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2014中国制导、导航与控制学术会议

作者： Qingji Gao Zheng chao Zeng Dandan Hu Computer Science and Technology Robotics InstituteCivil Aviation University of ChinaTianjin 300300China School of navigation guidance and control on aviation institute of automationCivil aviation university of ChinaTianjin300300 China Control Theory and Control EngineeringRobotics InstituteCivil Aviation University of ChinaTianjin 300300China

ISBN: (纸本)9781479946983

The 7th IARC (international aerial robot competition) focus on a long-term and real-time tracking of ground moving target for UAV (unmanned aerial vehicle).This paper proposes a tracking method using Camshift algorithm with color and edge features fusion,which will apply a Phash target detection algorithm basing on perceptual hash *** targets are severely obscured or disappear from view,which will lead tracking failure,whereas targets can be detected and obtained again using the *** results demonstrate that this method can provide a long-term and real-time tracking of ground moving target,which processes both robustness and computational efficiency.

关键词： UAV Target tracking Camshift Perceptual hash algorithm

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Deep joint task learning for generic object extraction 14

Deep joint task learning for generic object extraction

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Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1

作者： Xiaolong Wang Liliang Zhang Liang Lin Zhujin Liang Wangmeng Zuo Sun Yat-sen University Guangzhou China and The Robotics Institute Carnegie Mellon University Pittsburgh Sun Yat-sen University Guangzhou China Sun Yat-sen University Guangzhou China and SYSU-CMU Shunde International Joint Research Institute Shunde China School of Computer Science and Technology Harbin Institute of Technology China

This paper investigates how to extract objects-of-interest without relying on handcraft features and sliding windows approaches, that aims to jointly solve two sub-tasks: (i) rapidly localizing salient objects from images, and (ii) accurately segmenting the objects based on the localizations. We present a general joint task learning framework, in which each task (either object localization or object segmentation) is tackled via a multi-layer convolutional neural network, and the two networks work collaboratively to boost performance. In particular, we propose to incorporate latent variables bridging the two networks in a joint optimization manner. The first network directly predicts the positions and scales of salient objects from raw images, and the latent variables adjust the object localizations to feed the second network that produces pixelwise object masks. An EM-type method is presented for the optimization, iterating with two steps: (i) by using the two networks, it estimates the latent variables by employing an MCMC-based sampling method; (ii) it optimizes the parameters of the two networks unitedly via back propagation, with the fixed latent variables. Extensive experiments suggest that our framework significantly outperforms other state-of-the-art approaches in both accuracy and efficiency (e.g. 1000 times faster than competing approaches).

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Teachers' views on the use of empathic robotic tutors in the classroom

Teachers' views on the use of empathic robotic tutors in the...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Sofia Serholt Wolmet Barendregt Iolanda Leite Helen Hastie Aidan Jones Ana Paiva Asimina Vasalou Ginevra Castellano Department of Applied Information Technology University of Gothenburg Gothenburg Sweden GAIPS Instituto Superior Tecnico Lisboa Portugal Social Robotics Lab Yale University New Haven CT USA School of Mathematical and Computer Science Heriot-Watt University Edinburgh UK School of Electronic Electrical and Computer Engineering University of Birmingham Birmingham UK London Knowledge Lab Institute of Education London UK

ISBN: (纸本)9781479967667

In this paper, we describe the results of an interview study conducted across several European countries on teachers' views on the use of empathic robotic tutors in the classroom. The main goals of the study were to elicit teachers' thoughts on the integration of the robotic tutors in the daily school practice, understanding the main roles that these robots could play and gather teachers' main concerns about this type of technology. Teachers' concerns were much related to the fairness of access to the technology, robustness of the robot in students' hands and disruption of other classroom activities. They saw a role for the tutor in acting as an engaging tool for all, preferably in groups, and gathering information about students' learning progress without taking over the teachers' responsibility for the actual assessment. The implications of these results are discussed in relation to teacher acceptance of ubiquitous technologies in general and robots in particular.

关键词： Educational institutions Interviews Robot sensing systems Service robots Europe

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Neural control of unknown non-affine systems by state and output feedback

Neural control of unknown non-affine systems by state and ou...

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3rd IFAC Conference on Intelligent Control and Automation science, ICONS 2013

作者： He, Wei Deng, Dan Tang, Zhong-Liang Robotics Institute School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute of Intelligent Systems and Information Technology School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

ISBN: (纸本)9783902823458

In this paper, we consider the unknown non-affine nonlinear systems with the input deadzone and external disturbance. To solve the deadzone effects, a Radial Basis Function Neural Network (RBFNN) is introduced to approximate the deadzone effects and improve the robustness of the system. Moreover, we estimate the disturbance in another RBFNN. Based on the Lyapunov stability analysis and the support of high-gain observer, the adaptive neural network control is developed via both full-state feedback and output feedback. Simulation studies are proposed to illustrate the control performance. The semiglobally uniform boundedness is guaranteed in the closed-loop systems under the proposed control. Copyright © 2013 IFAC.

关键词： Dead zones

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Predicting the Speed of a Wave Glider Autonomous Surface Vehicle from Wave Model Data

Predicting the Speed of a Wave Glider Autonomous Surface Veh...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Phillip Ngo Jnaneshwar Das Jonathan Ogle Jesse Thomas Will Anderson Ryan N. Smith School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane QLD 4001 Australia Robotic Embedded Systems Laboratory University of Southern California Los Angeles CA USA Physics and Engineering Department Fort Lewis College Durango CO USA Liquid Robotics Inc. Sunnyvale CA USA

ISBN: (纸本)9781479969357

A key component of robotic path planning for monitoring dynamic events is reliable navigation to the right place at the right time. For persistent monitoring applications (e.g., over months), marine robots are beginning to make use of the environment for propulsion, instead of depending on traditional motors and propellers. These vehicles are able to realize dramatically higher endurance by exploiting wave and wind energy, however the path planning problem becomes difficult as the vehicle speed is no longer directly controllable. In this paper, we examine Gaussian process models to predict the speed of the Wave Glider autonomous surface vehicle from observable environmental parameters. Using training data from an on-board sensor, and wave parameter forecasts from the WAVEWATCH III model, our probabilistic regression models create an effective method for predicting Wave Glider speed for use in a variety of path planning applications.

关键词： Ground vehicles Path planning Vehicle speed speed Crucial components A wave

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Control of a three-dimensional string system

Control of a three-dimensional string system

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3rd IFAC Conference on Intelligent Control and Automation science, ICONS 2013

作者： He, Wei Zhang, Shuang Robotics Institute School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore

ISBN: (纸本)9783902823458

In this paper, the control design and stability analysis are presented for a three-dimensional string system with the payload dynamics. A set of partial-ordinary differential equations (PDEs-ODEs) are developed by using the Hamilton's principle to describe the motion of the three-dimensional string system. The dynamic model considers the comprehensive effects of environmental loads, which are critical for the analysis of a string system. Based on the Lyapunov's direct method and the properties of the string system dynamics, three boundary control inputs are applied at the boundary to suppress the vibrations of the system under the external disturbances. Uniformly boundedness of the three-dimensional dynamics with the proposed control is achieved. Exponential stability is proved via the Lyapunov's direct method when there is no distributed disturbance. Simulation examples are provided by using the finite difference method, and some useful conclusions are drawn. Copyright © 2013 IFAC.

关键词： Partial differential equations

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Learning control for a robotic manipulator with input saturation

Learning control for a robotic manipulator with input satura...

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3rd IFAC Conference on Intelligent Control and Automation science, ICONS 2013

作者： He, Wei Xiao, Shengtao Yu, Sijia Robotics Institute School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore

ISBN: (纸本)9783902823458

In this paper, adaptive neural-network control is designed for an n-DOF robotic manipulator system. In the tracking control design, both uncertainties and input saturation are considered. Stability of the closed-loop system is analyzed via the Lyapunov's direct method. The uncertain system is approximated by the radial basis function neural-networks (RBFNN) and the input saturation is solved by adding an auxiliary signal. Simulation studies are conducted to examine the effectiveness of the proposed model-based and RBFNN control. Copyright © 2013 IFAC.

关键词： Radial basis function networks

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Approximation-based control of an uncertain robot with output constraints

Approximation-based control of an uncertain robot with outpu...

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3rd IFAC Conference on Intelligent Control and Automation science, ICONS 2013

作者： Zhang, Shuang Xiao, Shengtao Ge, Weiliang Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Robotics Institute School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China

ISBN: (纸本)9783902823458

In this paper, we consider the problem of tracking a desired trajectory for an uncertain robot in the presence of constraints and uncertainties. The dynamics of the uncertain robot are represented by an n-link rigid robotic manipulator. To deal with the system uncertainties and disturbances, the adaptive neural networks are used to approximate the unknown model of the robot and handle the unknown disturbance. Uniform ultimate boundedness of the closed loop system is guaranteed by using a Barrier Lyapunov Function (BLF). Extensive simulations for a robot with constraints are carried out to illustrate the effectiveness of the proposed control. Copyright © 2013 IFAC.

关键词： Lyapunov functions

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Constructing hierarchical visual tree for discriminative image representation and classification

Constructing hierarchical visual tree for discriminative ima...

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14th Pacific-Rim Conference on Multimedia, PCM 2013

作者： Lei, Hao Zhou, Ning Mei, Kuizhi Dong, Peixiang Fan, Jianping Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an 710049 China School of Information Science and Technology Northwest University Xi'an 710069 China Department of Computer Science University of North Carolina Charlotte NC 28223 United States

ISBN: (纸本)9783319037301

To support large-scale visual recognition, it is critical to train a large number of classifiers with high discrimination power. To achieve this task, in this paper a hierarchical visual tree is constructed for organizing a large number of object classes and image concepts according to their inter-concept visual correlations. Based on the hierarchical visual tree, a novel approach is proposed for learning multi-scale group-based dictionary to support discriminative bag-of-visual-words (BoW-based) image representation. In addition, a structural learning approach is developed to enable large-scale classifier training over such hierarchical visual tree. We have also compared the performance of our hierarchical visual tree with traditional label tree over large-scale image collections. © Springer International Publishing Switzerland 2013.

关键词： Image classification

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Neural Control of Unknown Non-Affine Systems by State and Output Feedback

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IFAC Proceedings Volumes 2013年第20期46卷 224-229页

作者： Wei He Dan Deng Zhong-Liang Tang Robotics institute and School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute of Intelligent Systems and Information Technology and School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

关键词： Non-affine nonlinear system Input Deadzone Radial Basis Function Neural Network (RBFNN) Lyapunov direct method

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