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World Congress on intelligent Control and Automation (WCICA)

作者： Jianhe Lei Liankui Qiu Ming Liu Quanjun Song Yunjian Ge Department of Automation University of Science and Technology Hefei China Institute of Intelligent Machine Chinese Academy and Sciences Hefei China Department of Electrical & Computer Systems Engineering Monash University Melbourne VIC Australia

The static coupling of wrist force sensor is a major influencing factor to its measuring precision. Aiming at resolving the disadvantages such as low decoupling precision of the traditional method, we put forward a nonlinear decoupling method based on neural network. The major idea applied is to use the BP network to realize the mapping from input to output of the sensor. Owing to BP network's good nonlinear mapping ability, the decoupling result can reach an arbitrary precision theoretically. The effectiveness of this method was verified in the calibration of wrist force sensor of a force sensing system for an underwater robot gripper. The decoupling results demonstrate the validation of neural network method

关键词： Neural networks Robot sensing systems Wrist Force sensors Calibration Force measurement Grippers robotics and automation Manipulators Sensor systems

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First results of an automated model-based segmentation system for subcortical structures in human brain MRI data

First results of an automated model-based segmentation syste...

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IEEE International Symposium on Biomedical Imaging

作者： H. Belitz K. Rohr H. Muller G. Wagenknech Central Institute for Electronics Research Center Juelich Germany Dept. Intelligent Bioinformatics Systems University of Heidelberg and DKFZ Heidelberg Germany Department of Computer Science University of Dortmund Germany

We propose an automated model-based approach for segmenting subcortical structures, especially the basal ganglia, from 3D human brain MRI images. Our hybrid approach combines an automatic tissue classification scheme, a landmark detection algorithm and a discrete active surface model (ASM) to achieve its goal. A priori knowledge is incorporated into the different stages of the model and is used to retain shape and neighborhood information about the structures of interest throughout the segmentation process. The system is designed to require as little user interaction as possible. Sample results are given for the Brain Web simulated brain data set and for a real data set

关键词： Brain modeling Humans Magnetic resonance imaging Image segmentation Shape Basal ganglia Deformable models Topology Hybrid intelligent systems intelligent structures

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Movement Pattern Recognition of Weight Lifter Based on Ground Reaction Force

Movement Pattern Recognition of Weight Lifter Based on Groun...

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World Congress on intelligent Control and Automation (WCICA)

作者： Jianhe Lei Ming Liu Jinghua Ma Quanjun Song Liankui Qiu Yunjian Ge Department of Automation University of Science and Technology Hefei China Institute of Intelligent Machine Chinese Academy and Sciences Hefei China Department of Electrical & Computer Systems Engineering Monash University Melbourne VIC Australia

Automatic movement recognition is a crucial part to the development of weight lifter training and evaluating system which uses the kinematic data from video-analyzing and dynamic information for diagnosing weight lifter's performance. Previous works focused mainly on video processing (kinematic data) for analyzing athlete's performance, which needs a tremendous computation. In this paper a novel approach to the problem was investigated, using the vertical component of an athlete's ground reaction force (GRF). Typical movement phases of a weight lifter are decomposed and recognized automatically in terms of the GRF signal measured by a force platform. Support vector machine (SVM) multi-classifier for the recognition of weight lifter's movement phases were implemented and the model parameters were determined by art and science. The classification results demonstrate the validity of SVM-based method

关键词： Pattern recognition Kinematics Force measurement Support vector machines Support vector machine classification Motion analysis Information analysis Machine intelligence Data analysis Performance analysis

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Analysis of GRF by Means of Wavelet Transform for the Performance Diagnosis of Weight Lifter

Analysis of GRF by Means of Wavelet Transform for the Perfor...

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International Conference on Information and Automation (ICIA)

作者： Jianhe Lei Zhen Gao Quanjun Song Ming Liu Liankui Qiu Yong Yu Yunjian Ge Department of Automation University of Science and Technology Hefei China Institute of Intelligent Machine Chinese Academy and Sciences Hefei China Department of Electrical & Computer Systems Engineering Monash University Melbourne VIC Australia

Weightlifting is one of the most physically demanding sports. A successful lift is influenced by many factors. Among them, the ground reaction force (GRF) which is exerted on weight lifers during the motion process is crucial to the performance of a weight lifer, so the acquisition and analysis of GRF is very important to the scientific research of weightlifting. This paper describes GRF acquisition using a force platform and analysis by means of wavelet transform (WT) for the performance diagnosis of weight lifters. The differences of GRF between the skilled weight lifters and the learners are reported. The method allows to detect and to quantify details not easily perceivable by coaches through traditional techniques. By wavelet transform of the GRF, it is possible for biomechanics experts to analysis mechanical behaviours of athletes and to direct them to improve their skills. GRF acquisition and analysis provides a very important tool for modern athletes training.

关键词： Performance analysis Wavelet analysis Wavelet transforms Motion analysis Biomechanics Information analysis Kinematics Pattern analysis Machine intelligence Physics computing

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STEREO VISION-BASED ESTIMATION OF POSE AND MOTION FOR AUTONOMOUS LANDING OF AN UNMANNED HELICOPTER

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International Journal of Information Acquisition 2006年第3期3卷 181-190页

作者： CUI XU MING LIU BIN KONG YUNJIAN GE Department of Automation University of Science and Technology of China Hefei Anhui P. R. China Department of Electrical and Computer Systems Engineering Monash University Melbourne Victoria Australia Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui P. R. China

In this paper, a real-time stereo vision based pose and motion estimation system is presented. It is used for landing an unmanned helicopter on a moving target such as a ship deck. The vision algorithm mainly consists of a feature extraction task and a pose and motion estimation task. By the specially designed pattern of the landing target, the feature extraction algorithm can simplify the step of feature points matching of stereo system. In the task of feature extraction, the step of accurate corner detection can get to the precision of sub-pixel, which helps improve the measurement precision in state estimation. We present results from semi-physical simulation which show that our vision algorithm is accurate and robust to allow our vision sensor to be placed in the control loop of unmanned helicopter management system.

关键词： Stereo vision feature extraction pose and motion estimation unmanned helicopter

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Stereo Vision based Relative Pose and Motion Estimation for Unmanned Helicopter Landing

Stereo Vision based Relative Pose and Motion Estimation for ...

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International Conference on Information and Automation (ICIA)

作者： Cui Xu Liankui Qiu Ming Liu Bin Kong Yunjian Ge Department of Automation University of Science and Technology Hefei Anhui China Center for Biomimetic Sensing and Control Research Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China Department of Electrical and Computer Systems Engineering Monash University Melbourne VIC Australia

In this paper, we present a real-time stereo vision based pose and motion estimation system that will be used for landing an unmanned helicopter on a moving target such as a ship deck. The vision algorithm mainly consists of a feature extraction task and a pose and motion estimation task. The 2D planer target with regular features defined can significantly simplify the feature extraction task such as corner detection and feature points matching. To effectively estimate the distance between the camera carrier and target a stereo camera system is applied. By means of sub-pixel corner location the precisions of pose estimation and relative motion detection can be improved. We present results from semi-physical simulation which show that our vision algorithm is accurate and robust. The methodology provides an effective subsystem for the development of autonomous robot helicopter that will land on a given target under the guide of vision.

关键词： Stereo vision Motion estimation Helicopters Feature extraction Cameras Robot vision systems Real time systems Marine vehicles Metalworking machines computer vision

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Robust Control Design for the Mass-Damper Type Anti-Sway System

Robust Control Design for the Mass-Damper Type Anti-Sway Sys...

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SICE Annual Conference

作者： Young-bok Kim Masao Ikeda Jin-ho Suh Guisheng Zhai Seong-hoon Han Faculty of Mechanical Engineering Pukyong National University Busan South Korea Department of Computer-Controlled Mechanical Systems Osaka University Osaka Japan Pohang Institute of Intelligent Robotics PIRO Pohang South Korea Department of Mechanical Engineering Osaka Prefecture University Osaka Japan Department of Electrical Engineering Graduate School Dong-A University Busan South Korea

In the previous studies, we suggested a new type of swing motion control system for the crane system in which a small auxiliary mass is installed on the spreader. The actuator reacting against the auxiliary mass applies inertial control forces to the spreader of the container crane to reduce the swing motion in the desired manner. In the papers, to identify the usefulness and validity of the proposed system, we applied several control strategies. In the results, good control performance and valuable results had been achieved. In this paper, we evaluate and check the system in the point of more real application. For an example, the transportation process of RTG to handle the cargos is considered. In this case, undesirable sway motion might be occurred. To suppress this motion, a pursueable strategy (approach) is introduced. And, it will be shown that the proposed control strategy is useful and it can be easily applicable to the real world

关键词： Robust control Cranes Motion control Containers Control systems Mechanical engineering intelligent robots Marine vehicles Transportation Mechanical systems

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Multi-Modal Human Verification Using Face and Speech

Multi-Modal Human Verification Using Face and Speech

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IEEE International Conference on computer Vision systems (ICVS)

作者： Changhan Park Joonki Paik Taewoong Choi Soonhyob Kim Youngouk Kim J. Namkung Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Multimedia Signal Processing Laboratory Kwangwoon University Seoul South Korea Precision Machinery Center Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University Seoul South Korea

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time.

关键词： Humans Speech Face detection Face recognition Biometrics Principal component analysis Feature extraction Hidden Markov models Image edge detection Laboratories

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Optimal path planning method for sailing around race marks

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Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University 2006年第2期27卷 161-165页

作者： Xing, Hui-Li Wei, Zhen-Gang Meng, Qing-Chun Ge, Yan Department of Computer Science Ocean University of China Qingdao 266071 China State Key Lab of Intelligent Technology and Systems Tsinghua University Beijing 100084 China Institute of Information Science and Technology Qingdao University of Science and Technology Qingdao 266061 China

Optimal path planning is a key aspect in sailing contests. Proposed is an optimal path planning method for a sailboat sailing around race marks based on section optimization. A two-dimensional model for sailing was used to divide the voyage into several sections and obtain a corresponding coordinate system by a circumvolving and shifting operation. Each section utilized fuzzy comprehensive evaluation methods to find a local optimal path. The global optimal path was determined by reverting to the original coordinates. Simulation results indicate the method's effectiveness and applicability.

关键词： Sailing vessels

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A study on textual entailment

A study on textual entailment

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ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05

作者： Rus, Vasile Graesser, Art McCarthy, Philip M. Lin, King-Ip Department of Computer Science Institute for Intelligent Systems University of Memphis Memphis TN 38152

ISBN: (纸本)0769524885

In this paper we study a graph-based approach to the task of textual entailment between a Text and Hypothesis. The approach takes into account the full lexicosyntactic context of both the Text and Hypothesis and relies heavily on the concept of subsumption. It starts with mapping the Text and Hypothesis into graph structures where nodes represent concepts and edges represent lexico-syntactic relations among concepts. Based on a subsumption score between the Text-graph and Hypothesis-graph an entailment decision is then made. The impact of synonymy on entailment is quantified and discussed. An important advantage of our solution is the ability to customize it so that high-confidence results are obtained. © 2005 IEEE.

关键词： Graph theory

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