effect of illumination changes. In comparison with the existing techniques, the proposed scheme achieves robust face recognition without losing the important information carried by all DC coefficients. Extensive experiments support the conclusion that the proposed algorithm outperforms all representative existing techniques in terms of boosted learning, multiclass classification, lighting effect reduction and face recognition rates.     

Steady-state behaviors in nonlinear systems with an application to robust disturbance rejection

Despite the widespread intuitive appeal of the concept of steady-state response and its use in shaping the asymptotic behavior of control systems, this concept has only been rigorously defined for finite-dimensional, linear time invariant systems. In this paper, we investigate this concept for nonlinear systems, following some classical developments in nonlinear dynamics. As an application, we show how the concept in question plays a role of paramount importance in the design of control laws for asymptotic tracking and disturbance attenuation.     

A simulation-based genetic algorithm for inventory optimization in a serial supply chain

One of the important aspects of supply chain management is inventory management because the cost of inventories in a supply chain accounts for about 30% of the value of the product. The main focus of this work is to study the performance of a single‐product serial supply chain operating with a base‐stock policy and to optimize the inventory (i.e. base stock) levels in the supply chain so as to minimize the total supply chain cost (TSCC), comprising holding and shortage costs at all the installations in the supply chain. A genetic algorithm (GA) is proposed to optimize the base‐stock levels with the objective of minimizing the sum of holding and shortage costs in the entire supply chain. Simulation is used to evaluate the base‐stock levels generated by the GA. The proposed GA is evaluated with the consideration of a variety of supply chain settings in order to test for its robustness of performance across different supply chain scenarios. The effectiveness of the proposed GA (in terms of generating base‐stock levels with minimum TSCC) is compared with that of a random search procedure. In addition, optimal base‐stock levels are obtained through complete enumeration of the solution space and compared with those yielded by the GA. It is found that the solutions generated by the proposed GA do not significantly differ from the optimal solution obtained through complete enumeration for different supply chain settings, thereby showing the effectiveness of the proposed GA.     

自由角度显示系统下的运动向量算法

为了解决三维运动矢量计算的问题,提出一种算法,这种算法是在静态三维重建的基础上用二维图片计算刚体运动的线性方法,利用QR分解求解线性方程的最小均方误差解,迭代来消除离群值,来得到运动矢量.这种算法不需要摄像机标定,实时性好,有利于视频的流畅显示,实验结果表明,此种算法具有一定的鲁棒性.     

灰度投影在块匹配算法中的应用

运动参数估计在图像配准,电子稳像以及图像拼接中起着很重要的作用,其中块匹配算法是经常使用的一种方法。当平移较大的时候,块匹配算法仍然存在不足,因此本文提出了一种新的算法。首先利用灰度投影法得到相邻两幅图像的平移量,在此基础上再利用块匹配算法进行分块处理。实验说明了此方法的有效性,能够满足一般要求。