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International Conference on Intelligence Engineering Systems

作者： A. Cichon E. Szlachcic J. F. Kotowski Institute of Computer Engineering Control and Robotics Wroclaw University of Technology

ISBN: (纸本)9781424476527

In the paper an adapted version of the differential evolution algorithm has been created to solve a multi-objective optimization problem. Multi-objective Differential Evolution Algorithm using vector differences for perturbing the vector population with self adaptation is introduced. Through the combination of mutation strategies and self adaptation of crossover and differentiation constants the proposed MO algorithm performs better than the one with the simple DE scheme in terms of computation speed and quality of the generated multi-objective non-dominated solutions.

关键词： Multi-objective optimization Differential evolution Self adaptation Learning process

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Constrained robot motion planning: Imbalanced Jacobian algorithm vs. optimal control approach

Constrained robot motion planning: Imbalanced Jacobian algor...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Mariusz Janiak Krzysztof Tchon´ Institute of Computer Engineering Control and Robotics Wroclaw Institute of Technology Wroclaw Poland Poland Institute of Computer Engineering Control and Robotics Wrocław Institute of Technology Wrocław Poland

We address the motion planning problem in non-holonomic robotic systems with constraints imposed on configuration and control variables. The imbalanced Jacobian motion planning algorithm is compared with the optimal c... 详细信息

关键词： Jacobian matrices Planning Mobile robots Heuristic algorithms Optimal control Optimization

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New trends in optimization

New trends in optimization

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IEEE International Conference on Intelligent Engineering Systems (INES)

作者： Czeslaw Smutnicki Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

Summary form only given. Approaches used to solve optimization tasks generated in problems of control, planning, designing and management have completely changed during recent years. Cases with unimodal, convex, differentiable scalar goal functions have disappeared from research labs, because a lot of satisfactory efficient methods were developed. On the battle square there have remained hard cases: multimodal, multi-criteria, non-differentiable, NP-hard, discrete, with huge dimensionality. These practical tasks, generated by industry and market, have caused serious troubles in seeking global optimum. Main reasons of these troubles are recognized as: huge cardinality of local extremes frequently with the exponential number of extremes; curse of dimensionality; NP-hardness; lack of differentiability. Unfortunately, known “classical” exact solution methods have considered as rather weak in so hard conditions of the work. From the beginning of eighties have been observed fast development of approximate methods, resistant to local extremes. In fact, practice of these methods antecede development of the suitable theory, which has been formed usually 10-15 years later than the time moment of creating the approach. That's why we observe now more than 20 different approaches inspired by Nature and more than 30 if we include parallel computing environments. The paper presents critical survey of methods, approaches and trends observed in modern optimization, focusing on nature-inspired techniques recommended for particularly hard problems. Applicability of the methods, depending the class of stated optimization task and classes of goal function, have been discussed. Numerical as well theoretical properties of these algorithms are shown. Newest our own very efficient proposals are also provided.

关键词： Design optimization Optimization methods control engineering computing Design engineering Robot control Technology planning Technology management Engineering management Parallel processing Proposals

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Improving efficiency of the Newton algorithm of motion planning for robot manipulators

Improving efficiency of the Newton algorithm of motion plann...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Ignacy Duleba Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

In this paper a method to speed up a convergence of the Newton algorithm of motion planning for manipulators was presented. The method couples one dimensional optimization (with respect to a coefficient influencing the convergence property of the algorithm) with a virtual goal replacing a real goal of the planning. The first modification of the basic Newton algorithm can be used for any taskspace while the second one works only for low dimensional (not greater than 3) taskspaces. An algorithm based on the method was provided and its efficiency was illustrated on a planar double pendulum manipulator.

关键词： Jacobian matrices Manipulators Planning Kinematics Optimized production technology

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Multistage classification of signals with the use of multiscale wavelet representation

Multistage classification of signals with the use of multisc...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Urszula Libal Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal coefficients. The hierarchical construction of wavelet multiresolution analysis was an inspiration for the multistage classification rule. The algorithm makes an optimal decision for every set of coefficients and its main advantage is a smaller dimension of classification problem on every stage.

关键词： Manganese Heart Databases Diseases Classification algorithms Probability density function Signal representations

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Towards constrained motion planning of mobile manipulators

Towards constrained motion planning of mobile manipulators

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IEEE International Conference on robotics and Automation (ICRA)

作者： Mariusz Janiak Krzysztof Tchoń Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

This paper addresses a constrained motion planning problem for mobile manipulators. The constraints are included into the system model by means of a sort of penalty function, and then processed in accordance with the endogenous configuration space approach. Main novelty of this paper lies in deriving a constrained Jacobian motion planning algorithm with the following features: inequality constraints are included into an extended kinematics model using a smooth approximation of the plus function, the model is then regularized against singularities, and the resulting imbalance in error equations is handled as a perturbation of an exponentially stable linear dynamic system. The operation of the constrained motion planning algorithm is illustrated by a motion planning problem of a mobile manipulator with bounds imposed on a platform variable. Performance of the algorithm is tested by computer simulations.

关键词： Kinematics Jacobian matrices Motion planning control systems Space technology Manipulator dynamics End effectors Motion control robotics and automation USA Councils

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Towards identifying software project clusters with regard to defect prediction 10

Towards identifying software project clusters with regard to...

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Proceedings of the 6th International Conference on Predictive Models in Software Engineering

作者： Jureczko, Marian Madeyski, Lech Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wybrzeze Wyspiańskiego 27 50-370 Wroclaw Poland Institute of Informatics Wroclaw University of Technology Wybrzeze Wyspiańskiego 27 50-370 Wroclaw Poland

ISBN: (纸本)9781450304047

Background: This paper describes an analysisthat was conducted on newly collected repository with 92 versions of 38 proprietary, open-source and academic projects. A preliminary study perfomed before showed the need for a further in-depth analysis in order to identify project clusters. Aims: The goal of this research is to perform clustering on software projects in order to identify groups of software projects with similar characteristic from the defect prediction point of view. One defect prediction model should work well for all projects that belong to such group. The existence of those groups was investigated with statistical tests and by comparing the mean value of prediction efficiency. Method: Hierarchical and k-means clustering, as well as Kohonen's neural network was used to find groups of similar projects. The obtained clusters were investigated with the discriminant analysis. For each of the identified group a statistical analysis has been conducted in order to distinguish whether this group really exists. Two defect prediction models were created for each of the identified groups. The first one was based on the projects that belong to a given group, and the second one - on all the projects. Then, both models were applied to all versions of projects from the investigated group. If the predictions from the model based on projects that belong to the identified group are significantly better than the all-projects model (the mean values were compared and statistical tests were used), we conclude that the group really exists. Results: Six different clusters were identified and the existence of two of them was statistically proven: 1) cluster proprietary B - T=19, p=0.035, r=0.40;2) cluster proprietary/open - t(17)=3.18, p=0.05, r=0.59. The obtained effect sizes (r) represent large effects according to Cohen's benchmark, which is a substantial finding. Conclusions: The two identified clusters were described and compared with results obtained by other researchers

关键词： Statistical tests

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Modeling and analyzing nano-rod pushing with an AFM

Modeling and analyzing nano-rod pushing with an AFM

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2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Hou, Jing Wu, Chengdong Liu, Lianqing Wang, Zhidong Dong, Zaili Dept. of Electrical and Computer Engineering Northeastern University Shenyang 110004 China State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Dept. of Advanced Robotics Chiba Institute of Technology Chiba Japan School of Information and Control Engineering Shenyang Jianzhu University Shenyang 110168 China

ISBN: (纸本)9781424470334

In developing nano-devices and nano-structures, traditional methodologies on MEMS meet the difficulty from the scale restriction. With the strategy of objects assembly, using AFM to handle nano-rods and other nano-objects is considered as an important and high potential technology in constructing nanostructures. However most of AFM only has one tip as the end effector and cannot control both translational and rotational motions during manipulation, this makes it be difficult to realize posture controllable manipulation especially in nano environment. In this paper, the behavior of nano-rod under pushing is theoretically analyzed and modeled. Viscous friction is incorporated in the model and the two situations that the pivot of the nanorod is either inside or outside the rod are addressed. By modeling, the pivot can be determined at each manipulation in real time, and the pushing points can be planned to realize posture controllable manipulation by using nano-hand strategy which is inspired by stable pushing theory of object manipulation in macro world, and to improve the reliability and the precision of manipulation. ©2010 IEEE.

关键词： Nanorods

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Application of adaptive neural network to dishwasher operation control

Application of adaptive neural network to dishwasher operati...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Michał Podgórski Institute of Computer Engineering Control and Robotics Wrołcaw University of Technology Wroclaw Poland

The paper presents adaptive neural network based controller of dishwasher. It shows how to prepare input data for training networks and presents the simulation of network performance.

关键词： Neurons Robot sensing systems Artificial neural networks Smoothing methods Computational modeling Adaptation model Mathematical model

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Wiener-Hammerstein system identification with non-Gaussian input

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IFAC Proceedings Volumes 2010年第10期43卷 106-111页

作者： Grzegorz Mzyk The Institute of Computer Engineering Control and Robotics Wroclaw University of Technology 50-370 Wroclaw Poland tel: +48 71 320 32 77

The paper addresses the problem of non-parametric estimation of the static characteristic in Wiener-Hammerstein (sandwich) system excited and disturbed by random processes. A new, kernel-like method is presented. The proposed estimate is consistent under small amount of a priori information. An IIR dynamics, non-invertible static non-linearity, and non-Gaussian excitations are admitted. The convergence of the estimate is proved for each continuity point of the static characteristic and the asymptotic rate of convergence is analysed. The results of computer simulation example are included to illustrate the behaviour of the estimate for moderate number of observations.

关键词： Wiener-Hammerstein system nonparametric identification kernel estimate convergence analysis

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