Procedure for manipulator inverse kinematics computation and proper pseudoinverse perturbation

In this article, an efficient procedure for the proper pseudoinverse perturbation and the numerical inverse kinematics computation of robot manipulators is presented. The approach is based on solving a linear system of equations and using an original scheme for the appropriate perturbation of the pseudoinverse matrix in the next iteration. The resultant algorithm is tested on the simulation of an industrial robot manipulator. From the results obtained, it is observed that the proposed approach compares favorably with the approaches using a Gaussian elimination procedure and with pseudoinverse robustness based on a manipulability measure.     

On-line system identification algorithm combining stochastic approximation and pseudoinverse

A new algorithm for on-line system identification is presented combining stochastic approximation with the recursive pseudoinverse algorithm for least squares estimation. It is an extension of Clarke's generalized least squares method, and gives unbiased estimates of the parameters even in the presence of large noise. An example of a simulated second-order process compares the proposed method with three earlier methods.     

广义逆在嵌入式大气数据传感系统中的应用

应用广义逆矩阵对嵌入式大气数据传感系统中的算法进行简化,提出了以Moore-Penrose广义逆矩阵为基础的动压、静压和修正参数的改进算法,并对其进行了收敛性分析,最后,应用M atlab软件进行了数字计算验证。计算结果表明:改进算法具有确定的收敛性,由于避免了迭代过程中求解逆矩阵,达到同样的精度所需要的计算时间只相当于原有算法的70%,改进算法可以满足系统的精度、可靠性和实时性要求。     

Order-recursive factorization of the pseudoinverse of a covariancematrix

A numerically reliable algorithm is developed to recursively update the square root of a pseudoinverse matrix using the square root of a lower dimension pseudoinverse matrix. The numerical computations are based on a generalized singular value decomposition which is used to do a canonical correlation analysis. An operation count is given for sequential and parallel implementation of a partitioned order-recursive algorithm. These methods are useful for covariance analysis to determine the contributions due to various modeling errors in the design of a Kalman filter     

Predictive stochastic feedforward-feedback control of a heat exchanger-stirred tank system

An optimal stochastic feedforward-feedback control scheme is implemented on a heat exchanger-stirred tank system using an on-line minicomputer. Because variations in the measured disturbance variable affect the process output (controlled variable) before the compensating action can become effective, the feedforward action must be predictive in nature. Statistical time series models are used to model both the measured and unmeasured disturbances in the system. These stochastic disturbance models and the transfer-function models for the process are identified, fitted and checked using statistical model-building procedures on a set of data collected on-line using the minicomputer. The predictive feedforward-feedback controller is derived from these models. The performance of this control scheme is compared with that of an optimal feedback scheme and the actual on-line performance is shown to conform well to the theoretical predictions     

Dynamic Visual Tracking for Manipulators Using an Uncalibrated Fixed Camera

This paper presents a new controller for controlling a number of feature points on a robot manipulator to trace desired trajectories specified on the image plane of a fixed camera. It is assumed that the intrinsic and extrinsic parameters of the camera are not calibrated. A new adaptive algorithm is developed to estimate the unknown parameters online, based on three original ideas. First, we use the pseudoinverse of the depth-independent interaction matrix to map the image errors onto the joint space of the manipulator. By eliminating the depths in the interaction matrix, we can linearly parameterize the closed-loop dynamics of the manipulator. Second, to guarantee the existence of the pseudoinverse, the adaptive algorithm introduces a potential force to drive the estimated parameters away from the values that result in a singular Jacobian matrix. Third, to ensure that the estimated parameters are convergent to their true values up to a scale, we combine the Slotine-Li method with an online algorithm for minimizing the error between the estimated projections and real image coordinates of the feature points. We have proved asymptotic convergence of the image errors to zero by the Lyapunov theory based on the nonlinear robot dynamics. Experiments have been carried out to verify the performance of the proposed controller.     

Methods of computing weighted pseudoinverse matrices with singular weights

Three iterative processes are constructed and investigated for computing weighted pseudoinverse matrices with singular weights and ML-weighted pseudoinverse matrices. Two of them are based on the decompositions of the weighted pseudoinverse matrix with singular weights into matrix power series, and the third is a generalization of the Schulz method to nonsingular square matrices. Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 150–169, September–October, 1999.     

机器人运动学反解中的奇异点处理

本文研究机器人运动学反解中的奇异点处理问题，给出了机器人微分运动Ｊａｃｏｂｉａｎ矩阵Ｊ（ｑ）条件数的一个上界，并在此基础上提出机器人关节速度阻尼伪逆解方法中阻尼系数的一种自适应调整方法，该方法可以保证在奇异点附近伪逆解的稳定性。     

A generalized pseudoinverse algorithm for unbiased parameter estimation

Unbiased estimates of the parameters of a discrete-time system from noisy measurements of input-output data can be obtained by using a generalized pseudo-inverse algorithm. Because of its recursive nature, the algorithm can be used for on-line identification. Results of simulation are presented comparing this algorithm with earlier methods.     

Spectral domain estimation of autoregressive moving-average models using shuttle iterative methods

An efficient iterative algorithm for the estimation of autoregressive moving-average (ARMA) time series models is presented. The prediction error criterion is transformed into the spectral domain, and the autoregressive (AR) parameters are computed (inner loop) using the Newton iterative steps by fixing the AR parameters. Use of data compression in the form of signal power spectrum (fewer frequency points compared to large data size), application of linear solution methods, and the ease of closed form computation of gradients and Hessian matrix of the optimality criterion result in an efficient estimation algorithm for systems with varied spectral forms. The algorithm is implemented on a PDP 11/35 mini computer, and may be used for on-line monitoring and diagnostics of dynamic processes (nuclear power reactors, chemical industry processes), pattern recognition systems, and evaluation of sensor response time characteristics.     

A Robust Method for the Concurrent Motion Planning of Multi-Manipulators Systems

In this article a robust and simple procedure for the on-line concurrent motion planning of multi-manipulators is presented. The approach is based on solving for each manipulator a linear system of equations taking into account a vector for motion planning, and an original scheme for the appropriate perturbation of the pseudoinverse matrix. This method can pursue simultaneously both motion coordination and singularities prevention in real time in a sensor based environment. These properties make it suitable for fully autonomous or telerobotic systems operations.     

MIC-III--an integrated software package to support experiments using the radioactive microsphere technique

MIC-III is a versatile program system to support gamma spectrometry data management and data collection for experiments using the radioactive microsphere technique. It is mainly written in PASCAL and running on a minicomputer. Hierarchical organ dissection schemes are used for unique classification and identification of samples. For each series of experiments, up to 12 different nuclides and up to 20 different organ dissection schemes can be handled simultaneously. Sample weights are collected on-line and sample radioactivities are measured automatically by gamma spectrometry under process control. The spectra with a resolution of 1022 channels are analyzed using a modified linear regression technique and a strategy to compensate for global spectrum shifts. The spectrum deconvolution algorithm was evaluated by calculating the recovery indices for known nuclide mixtures and compared to the stripping method, matrix method and a linear regression technique using window counts. Recovery values produced by MIC-III are better balanced than those of the other methods. MIC-III showed the smallest dispersion of the recovery index and exhibited least error accumulation in case of spectrum shift. MIC-III computes regional blood flow and arterio-venous shunt, and provides interfaces to customized programs or statistical software packages for further analysis. It has successfully been employed in more than 140 experiments.     

水泥回转窑多因素智能控制系统

针对复杂的水泥回转窑热工过程．提出了一种基于系统运行模式的智能控制算法。依据专家操作模式下。对影响系统各因素的在线测量数据．运用改进聚类分析算法．建立系统的运行模式．并针对每个运行模式在线学习生成一条控制规则。进而自动生成控制规则库．实现复杂的水泥回转窑热工制度的最优控制。     

A fast procedure for manipulator inverse kinematics computation and singularities prevention

In this article, a fast procedure for numerical manipulator inverse kinematics computation and singularities prevention is presented. The approach is based upon solving a linear system and automatically calculating some parameters. These parameters are properly used in either one of two original schemes that are also proposed to induce robustness to the pseudoinverse. Furthermore, here it is also shown how to properly implement one of these schemes in conjunction with a recently developed approach for the singularities prevention of redundant manipulators. The resultant algorithms are tested on the simulation of a planar redundant manipulator. From the results obtained, it is observed that the proposed approach compares favorably with the approaches using a Gaussian elimination procedure and with pseudoinverse robustness based on a manipulability measure.     

Localization and comparison of two free-form surfaces

Comparison of two free-form surfaces based on discrete data points is of paramount importance for reverse engineering. It can be used to assess the accuracy of the reconstructed surfaces and to quantify the difference between two such surfaces. The entire process involves three main steps: data acquisition, 3D feature localization and quantitative comparison. This paper presents models and algorithms for 3D feature localization and quantitative comparison. Complex free-form surfaces are represented by bicubic parametric spline surfaces using discrete points. A simple yet effective pseudoinverse algorithm was developed and implemented for localization. It consists of two iterative operations, namely, constructing a pseudo transformation matrix and point matching. A computing algorithm was developed to compare two such surfaces using optimization techniques. Since this approach does not involve solving non-linear equations for the parameters of positions and orientations, it is fast and robust. The algorithm was implemented and tested with several examples. It is effective and can be used in industry for sculptured surface comparison.     

Adaptive sampling of cumulus clouds with UAVs

This paper presents an approach to guide a fleet of Unmanned Aerial Vehicles (UAVs) to actively gather data in low-altitude cumulus clouds with the aim of mapping atmospheric variables. Building on-line maps based on very sparse local measurements is the first challenge to overcome, for which an approach based on Gaussian Processes is proposed. A particular attention is given to the on-line hyperparameters optimization, since atmospheric phenomena are strongly dynamical processes. The obtained local map is then exploited by a trajectory planner based on a stochastic optimization algorithm. The goal is to generate feasible trajectories which exploit air flows to perform energy-efficient flights, while maximizing the information collected along the mission. The system is then tested in simulations carried out using realistic models of cumulus clouds and of the UAVs flight dynamics. Results on mapping achieved by multiple UAVs and an extensive analysis on the evolution of Gaussian processes hyperparameters is proposed.     

A new way to stabilize discrete-time plants under compact uncertainty

A method is proposed for stabilization of uncertain discrete-time plants of which only compact sets are known to which plant parameters and exogenous perturbations belong. The parametric family of feedbacks is quantified and subsequently a stabilizing feedback is localized on the resultant finite discrete set by using on-line measurements of the state path. This method is termed locatization. Its salient features are quantification and the localization algorithm. Three localization procedures are described which are used under various assumptions on the form of the uncertainty. Solvability conditions are provided for the stabilization problem and estimates of transient processes are reported.     

一种T-S 模型的在线辨识算法

提出一种能通过输入输出数据在线获得T-S模型的结构和参数的辨识算法。首先,对输入空间进行划分,并在线优化子空间的形状和个数;然后,通过RLS更新子模型参数,使各个子模型逼近当前工况的实际系统;当子空间生成或形状发生变化时,调整相应子模型参数和数据矩阵;最后,针对非线性动态系统和煤气炉数据进行仿真实验,验证了所提出算法的有效性。     

Series expansion of weighted pseudoinverse matrices and iterative methods for calculating weighted pseudoinverse matrices and weighted normal pseudosolutions

Weighted pseudoinverse matrices are expanded into matrix power series with negative exponents and arbitrary positive parameters. Based on this expansion, iterative methods for evaluating weighted pseudoinverse matrices and weighted normal pseudosolutions are designed and analyzed. The iterative methods for weighted normal pseudosolutions are extended to solving constrained least-squares problems. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 32–62, January–February 2006.     

异类传感器融合跟踪系统配准偏差的在线补偿

针对多传感器融合跟踪系统的时变配准偏差补偿问题,提出了一种配准偏差的在线估计和补偿算法.该算法首先依据多传感器提供的测量和跟踪信息,建立配准偏差的动态模型,然后利用极小化似然函数结合卡尔曼滤波方法在线估计系统偏差,利用估计的配准偏差,补偿和修正跟踪器的测量信息,实现多传感器的融合跟踪.最后针对异类传感器(雷达、红外)组成的多传感器跟踪系统,给出了应用该方法的仿真结果.