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13th International Conference on Intelligent Autonomous Systems, IAS 2014

作者： Lui, Sin Ting Peynot, Thierry Fitch, Robert Sukkarieh, Salah Australian Centre for Field Robotics The University of Sydney Sydney Australia School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Australia

ISBN: (纸本)9783319083377

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain. © Springer International Publishing Switzerland 2016.

关键词： Motion planning

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A hybrid biogeography-based optimization method for the inverse kinematics problem of an 8-DOF redundant humanoid manipulator

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Frontiers of Information technology & Electronic Engineering 2015年第7期16卷 607-616页

作者： Zi-wu REN Zhen-hua WANG Li-ning SUN School of Computer Science & Technology Soochow University Suzhou 215021 China Robotics and Microsystems Center Soochow University Suzhou 215021 China

The redundant humanoid manipulator has characteristics of multiple degrees of freedom and complex joint structure, and it is not easy to obtain its inverse kinematics solution. The inverse kinematics problem of a humanoid manipulator can be formulated as an equivalent minimization problem, and thus it can be solved using some numerical optimization methods. Biogeography-based optimization （BBO） is a new biogeography inspired optimization algorithm, and it can be adopted to solve the inverse kinematics problem of a humanoid manipulator. The standard BBO algorithm that uses traditional migration and mutation operators suffers from slow convergence and prematurity. A hybrid biogeography-based optimization （HBBO） algorithm, which is based on BBO and differential evolution （DE）, is presented. In this hybrid algorithm, new habitats in the ecosystem are produced through a hybrid migration operator, that is, the BBO migration strategy and Did/best/I/bin differential strategy, to alleviate slow convergence at the later evolution stage of the algorithm. In addition, a Gaussian mutation operator is adopted to enhance the exploration ability and improve the diversity of the population. Based on these, an 8-DOF （degree of freedom） redundant humanoid manipulator is employed as an example. The end-effector error （position and orientation） and the ＇away limitation level＇ value of the 8-DOF humanoid manipulator constitute the fitness function of HBBO. The proposed HBBO algorithm has been used to solve the inverse kinematics problem of the 8-DOF redundant humanoid manipulator. Numerical simulation results demonstrate the effectiveness of this method.

关键词： Inverse kinematics problem 8-DOF humanoid manipulator Biogeography-based optimization （BBO） Differential evolution （DE）

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Epidermal radio frequency electronics for wireless power transfer

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Microsystems & Nanoengineering 2016年第1期2卷 52-60页

作者： Xian Huang Yuhao Liu Gil Woo Kong Jung Hun Seo Yinji Ma Kyung-In Jang Jonathan A.Fan Shimin Mao Qiwen Chen Daizhen Li Hank Liu Chuxuan Wang Dwipayan Patnaik Limei Tian Giovanni A.Salvatore Xue Feng Zhenqiang Ma Yonggang Huang John A.Rogers Department of Biomedical Engineering School of Precision Instrument and Opto-electronics EngineeringTianjin UniversityTianjin 300072China Department of Materials Science and Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Electrical and Computer Engineering University of Wisconsin-MadisonMadisonWI 53706USA Department of Civil and Environmental Engineering Northwestern UniversityEvanstonIL 60208USA Department of Engineering Mechanics Center for Mechanics and MaterialsTsinghua UniversityBeijing 100084China Department of Mechanical Engineering Northwestern UniversityEvanstonIL 60208USA Department of Robotics Engineering Daegu Gyeongbuk Institute of Science and TechnologyDaegu 42988Republic of Korea Department of Electrical Engineering Stanford UniversityStanfordCA 94305USA

Epidermal electronic systems feature physical properties that approximate those of the skin,to enable intimate,long-lived skin interfaces for physiological measurements,human–machine interfaces and other applications that cannot be addressed by wearable hardware that is commercially available today.A primary challenge is power supply;the physical bulk,large mass and high mechanical modulus associated with conventional battery technologies can hinder efforts to achieve epidermal characteristics,and near-field power transfer schemes offer only a limited operating *** we introduce an epidermal,farfield radio frequency(RF)power harvester built using a modularized collection of ultrathin antennas,rectifiers and voltage *** components,separately fabricated and tested,can be integrated together via methods involving soft contact *** studies of the individual components and the overall performance in various dielectric environments highlight the key operational features of these systems and strategies for their *** results suggest robust capabilities for battery-free RF power,with relevance to many emerging epidermal technologies.

关键词： antenna design epidermal electronics modularization silicon nanomembrane soft-contact lamination specific absorption rate wireless power

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Adaptive extended Kalman filter for a red shift navigation system 34

Adaptive extended Kalman filter for a red shift navigation s...

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34th Chinese Control Conference, CCC 2015

作者： Fu, Kui Zhang, Dan Tang, Peng Tang, Zhongliang He, Wei School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Computer Science Department Stony Brook University and SUNY KoreaIncheon 406-840 United States Center for Robotics University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9789881563897

In this paper, a navigation system based on red shift for spacecraft mission in solar system is implemented. Deep space environment is complex and changeable, its characteristics are hard to handle, there exist difficulties to simulate the deep space environment accurately. We know that red shift navigation system can achieve high navigation accuracy in deep space missions. And innovation-based adaptive estimation(IAE) can utilize latest measurement to adaptive adjust the covariance matrix of observation equations and state error covariance matrix. Using IAE method, we proposed a new adaptive filter to handle variable deep space environment. Employing adaptive extended Kalman filter (AEKF) in this system, the navigation performance is analysed. Simulation results indicate that the proposed navigation system using AEKF can achieve higher precision, better availability and continuity compared with conventional extended Kalman filter (EKF), but greater computational burden. © 2015 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Adaptive filtering

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Object detection based on two level fast matching

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2015年第12期10卷 381-394页

作者： Dou, Yumin Ye, Mao Xu, Pei Pei, Lishen Liu, Zhenghua School of Computer Science and Engineering Center for Robotics University of Electronic Science and Technology of China Chengdu China

Shape template matching is an important approach in object detection and recognition. In this paper, we propose a fast and novel object detection method, which represents edge map contours with salient points and retrieves the target object by using a backtracking method with two stages from coarse matching to fine matching. Our method has two main contributions. One is we propose the way to represent contour structure with salient points. The other is that the object detection method proposed can directly operate on the real images, which improves its practicability. According to the experimental results, the proposed approach improves the speed than previous works. © 2015 SERSC.

关键词： Template matching

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Nonlinear Model Predictive Formation Control for Quadcopters

Nonlinear Model Predictive Formation Control for Quadcopters

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作者： Ribeiro, Tiago T. Conceição, André G.S. Sa, Inkyu Corke, Peter LaR - Robotics Laboratory Department of Electrical Engineering Federal University of Bahia Salvador Brazil Australian Centre for Robotic Vision School of Electrical Engineering and Computer Science Queensland University of Technology Australia

This paper presents a Nonlinear Model Predictive Formation Control for a group of Quadcopters. In this approach the controllers are distributed to the quadcopters and the coupling is done through its objective function. The path following problem is expressed through a dynamic model of the quadcopter's state errors relative to a Serret-Frenet frame, and the coordination problem is solved through adjustments in the robots' speeds combined with the path update rate for each robot. A strategy based on constraints relaxing is proposed to solve the problem of high state and formation errors, factors that directly affect feasibility and stability. Simulation results considering a realistic scenario are provided to demonstrate the performance of the proposed control strategy. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Electronic Stuctures: Mechanically Guided Post‐Assembly of 3D Electronic Systems (Adv. Funct. Mater. 48/2018)

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Advanced Functional Materials 2018年第48期28卷

作者： Bong Hoon Kim Fei Liu Yongjoon Yu Hokyung Jang Zhaoqian Xie Kan Li Jungyup Lee Ji Yoon Jeong Arin Ryu Yechan Lee Do Hoon Kim Xueju Wang KunHyuck Lee Jong Yoon Lee Sang Min Won Nuri Oh Jeonghyun Kim Ju Young Kim Seong‐Jun Jeong Kyung‐In Jang Seungmin Lee Yonggang Huang Yihui Zhang John A. Rogers Department of Materials Science and Engineering Simpson Querrey Institute and Feinberg Medical School Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA Center for Mechanics and Materials Center for Flexible Electronics Technology AML Department of Engineering Mechanics Tsinghua University Beijing 100084 China Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana IL 61801 USA Department of Civil and Environmental Engineering Mechanical Engineering and Materials Science and Engineering Northwestern University Evanston IL 60208 USA AML Department of Engineering Mechanics Center for Mechanics and Materials Tsinghua University Beijing 100084 China Division of Materials Science and Engineering Hanyang University Seoul 04763 Republic of Korea Department of Electronics Convergence Engineering Kwangwoon University Seoul 01897 Republic of Korea Multidisciplinary Sensor Research Group Electronics and Telecommunications Research Institute (ETRI) Daejeon 34129 Republic of Korea Department of Organic Materials and Fiber Engineering Department of Information Communication Materials and Chemistry Convergence Technology Soongsil University 369 Sangdo‐ro Dongjak‐gu Seoul 06978 Republic of Korea Department of Robotics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Republic of Korea Department of Energy Electronics Convergence Kookmin University Seoul 02707 Republic of Korea Department of Civil and Environmental Engineering Mechanical Engineering Materials Science and Engineering Northwestern University Evanston IL 60208 USA Department of Materials Science and Engineering Department of Biomedical Engineering Department of Chemistry Department of Neurological Surgery Department of Mechanical Engineering Department of Electrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical School Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA

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HYPERSPECTRAL CLASSIFICATION VIA LEARNT FEATURES

HYPERSPECTRAL CLASSIFICATION VIA LEARNT FEATURES

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IEEE International Conference on Image Processing

作者： Yazhou Liu Guo Cao Quansen Sun Mel Siegel School of Computer Science and Engineering Nanjing University of Science and Technology Robotics Institute Carnegie Mellon University

ISBN: (纸本)9781479983407

This paper presents a new hyperspectral image (HSI) classification method which is capable of automatic feature learning while achieving high classification accuracy. The method contains two major modules: the spectral classification module and the spatial constraint module. Spectral classification module uses a deep network named stacked denoising autoencoders (SdA) to learn feature representation of the data. Through SdA, the data are projected nonlinearly from its original hyperspectral space to some higher dimensional space where more compact distribution is obtained. An interesting aspect of this method is that it does not need a feature design/extraction process guided by human prior. The suitable feature for the classification is learned by the deep network itself. Superpixel is utilized to generate the spatial constraints to refine the spectral classification results. By exploiting the spatial consistency of neighborhood pixels, the accuracy of classification is further improved by a big margin. Experiments on the public datasets reveal the superior performance of the proposed method.

关键词： Deep learning Stacked denoising autoen-coders (SdA) Hyperspectral image classification Superpixel Remote sensing spectral classification remote sensing Image classification B4GALNT2 gene sort module Learning Taxonomy

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Neural Adaptive Control for Robots with Uncertainties in Manipulator Dynamics and Actuator Dynamics Under Constrained Task Space

Neural Adaptive Control for Robots with Uncertainties in Man...

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第三十四届中国控制会议

作者： Zhong-Liang Tang Shuzhi Sam Ge Wei He Center for Robotics and School of Computer Science and Engineering University of Electronic Science and Technology of China Social Robotics Lab Interactive Digital Media Institute National University of Singapore Center for Robotics and School of Automation Engineering University of Electronic Science and Technology of China

ISBN: (纸本)9781467374439

Driven by the needs of safe human-robot interaction, this paper presents control designs for tracking control of robot system with uncertain manipulator dynamics and joint actuator dynamics subject to constrained task space. The integral Barrier Lyapunov Functional(i BLF) is employed to guarantee the constraint satisfaction, in which a conservative mapping of original constraint into new constraints on tracking errors is removed. Neural Networks(NN) are adopted to approximate the unknown packaged terms in desired control. Appropriate adapting parameters are constructed to estimate the unknown bounds on NN approximation. It is proved that the task space vector of end-effector converge to a small neighborhood around a desired trajectory without violating the predefined constrained region. Simulation results are provided to illustrate the performance of proposed control.

关键词： Robot,Constrained Task Space,Safe Interaction,Neural Networks,Barrier Lyapunov Function

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An Anti-interference EEG-EOG Hybrid Detection Approach for Motor Image Identification and Eye Track Recognition

An Anti-interference EEG-EOG Hybrid Detection Approach for M...

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第三十四届中国控制会议

作者： Haoyue Tang Yue Zhao Wei He Wei Fu School of Computer Science and Technology University of Electronic Science and Technology of China School of Automation Engineering University of Electronic Science and Technology of China School of Automation Engineering & Center for Robotics University of Electronic Science and Technology of China

ISBN: (纸本)9781467374439

In this paper, an anti-interference EEG-EOG hybrid detection approach is adopted for motor image identification and eye track recognition. We present a wave trap filter and a band pass filter to suppress power frequency interference and white noise. Meanwhile, the filter can still separate EEG and EOG signal from hybrid signal. Then, the features of EEG/EOG signal are extracted by the wavelet transform algorithm, and classified by the linear discriminant analysis(LDA) *** effectiveness of the signal process method described in this paper can be clearly observed through both of simulations and experiments, and the accuracy rate of pattern recognition is demonstrated in the end of the paper.

关键词： EEG signal,EOG signal,wavelet transform,LDA algorithm

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