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Obstacle Avoidance for Kinematically Redundant Robot

IFAC-PapersOnLine 2015年第28期48卷 490-495页

作者： WANG, Xinyu YANG, Chenguang CHEN, Junshen MA, Hongbin LIU, Feng School of Automation Beijing Institute of Technology Beijing China State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Centre for Robotics and Neural Systems Plymouth University Plymouth United Kingdom College of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Jiaotong University Beijing China

Manipulator's obstacle avoidance is always a challenging topic in robotics. With the concern of the safety problems in human working environment, an improved obstacle avoidance method is proposed based on the general solution of the inverse kinematic problem of a redundant manipulator. A new obstacle detection method using Kinect R sensor is designed to give a robust obstacle information. By designing a parallel system of the manipulator, the proposed control method is not only to achieve the goal of moving away from the obstacle, but also able to guarantee the robot move back to its original pose. The stability of the closed-loop system is established using Lyapunov direct method to ensure the asymptotic stability of the system. The performance of the simulation results verifies the effectiveness of the proposed obstacle detection algorithm and the obstacle avoidance method. © 2015

关键词： Inverse problems Asymptotic stability Closed loop systems Collision avoidance Inverse kinematics Obstacle detectors Redundant manipulators system stability General solutions Inverse kinematic problems Kinematically Redundant Lyapunov direct method Obstacle detection Parallel system Redundant robot Working environment

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DWT-DCT based individuals identification using robust gait feature images

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第4期8卷 113-124页

作者： Ibrahim Khalilullah, K.M. Hossain, Delowar Hamid, Ekramul Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh Intelligent Robotics Lab Department of Electrical and Electronics System Engineering University of Toyama Japan Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh

Individual identification at a distance using gait features has newly gained growing interest from biometrics researchers. Most of the researchers have been shown that different covariate factors can affect different parts of the human body. In this paper, we propose a new approach that minimizes these difficulties, especially for carrying objects by combining static, dynamic, and part-based features. The Gait Features of the walking sequences are extracted by selecting only four sub bands of the Discrete Wavelet Transform (DWT) of the individual images. Moreover, Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) are implemented to extract lowest and middle frequency components that are used to create robust gait feature images (RGFIs). Then we select effective parts of the body from the Robust Gait Feature Images. After that, these parts of the body are trained using Principal Component Analysis (PCA) and Multiple Discriminant Analysis (MDA) to identify individuals. Experimental result shows promising performance in comparison with other methods. © 2015 SERSC.

关键词： Discrete cosine transforms

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Multi-scale analysis of contextual information within spatio-temporal video volumes for anomaly detection

Multi-scale analysis of contextual information within spatio...

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作者： Li, Nannan Guo, Huiwen Xu, Dan Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781479957514

In this paper, we present a novel approach for video anomaly detection in crowded scenes. The proposed approach detects anomalies based on the contextual information analysis within spatio-temporal video volume. Around each pixel, spatio-temporal volumes are built and clustered to construct the activity pattern codebook. Then, the composition information of the volumes within a large spatiotemporal window is described via a dictionary learned by sparse representation. Furthermore, multi-scale analysis is employed to adapt the size change of abnormal events. Finally, the sparse reconstruction cost is designed to evaluate the abnormal level of an input motion pattern. We demonstrate the efficiency of the proposed method on the existing public available anomaly-detection datasets and the performance comparasion with three existing methods validates that the proposed method detects anomalies more accurately. © 2014 IEEE.

关键词： Statistics

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Multi-scale analysis of contextual information within spatio-temporal video volumes for anomaly detection

Multi-scale analysis of contextual information within spatio...

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IEEE International Conference on Image Processing

作者： Nannan Li Huiwen Guo Dan Xu Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Chinese Academy of Sciences China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

ISBN: (纸本)9781479957521

关键词： Vectors Dictionaries Hidden Markov models Computer vision Trajectory Cameras Feature extraction

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A novel nuclear station inspection robot

A novel nuclear station inspection robot

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International Conference on Information Science and Technology (ICIST)

作者： Qingsong Liu Guohe Wang Yachao Dong Pengfei Liu Jianquan Sun Xinyu Wu Yangsheng Xu China Nuclear Power Technology Research Institute(CNPRI) China Guangdong Provincial Key Lab of Robotics and Intelligent System Chinese Academy of Sciences China Department of Mechanical and Automation Engineering The Chinese University Hong Kong

As a key device in nuclear station, the steam generator is vulnerable to certain kinds of damages, which make it necessary to check the generator annually. However, it is impossible for human to finish the examine because of that the tremendous tubes inside the generator makes its inner space too crowded. In this paper, we introduced a novel designed climbing robot system which is competent to the work. The main part of the robot system is a vehicle which can moves inside the steam generator carrying a PT Arm. Four cameras are installed in the vehicle and PT Arm to send the real time video back for analysis. We built a control panel as the interface for users to control the vehicle and a cabinet as the container of all the processors int the control system. Experiments show that our system works stably inside the steam generator.

关键词： Vehicles Generators Inspection Climbing robots Service robots Electron tubes

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A Novel Nuclear Station Inspection Robot

A Novel Nuclear Station Inspection Robot

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2014 4th IEEE International Conference on Information Science and Technology

作者： Qingsong Liu Guohe Wang Yachao Dong Pengfei Liu Jianquan Sun Xinyu Wu Yangsheng Xu China Nuclear Power Technology Research Institute(CNPRI) Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

关键词： Arm A Novel Nuclear Station Inspection Robot

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A novel feature extracting method for dynamic gesture recognition based on support vector machine

A novel feature extracting method for dynamic gesture recogn...

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International Conference on Information and Automation (ICIA)

作者： Yuanrong Xu Qianqian Wang Xiao Bai Yen-Lun Chen Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences University of Science and Technology of China Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

In this paper, we propose a method based on the SVM algorithm to recognize dynamic hand gestures. The information of motion trajectory is captured by a leap motion in three-dimension space. A new methodology of feature extracting is proposed to guarantee the length of samples being the same. The elements of feature vectors are ranged according to two different criteria: one is the amplitude of the variation of orientation angles, and the other criterion is the order of the appearance of features. Experimental results show that this method can classify the dynamic hand gestures effectively.

关键词： Vectors Trajectory Feature extraction Equations Mathematical model Hidden Markov models Automation

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Dynamic hand gesture early recognition based on Hidden Semi-Markov Models

Dynamic hand gesture early recognition based on Hidden Semi-...

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IEEE International Conference on robotics and Biomimetics

作者： Qianqian Wang Yuanrong Xu Yen-Lun Chen Yong Wang Xinyu Wu University of Science and Technology of China Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong. Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

ISBN: (纸本)9781479973989

Real-time performance can be greatly improved, if the early recognition is implemented. In this paper, a dynamic hand gesture early recognition system is proposed. The system can recognize the gesture before it is completed. Our method is based on the Hidden Semi-Markov Models. Three-dimensional information of the gesture trajectory collected by leapmotion is the main data we used. Experiments on the dataset which we established demonstrate the effectiveness of our method.

关键词： Hidden Markov models Gesture recognition Training Conferences Trajectory Arrays

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HIERARCHICAL ACTIVITY DISCOVERY WITHIN SPATIO-TEMPORAL CONTEXT FOR VIDEO ANOMALY DETECTION

HIERARCHICAL ACTIVITY DISCOVERY WITHIN SPATIO-TEMPORAL CONTE...

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IEEE International Conference on Image Processing

作者： Dan Xu Xinyu Wu Dezhen Song Nannan L Yen-Lun Chen Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Computer Science and Engineering Texas A&M University USA

ISBN: (纸本)9781479923427

In this paper, we present a novel approach for video anomaly detection in crowded and complicated scenes. The proposed approach detects anomalies based on a hierarchical activity pattern discovery framework comprehensively considering both global and local spatio-temporal contexts. The discovery is a coarse-to-fine learning process with unsupervised ways for automatically constructing normal activity patterns at different levels. An unified anomaly energy function is designed based on these discovered activity patterns to identify the abnormal level of an input motion pattern. We demonstrate the efficiency of the proposed method on the UCSD anomaly detection datasets (Ped1 and Ped2) and compare the performance with existing work.

关键词： Visual surveillance video anomaly detection hierarchical discovery energy function Visual surveillance Activity patterns anomaly Videotapes anomaly detection Crowding

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A robotic holder of transcranial doppler probe for CBFV auto-searching

A robotic holder of transcranial doppler probe for CBFV auto...

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International Conference on Information and Automation (ICIA)

作者： Quanli Qiu Xiaoping Yang Jia Liu Pandeng Zhang Xinyu Wu Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen Guangdong China Key Lab of Advanced Manufacturing Technology Harbin Institute of Technology China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR China

ISBN: (纸本)9781479913329

The operational difficulty of Transcranial Doppler (TCD) limits its use in normal clinical settings. We therefore present a robotic arm consists of five degrees of freedom which are achieved by four motors and one extra flexible spring, to assure appropriate pressure on temporal window. With proper control strategies, the robotic arm can move the TCD probe to automatically search temporal window positions. In this paper, we have developed the first full-automatic ambulatory TCD system, evaluated its reliability and efficiency after many experiments. In view of the validation of the instrument in successful experiments, this probe holder is likely to have great impact on future TCD examination.

关键词： Probes DC motors Robots Equations Mathematical model Force Arteries

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