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World Congress on Intelligent control and Automation

作者： Xiangrui Meng Zhiqiang Cao Leijie Zhang Shuo Wang Chao Zhou State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Beijing 100190 China

ISBN: (纸本)9781467384155

This paper introduces a slope detection method based on point cloud data from 3D LiDAR for quadruped robots in unknown environments. For quadruped robots, they need to adjust their gaits according to different slope angles to avoid some potential dangers. 3D LiDAR is used to gather point cloud data, which is superior to 2D LiDAR in speed and accuracy. In this paper, a slope detection method using bilateral filtering and RANSAC algorithms is discussed. The experiments of slope detection are fulfilled with the consideration of different angles of slopes and different orientations to the slopes, and the results demonstrate that errors of angle estimation is small.

关键词： Laser radar Three-dimensional displays Robot kinematics Robot sensing systems Mobile robots Lidar quadruped robot three-dimensional displays Manipulator sensing systems Robot kinematics Mobile robots bilateral filtering Unknown environments

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Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment

arXiv

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arXiv 2017年

作者： Lu, Yan-Feng Jia, Li-Hao Qaio, Hong Li, Yi Research Center for Brain-inspired Intelligence Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai China School of Information Engineering Nanchang University Nanchang China

Biologically inspired model (BIM) for image recognition is a robust computational architecture, which has attracted widespread attention. BIM can be described as a four-layer structure based on the mechanisms of the visual cortex. Although the performance of BIM for image recognition is robust, it takes the randomly selected ways for the patch selection, which is sightless, and results in heavy computing burden. To address this issue, we propose a novel patch selection method with oriented Gaussian-Hermite moment (PSGHM), and we enhanced the BIM based on the proposed PSGHM, named as PBIM. In contrast to the conventional BIM which adopts the random method to select patches within the feature representation layers processed by multi-scale Gabor filter banks, the proposed PBIM takes the PSGHM way to extract a small number of representation features while offering promising distinctiveness. To show the effectiveness of the proposed PBIM, experimental studies on object categorization are conducted on the CalTech05, TU Darmstadt (TUD), and GRAZ01 databases. Experimental results demonstrate that the performance of PBIM is a significant improvement on that of the conventional BIM. Copyright © 2017, The Authors. All rights reserved.

关键词： Image enhancement

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Quantum gate identification: Error analysis, numerical results and optical experiment?

arXiv

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arXiv 2017年

作者： Wang, Yuanlong Yin, Qi Dong, Daoyi Qi, Bo Petersen, Ian R. Hou, Zhibo Yonezawa, Hidehiro Xiang, Guo-Yong School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia Centre for Quantum Computation and Communication Technology Australian Research Council CanberraACT2600 Australia Key Laboratory of Quantum Information University of Science and Technology of China CAS Hefei230026 China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui230026 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Research School of Engineering Australian National University CanberraACT0200 Australia

The identification of an unknown quantum gate is a significant issue in quantum technology. In this paper, we propose a quantum gate identification method within the framework of quantum process tomography. In this method, a series of pure states are inputted to the gate and then a fast state tomography on the output states is performed and the data are used to reconstruct the quantum gate. Our algorithm has computational complexity O(d3) with the system dimension d. The algorithm is compared with maximum likelihood estimation method for the running time, which shows the efficiency advantage of our method. An error upper bound is established for the identification algorithm and the robustness of the algorithm against the purity of input states is also tested. We perform quantum optical experiment on single-qubit Hadamard gate to verify the effectiveness of the identification algorithm. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational complexity

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A fast and compact saliency score regression network based on fully convolutional network

arXiv

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arXiv 2017年

作者： Xi, Xuanyang Luo, Yongkang Li, Fengfu Wang, Peng Qiao, Hong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing100190 China LSEC Institute of Applied Mathematics AMSS Chinese Academy of Sciences Beijing100190 China

Visual saliency detection aims at identifying the most visually distinctive parts in an image, and serves as a pre-processing step for a variety of computer vision and image processing tasks. To this end, the saliency detection procedure must be as fast and compact as possible and optimally processes input images in a real time manner. It is an essential application requirement for the saliency detection task. However, contemporary detection methods often utilize some complicated procedures to pursue feeble improvements on the detection precession, which always take hundreds of milliseconds and make them not easy to be applied practically. In this paper, we tackle this problem by proposing a fast and compact saliency score regression network which employs fully convolutional network, a special deep convolutional neural network, to estimate the saliency of objects in images. It is an extremely simplified end-to-end deep neural network without any pre-processings and post-processings. When given an image, the network can directly predict a dense full-resolution saliency map (image-to-image prediction). It works like a compact pipeline which effectively simplifies the detection procedure. Our method is evaluated on six public datasets, and experimental results show that it can achieve comparable or better precision performance than the state-of-the-art methods while get a significant improvement in detection speed (35 FPS, processing in real time). Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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Attitude synchronization of multiple rigid bodies in SE(3) over proximity networks

Attitude synchronization of multiple rigid bodies in SE(3) o...

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第35届中国控制会议

作者： Juan Deng Zhixin Liu Lin Wang John S.Baras Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceCAS Department of Automation Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education Department of Electrical and Computer Engineering and the Institute for Systems Research University of MarylandCollege Park

ISBN: (纸本)9781509009107

This paper investigates the attitude synchronization of a group of moving rigid bodies whose states including positions and rotation matrices evolve in the Lie group SE(3).The commonly used circular neighborhood is adopted,and the neighbor graphs are described by proximity *** order to avoid introducing discussions on the abrupt changes of neighbor graphs,a dwell time is *** distributed sampled-data control law for the angular velocity is *** the assumptions on the initial states,we provide sufficient conditions for the attitude synchronization of multiple rigid body *** with the existing results,our condition depends only on the neighborhood radius,the moving velocity and the dwell time.

关键词： rigid body SE(3) attitude synchronization sampled-data control proximity network

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Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks

Understand Scene Categories by Objects: A Semantic Regulariz...

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IEEE International Conference on Robotics and Automation

作者： Yiyi Liao Sarath Kodagoda Yue Wang Lei Shi Yong Liu the State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University Zhejiang 310027 China. the Centre for Autonomous Systems (CAS) The University of Technology Sydney Australia.

ISBN: (纸本)9781467380270

Scene classification is a fundamental perception task for environmental understanding in today's robotics. In this paper, we have attempted to exploit the use of popular machine learning technique of deep learning to enhance scene understanding, particularly in robotics applications. As scene images have larger diversity than the iconic object images, it is more challenging for deep learning methods to automatically learn features from scene images with less samples. Inspired by human scene understanding based on object knowledge, we address the problem of scene classification by encouraging deep neural networks to incorporate object-level information. This is implemented with a regularization of semantic segmentation. With only 5 thousand training images, as opposed to 2.5 million images, we show the proposed deep architecture achieves superior scene classification results to the state-of-the-art on a publicly available SUN RGB-D dataset. In addition, performance of semantic segmentation, the regularizer, also reaches a new record with refinement derived from predicted scene labels. Finally, we apply our model trained on SUN RGB-D dataset to a set of images captured in our university using a mobile robot, demonstrating the generalization ability of the proposed algorithm.

关键词： Categories Objects RGB-D

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GB-RC4: Effective brute force attacks on RC4 algorithm using GPU 7

GB-RC4: Effective brute force attacks on RC4 algorithm using...

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7th International Green and Sustainable Computing Conference, IGSC 2016

作者： Xue, Pei Li, Tao Dong, Han Liu, Chunbo Ma, Wenjing Pei, Songwen College of Computer and Control Engineering Nankai University Tianjin300071 China Information Security Evaluation Center Civil Aviation University of China Tianjin300300 China Laboratory of Parallel Software and Computational Science State Key Laboratory of Computing Science Institute of Software CAS Beijing China Shanghai Key Lab of Modern Optical Systems Department of Computer Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9781509051175

Encryption algorithms are applied to a variety of fields and the security of encryption algorithms depends heavily on the computational infeasibility of exhaustive key-space search. RC4 algorithm has an extensive application for stream encryption, however, the disadvantages of traditional RC4 serial algorithm are large computational quantity and slow computation speed, which means a great challenge for throughput of computing system. Graphics processors recently have been widely used as accelerators for high throughput computing. In this paper, GPU is used to improve the efficiency and performance of attacking RC4 algorithm. First, we revised RC4 algorithm to make it easier to parallelize on a GPU. Then we take advantage of constant memory and shared memory in GPU to search the key space of RC4 algorithm efficiently. Besides, we solved the bank conflict problem in shared memory to further improve the performance. Our approach was evaluated in the whole key space of 40-bit, and the results show it can complete searching of the whole key space within 12.8 hours. © 2016 IEEE.

关键词： Graphics processing unit

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Output stabilization for a class of nonlinear systems via high-gain observer with limited gain power

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IFAC-PapersOnLine 2015年第11 11期48卷 730-735页

作者： Wang, Lei Astolfi, Daniele Su, Hongye Marconi, Lorenzo Isidori, Alberto State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China CASY -DEI University of Bologna Italy MINES ParisTech PSL Research University CAS Paris France Department of Computer Control and Management Engineering University of Rome "La Sapienza" Rome Italy

We address the problem of output stabilization for the class of nonlinear minimumphase systems with a well-defined relative degree whose output is affected by measurement noise. In the proposed control structure the derivatives of the output are estimated by means of a new high-gain observer proposed in Astolfi and Marconi [2015], which, with respect to high-gain observers conventionally used in literature, has limited gain power. The advantage in using the proposed observer is in its implementation for systems with high relative degree and in the sensitivity to the sensor noise. Simulation results are presented to show the effectiveness of the proposed control structure. © 2015

关键词： Nonlinear systems Stabilization control structure High gain observers Measurement Noise Minimum phase systems Normal form Output stabilization Relative degrees Sensor noise

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Stability of Distributed LMS Under Cooperative Stochastic Excitation

Stability of Distributed LMS Under Cooperative Stochastic Ex...

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第三十四届中国控制会议

作者： Siyu Xie Lei Guo Key Laboratory of Systems and Control Academy of Mathematics and Systems Science CAS

ISBN: (纸本)9781467374439

Distributed estimation algorithms can estimate a dynamic process of interest by a set of estimators cooperatively, when any individual estimator cannot. The paper considers this kind of problems and focuses on a class of distributed least meansquare(LMS) algorithms in discrete time. Stability analysis will be provided under a weakest possible cooperative stochastic excitation condition. We remark that the stringent conditions such as independency and stationarity that have been used in almost all the existing literatures are no longer used in this paper. In addition, a simulation result comparing with the non-cooperative LMS algorithm will be provided to show the advantage of the distributed LMS algorithm studied in the paper.

关键词： Distributed LMS algorithm,Cooperative stochastic excitation,Lp-exponentially stability

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Native diversity buffers against severity of non-native tree invasions ( vol 621,pg 773 , 2023 )

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NATURE 2023年第7982期622卷 E2-E2页

作者： Delavaux, Camille S. Crowther, Thomas W. Zohner, Constantin M. Robmann, Niamh M. Lauber, Thomas van den Hoogen, Johan Kuebbing, Sara Liang, Jingjing de-Miguel, Sergio Nabuurs, Gert-Jan Reich, Peter B. Abegg, Meinrad Yao, Yves C. Adou Alberti, Giorgio Zambrano, Angelica M. Almeyda Alvarado, Braulio Vilchez Alvarez-Davila, Esteban Alvarez-Loayza, Patricia Alves, Luciana F. Ammer, Christian Anton-Fernandez, Clara Araujo-Murakami, Alejandro Arroyo, Luzmila Avitabile, Valerio Aymard, Gerardo A. Baker, Timothy R. Balazy, Radomir Banki, Olaf Barroso, Jorcely G. Bastian, Meredith L. Bastin, Jean-Francois Birigazzi, Luca Birnbaum, Philippe Bitariho, Robert Boeckx, Pascal Bongers, Frans Bouriaud, Olivier Brancalion, Pedro H. S. Brandl, Susanne Brienen, Roel Broadbent, Eben N. Bruelheide, Helge Bussotti, Filippo Gatti, Roberto Cazzolla Cesar, Ricardo G. Cesljar, Goran Chazdon, Robin Chen, Han Y. H. Chisholm, Chelsea Cho, Hyunkook Cienciala, Emil Clark, Connie Clark, David Colletta, Gabriel D. Coomes, David A. Valverde, Fernando Cornejo Corral-Rivas, Jose J. Crim, Philip M. Cumming, Jonathan R. Dayanandan, Selvadurai de Gasper, Andre L. Decuyper, Mathieu Derroire, Geraldine DeVries, Ben Djordjevic, Ilija Dolezal, Jiri Dourdain, Aurelie Obiang, Nestor Laurier Engone Enquist, Brian J. Eyre, Teresa J. Fandohan, Adande Belarmain Fayle, Tom M. Feldpausch, Ted R. Ferreira, Leandro V. Fischer, Markus Fletcher, Christine Frizzera, Lorenzo Gamarra, Javier G. P. Gianelle, Damiano Glick, Henry B. Harris, David J. Hector, Andrew Hemp, Andreas Hengeveld, Geerten Herault, Bruno Herbohn, John L. Herold, Martin Hillers, Annika Coronado, Euridice N. Honorio Hui, Cang Ibanez, Thomas T. Amaral, Ieda Imai, Nobuo Jagodzinski, Andrzej M. Jaroszewicz, Bogdan Johannsen, Vivian Kvist Joly, Carlos A. Jucker, Tommaso Jung, Ilbin Karminov, Viktor Kartawinata, Kuswata Kearsley, Elizabeth Kenfack, David Kennard, Deborah K. Kepfer-Rojas, Sebastian Keppel, Gunnar Khan, Mohammed Latif Killeen, Timothy J. Kim, Hyun Seok Kitayama, Kanehiro Kohl, Michael Korju Institute of Integrative Biology ETH Zurich (Swiss Federal Institute of Technology) Zurich Switzerland Department of Genetics Evolution and Environment University College London London UK The Forest School at The Yale School of the Environment Yale University New Haven CT USA Department of Forestry and Natural Resources Purdue University West Lafayette IN USA Department of Agriculture Forestry and Bioresources Seoul National University Seoul South Korea Department of Crop and Forest Sciences University of Lleida Lleida Spain Joint Research Unit CTFC–AGROTECNIO–CERCA Solsona Spain Wageningen University and Research Wageningen The Netherlands World Agroforestry (ICRAF) Nairobi Kenya Department of Forest Resources University of Minnesota St Paul MN USA Hawkesbury Institute for the Environment Western Sydney University Penrith New South Wales Australia Institute for Global Change Biology and School for Environment and Sustainability University of Michigan Ann Arbor MI USA Swiss Federal Institute for Forest Snow and Landscape Research WSL Birmensdorf Switzerland UFR Biosciences University Félix Houphouët-Boigny Abidjan Côte d’Ivoire Department of Agricultural Food Environmental and Animal Sciences University of Udine Udine Italy Faculty of Science and Technology Free University of Bolzano Bolzano Italy Spatial Ecology and Conservation Laboratory Department of Tourism Recreation and Sport Management University of Florida Gainesville FL USA Forestry School Tecnológico de Costa Rica TEC Cartago Costa Rica Fundacion ConVida Universidad Nacional Abierta y a Distancia UNAD Medellin Colombia Field Museum of Natural Histiory Chicago IL USA Center for Tropical Research Institute of the Environment and Sustainability UCLA Los Angeles CA USA Silviculture and Forest Ecology of the Temperate Zones University of Göttingen Göttingen Germany Division of Forest and Forest Resources Norwegian Institute of Bioeconomy Research (NIBIO) Ås Norway Museo de Hi

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