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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Weifeng Zhang Zengchang Qin Intelligent Computing and Machine Learning Laboratory School of Automation Science and Electrical Engineering Beihang University China Robotics Institute CMU USA Intelligent Computing and Machine Learning Laboratory School of ASEE Beihang University China

Cluster analysis is the assignment of grouping a set of observations into clusters so that observations in the same cluster are similar in some sense. One of the key features for clustering is how to define a sensible similarity measure. However, classical clustering algorithms have no ability to cluster data instances and imprecise concepts using traditional distance measures. In this paper, we proposed a (dis)similarity measure based on a new knowledge representation framework called label semantics. Based on this new measure, we can automatically cluster data instance and descriptive concepts represented by logical expressions of linguistic labels. Experimental results on a toy problem in image classification demonstrate the effectiveness of the new proposed clustering algorithm. Since the new proposed measure can be extended to measuring distance between any two granularities, the new clustering algorithms can also be extended to clustering data instance and imprecise concepts represented by other granularities.

关键词： Pragmatics Clustering algorithms Semantics Image color analysis Silicon Algorithm design and analysis Humans

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Robust 3D vision for robots using dynamic programming

Robust 3D vision for robots using dynamic programming

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Lazaros Nalpantidis John Kalomiros Antonios Gasteratos Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Department of Informatics and Communications School of Technological Applications Technological Educational Institute of Serres Serres Greece

In this paper a new stereo vision method is presented that combines the use of a lightness-invariant pixel dissimilarity measure within a dynamic programming depth estimation framework. This method uses concepts such as the proper projection of the HSL colorspace for lightness tolerance, as well as the Gestalt-based adaptive support weight aggregation and a dynamic programming optimization scheme. The robust behavior of this method is suitable for the working environments of outdoor robots, where non ideal lighting conditions often occur. Such problematic conditions heavily affect the efficiency of robot vision algorithms in exploration, military and security applications. The proposed algorithm is presented and applied to standard image sets.

关键词： Pixel Stereo vision Lighting Image color analysis Dynamic programming Robots Heuristic algorithms

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Analysis and Design of Attachment Module Based on Sine Vibrating Suction Method for Wall-climbing Robot

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Procedia engineering 2011年 12卷 9-14页

作者： Kun Wang Wei Wang Houxiang Zhang School of Instrumentation Science and Opto-electronics Engineering BeiHang University Beijing 100191 P.R. China Robotics Institute School of Mechanical Engineering and Automation BeiHang University Beijing 100191 P.R. China TAMS Department of Informatics University of Hamburg Vogt-Kölln-Straße 30 Hamburg 22527 Germany

This paper presents an attachment module for mini wall-climbing robot based on sine vibrating suction method. The basic idea of this method is that the vacuum can be generated inside a suction cup attaching on a surface, if a periodically vibrating force directly drives the suction cup. In this paper, mathematical model of sine vibrating suction method based on Bernoulli's equation is built. It is found that the vacuum degree in the suction cup is mainly determined by two parameters, namely the amplitude and frequency. To verify the correctness of the analyses, an experimental platform was developed. The results indicate that the vibrating suction method can definitely produce continuous vacuum. According to the experiment result, an attachment module for wall-climbing robot was developed. Moreover, the validity was verified by a series of suction experiments on different wall. Finally, the feasibility of the attachment module was basically testified on a caterpillar wall-climbing robot.

关键词： Vibrating suction method Attachment module Suction cup Wall-climbing robot Caterpillare robot

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Probing protein-protein interaction forces using single-molecule force spectroscopy

Probing protein-protein interaction forces using single-mole...

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2011 11th IEEE International Conference on Nanotechnology, NANO 2011

作者： Li, Mi Liu, Lianqing Xi, Ning Wang, Yuechao Dong, Zaili Li, Guangyong Xiao, Xiubin Zhang, Weijing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100049 China Department of Electrical and Computer Engineering Michigan State University East Lansing MI 48824 United States Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA 15261 United States Department of Lymphoma Affiliated Hospital Military Medical Academy of Sciences Beijing 100071 China

ISBN: (纸本)9781457715143

The invention of atomic force microscopy (AFM) provides new technology for measuring the molecular specific binding forces. With the use of AFM single-molecule force spectroscopy (SMFS), the CD20-rituximab binding forces were measured on purified CD20 proteins (CD20 segment protein and CD20 full-length protein) and on Burkitt's lymphoma Raji cells, respectively. With AFM probe functionalization technology, rituximabs were linked onto AFM tips. With substrate functionalization technology, purified CD20 segment proteins and CD20 full-length proteins were attached onto mica. Lymphoma Raji cells were immobilized onto glass substrate with electrostatic adsorption and chemical fixation. The differences of measuring the binding forces on purified proteins and on cells were analyzed. The experimental results indicate that the binding force between CD20 segment protein and rituximab were markedly larger than that of CD20 full-length protein and CD20 protein on lymphoma cells, providing an effective method for investigating the rituximab's mechanism. © 2011 IEEE.

关键词： Proteins

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Industrial fault detection and isolation using Dominant Feature Identification

Industrial fault detection and isolation using Dominant Feat...

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Asian Control Conference

作者： Chee Khiang Pang Jun-Hong Zhou Zhao-Wei Zhong Frank L. Lewis Department of Electrical and Computer Engineering National University of Singapore Singapore ASTAR Singapore Institute of Manufacturing Technology Singapore School of Mechanical and AeroSpace Engineering Nanyang Technological University Singapore Automation & Robotics Research Institute University of Texas Arlington Fort Worth TX USA

ISBN: (纸本)9781612844879

In this paper, we show how to find a reduced feature subset which is optimal in both estimation and clustering least square errors using two new Dominant Feature Identification (DFI) methods. We apply DFI to to identify the important features in a given set of faults, and a Neural Network (NN) is used for online fault classification based on the determined reduced feature set in the proposed two-stage framework. Our experimental results on an industrial machine fault simulator show the effectiveness in fault diagnosis and classification. Accuracy of 99.4% for fault identification is observed when using proposed new DFI followed by NN classification, reducing the number of required features from 120 to 13 and the number of sensors from 8 to 4.

关键词： Artificial neural networks Feature extraction Harmonic analysis Sensor phenomena and characterization Fault detection Torque

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An on-board pan-tilt controller for ground target tracking systems

An on-board pan-tilt controller for ground target tracking s...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： Zhekui Xin Yongchun Fang Bin Xian Beijing AeroSpace Automatic Control Institute China Institute of Robotics and Information Automatic System Nankai University Tianjin China Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin China

For a ground target tracking system using an unmanned helicopter, an on-board pan-tilt controller is proposed to adjust the attitude of the camera, so that to keep the target staying at the center of the image plane when the target is in sight. When the target is temporarily out of view due to various reasons, the designed controller will make the camera quickly re-capture the target by estimating its state and then regulating the orientation of the camera correspondingly. Specifically, a novel state transformation is firstly introduced to make the error system independent of the target image. Subsequently, a nonlinear pan-tilt controller is designed for the transformed error system. Lyapunov techniques are then employed to prove that the target tracking error in the image plane is driven to zero exponentially fast. To facilitate the implementation of the constructed controller, a visual estimator is also utilized to obtain the state information of the target even if it is occasionally out of the view of the camera by introducing an effective nonlinear filter. Simulation results are provided to validate the performance of the presented control system.

关键词： Target tracking Cameras Helicopters Jacobian matrices Visualization Robot vision systems

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Homography-based ground area detection for indoor mobile robot using binocular cameras

Homography-based ground area detection for indoor mobile rob...

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IEEE Conference on robotics, automation and Mechatronics

作者： Peiqi Ke Cai Meng Jihao Li Ying Liu Image Processing Center School of Astronautics Beihang University Beijing 100191 China Social Robotics Lab Interactive Digital Media Institute National University of Singapore 119613 Singapore Mechatronics Engineering Department School of Mechanical Engineering Beijing University of Science Technology 100083 China Industrial Robot & Production Automation Lab School of Mechanical Engineering University of Science & Technology Beijing 100083 China

Drivable area detection is an important issue for mobile robot to work in indoor and outdoor environments with safety and security with respect to itself and environment. In this paper, we propose an approach to detect the ground area for indoor mobile robots with binocular cameras. At first, the ground induced homography between onboard binocular cameras is calibrated. In ground area detection, the right eye image is warped to left eye by the homography and subtracted by the left eye image. From the difference image the rough non-ground regions can be detected. Then the closed contours on the difference image and the left eye image are searched to segment them into regions. These corresponding regions are compared to judge whether they belong to ground plane. The conducted experiments show that the proposed method is valid in detecting ground area.

关键词： Mobile robots Cameras Conferences automation Image segmentation Robot vision systems

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Modeling and Optimization of An Ultrasonic Setup Based on Combination of Finite Element Method And Mathematical Full Factorial Design

Modeling and Optimization of An Ultrasonic Setup Based on Co...

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The 2011 International Conference on Key engineering Materials and Computer Science(KEMCS 2011)

作者： Nick Javad Akbari Mohamad.R Movahhedy S.Mehdi Hoseini Graduate Student School of Mechanical EngineeringSharif University of TechnologyTehranIran.Mohsen Ghahramani Associate Professor Centre of Ecellence in DesignRobotics and AutomationSchool of Mechanical EngineeringSharif University of TechnologyTehranIran. Professor School of Mechanical EngineeringSharif University of TechnologyTehranIran. Graduate Student Islamic Azad UniversityScience and Research BranchTehranIran.

Ultrasonic assisted machining(UAM) is an efficient nontraditional machining operation for brittle, hard-to-cut and poor-machinability materialsIn UAM, high frequency oscillation in ultrasonic range at low amplitude is imposed on the workpiece or cutting toolIn most cases, the equipments that generates and transfers the vibration, have a complicated structure, and requires significant effort to achieve their optimum functionIn this work, a mathematical model is developed and an optimization method is employed for design processThis makes it possible to achieve proper setup and reduce the amount of calculationFor this purpose, the combination of a two level full factorial design is performed with data that are obtained from finite element model(FEM)are usedBased on the mathematical model, an objective function is defined with the objective of maximizing the vibration amplitude at longitudinal resonance frequency of 22 k *** algorithm is used to optimize the design parameters according to the defined objective functionThe obtained results are shown just an error about 0.03 percent between FEM modal analysis and mathematical model answerThe advantages of the proposed optimization method in ultrasonic setup design in case of complicated geometries is discussedTherefore optimization methods via FEM data could be regarded as an efficient approach for design of complicated structures.

关键词： Optimization,Ultrasonic Vibration,Genetic Algorithm,Finite Element Analysis,Mathematical Model

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Hierarchical Projected Regression for Torque of Elbow Joint Using EMG Signals

Hierarchical Projected Regression for Torque of Elbow Joint ...

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International Conference on Bioinformatics and Biomedical engineering (ICBBE)

作者： Yang Chen Qichuan Ding Xingang Zhao Jianda Han School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

Predicting Torque by using Electromyography (EMG) signals is a significant problem as long as wearable robots is concerned. In this paper, a coarse-to-fine algorithm, named as Hierarchical Projected Regression, is proposed to estimate the torque of elbow by the surface EMG signals from human's arm. HPR is learned based on a clinical dataset. First, the real torque distribution can be clustered by k-means algorithm. Meanwhile, the EMG signals are divided into multi-clusters corresponding to the partitions of torque dataset. Then, a projected matrix is derived based on the criterion of Linear Discriminant Analysis, by which the low dimensional features are extracted from the original high dimensional EMG. Finally, the process extends to multi-level tree algorithm based on the hierarchical variance reduction of individual torque cluster. The experimental results show the high accuracy and efficiency of this novel method.

关键词： Torque Electromyography Joints Robots Digital filters Muscles Artificial neural networks

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Retraction notice to “Dynamic analysis of geometrically nonlinear and electrostatically actuated micro-beams” [Commun Nonlinear Sci Numer Simulat 14 (4) (2009) 1627–1645]

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Communications in Nonlinear Science and Numerical Simulation 2011年第1期16卷 602-602页

作者： Ahmadian M T Borhan H Esmailzadeh E Centre of Excellence for Design Robotics and Automation School of Mechanical Engineering Sharif University of TechnologyIran Iran Tehran

This article has been removed at the request of the authors and the Editors-in-Chief.

关键词： Dynamic analysis geometrically nonlinear electrostatically actuated micro-beams

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