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26th IEEE International Conference on Image Processing (ICIP)

作者： Zheng, Wenbo Yan, Lan Zhang, Wenwen Gou, Chao Wang, Fei-Yue Xi An Jiao Tong Univ Sch Software Engn Xian 710049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau 999078 Peoples R China

ISBN: (纸本)9781538662496

Face super-resolution has been studied for decades, and many approaches have been proposed to upsample low-resolution face images using information mined from paired low-resolution (LR) images and high-resolution (HR) images. However, most of this kind of works only simply sharpen the blurry edges in the upsampled face images and typically no photo-realistic face is reconstructed in the final result. In this paper, we present a GAN-based algorithm for face super-resolution which properly synthesizes photo-realistic super-recovered face. To this end, we introduce semi-dual optimal transport to optimize our model such that the distribution of its generated data can match the distribution of a target domain as much as possible. This way would endow our model with learning the mapping of distribution from unpaired LR images and HR images with desired properties. We demonstrate the robustness of our algorithm by testing it on Color FERET database and show that its performance is considerably superior to all state-of-the-art approaches.

关键词： Face Super-Resolution Semi-Dual Optimal Transport CycleGAN

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Path Planning of Industrial Robot Based on Improved RRT Algorithm in complex Environments

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IEEE ACCESS 2018年 6卷 53296-53306页

作者： Zhang, Haojian Wang, Yunkuan Zheng, Jun Yu, Junzhi Chinese Acad Sci Inst Automat Intelligent Mfg Technol & Syst Res Ctr Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

With the development of modern manufacturing industry, the application scenarios of industrial robot are becoming more and more complex. Manual programming of industrial robot requires a great deal of effort and time. Therefore, an autonomous path planning is an important development direction of industrial robot. Among the path planning methods, the rapidly-exploring random tree (RRT) algorithm based on random sampling has been widely applied for a high-dimensional robotic manipulator because of its probability completeness and outstanding expansion. However, especially in the complex scenario, the existing RRT planning algorithms still have a low planning efficiency and some are easily fall into a local minimum. To tackle these problems, this paper proposes an autonomous path planning method for the robotic manipulator based on an improved RRT algorithm. The method introduces regression mechanism to prevent over-searching configuration space. In addition, it adopts an adaptive expansion mechanism to continuously improve reachable spatial information by refining the boundary nodes in joint space, avoiding repeatedly searching for extended nodes. Furthermore, it avoids the unnecessary iteration of the robotic manipulator forward kinematics solution and its time-consuming collision detection in Cartesian space. The method can rapidly plan a path to a target point and can be accelerated out of a local minimum area to improve path planning efficiency. The improved RRT algorithm proposed in this paper is simulated in a complex environment. The results reveal that the proposed algorithm can significantly improve the success rate and efficiency of the planning without losing other performance.

关键词： Rapidly-exploring random tree (RRT) path planning industrial robot obstacle avoidance collision-free

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A Bibliometric Analysis of Blockchain Research

A Bibliometric Analysis of Blockchain Research

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2018 IEEE intelligent Vehicles Symposium, IV 2018

作者： Zeng, Shuai Ni, Xiaochun Yuan, Yong Wang, Fei-Yue State Key Lab for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Shandong266000 China Research Center of Military Computational Experiments and Parallel System National University of Defense China

ISBN: (纸本)9781538644522

Taking Ei Compendex (EI) and China National Knowledge Infrastructure (CNKI) databases as the literature sources, this paper presented a bibliographic analysis of the blockchain-related literature between January 2011 and September 2017. For each literature source, we built a separate dataset. Authors' productivity and collab.ration, affiliation of authors and collab.ration amongst institutions were analyzed using techniques of social networks analysis on both datasets. According to the results, the CNKI authors/institutes raised their productivity and outperformed the EI authors/institutes since 2016. However, the EI authors/institutes show a higher level than the CNKI authors/institutes in collab.ration. We also summarized the hot topics on the EI dataset using textual analysis and discovered researchers have shifted their attention from Bitcoin itself to the blockchain technology underlying it. © 2018 IEEE.

关键词： Blockchain

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Development of a Tetris playing robot controlled by KNR 15

Development of a Tetris playing robot controlled by KNR

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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Wang, Ming Zhang, Yanlu Dong, Huifang Li, Xu Yu, Junzhi Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan250100 China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538660720

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elab.rated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with lab.IEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system. © 2018 IEEE.

关键词： controllers

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Formation control for multiple agents with local measurements: Continuous-time and sampled-data-based cases

arXiv

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arXiv 2019年

作者： Wang, Chen Li, Shuai Xia, Weiguo Sun, Jinan Xie, Guangming National Engineering Research Center for Software Engineering Peking University Beijing100871 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian116024 China State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing100871 China

We study the formation control problem for a group of mobile agents in a plane, in which each agent is modeled as a kinematic point and can only use the local measurements in its local frame. The agents are required to maintain a geometric pattern while keeping a desired distance to a static/moving target. The prescribed formation is a general one which can be any geometric pattern, and the neighboring relationship of the N-agent system only has the requirement of containing a directed spanning tree. To solve the formation control problem, a distributed controller is proposed based on the idea of decoupled design. One merit of the controller is that it only uses each agent's local measurements in its local frame, so that a practical issue that the lack of a global coordinate frame or a common reference direction for real multi-robot systems is successfully solved. Considering another practical issue of real robotic applications that sampled data is desirable instead of continuous-time signals, the sampled-data based controller is developed. Theoretical analysis of the convergence to the desired formation is provided for the multiagent system under both the continuous-time controller with a static/moving target and the sampled-data based one with a static target. Numerical simulations are given to show the effectiveness and performance of the controllers. Copyright © 2019, The Authors. All rights reserved.

关键词： Multi agent systems

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Time-Optimal Trajectory Planning for Delta Robot Based on Quintic Pythagorean-Hodograph Curves

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IEEE ACCESS 2018年 6卷 28530-28539页

作者： Su, Tingting Cheng, Long Wang, Yunkuan Liang, Xu Zheng, Jun Zhang, Haojian Chinese Acad Sci Intelligent Mfg Technol & Syst Res Ctr Inst Automat Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In this paper, a time-optimal trajectory planning method based on quintic Pythagorean-Hodograph (PH) curves is proposed to realize the smooth and stable high-speed operation of the Delta parallel robot. The trajectory is determined by applying the quintic PH curves to the transition segments in the pick-and-place operation trajectory and the 3-4-5 polynomial motion law to the trajectory. The quintic PH curves are optimized to reduce the cycle time of the pick-and-place operation. In addition, a comparison between different trajectory planning methods has been implemented so as to observe the performance of the obtained results. The MATlab.simulation results reveal that compared with the trajectory planning based on vertical and horizontal motion superposition, the trajectory planning based on quintic PH curves is completed with a shorter motion cycle time and more stable motion performance, with the velocities, accelerations, and jerks in joint space bounded and continuous. Experiments carried out on the prototype also confirm that the trajectory planning based on quintic PH curves has a shorter cycle time, which is of great importance to high-speed operations of Delta parallel robots.

关键词： Delta parallel robot pick-and-place operation trajectory planning quintic Pythagorean-Hodograph curves optimization

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Multiple-Antenna Cooperative Spectrum Sensing Based on the Wavelet Transform and Gaussian Mixture Model

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SENSORS 2019年第18期19卷 3863-3863页

作者： Zhang, Shunchao Wang, Yonghua Yuan, Hantao Wan, Pin Zhang, Yongwei Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China South Cent Univ Nationalities Hubei Key Lab Intelligent Wireless Commun Wuhan 430074 Hubei Peoples R China

Spectrum sensing is a core technology in cognitive radio (CR) systems. In this paper, a multiple-antenna cooperative spectrum sensor based on the wavelet transform and Gaussian mixture model (MAWG) is proposed. Compared with traditional methods, the MAWG method avoids the derivation of the threshold and improves the performance of single secondary user (SU) spectrum sensing in cases of channel loss and hidden terminal. The MAWG method reduces the noise of the signal which collected by the multiple-antenna SUs through the wavelet transform. Then, the fusion center (FC) extracts the statistical features from the signals that are pre-processed by the wavelet transform. To extract the statistical features, an sensing data fusion method is proposed. The MAWG method divides all SUs that are involved in the cooperative spectrum sensing into two clusters and extracts a two-dimensional feature vector. In order to avoid complicated decision threshold derivation, the Gaussian mixture model (GMM) is used to train a classifier for spectrum sensing according to these two-dimensional feature vectors. Simulation experiments are performed in the kappa-mu channel model. The simulation shows that the MAWG can effectively improve spectrum sensing performance under the kappa-mu channel model.

关键词： cognitive radio spectrum sensing multiple-antenna wavelet transform Gaussian mixture model

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PredNet and CompNet: Prediction and High-Precision Compensation of In-Plane Shape Deformation for Additive Manufacturing 15

PredNet and CompNet: Prediction and High-Precision Compensat...

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15th IEEE International Conference on Automation Science and Engineering (IEEE CASE)

作者： Shen, Zhen Shang, Xiuqin Li, Yuqing Bao, Yin Zhang, Xipeng Dong, Xisong Wan, Li Xiong, Gang Wang, Fei-Yue Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci Cloud Comp Ctr Donggguan 523808 Peoples R China Univ Southern Calif Los Angeles CA 90007 USA Univ Chinese Acad Sci Sch Comp & Control Engn Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Shandong Peoples R China Beijing Ten Dimens Technol Co Ltd Beijing Peoples R China

ISBN: (纸本)9781728103563

The error compensation for printed objects in additive manufacturing (AM) has always been one of the most critical problems. The precision control of the AM is usually more difficult than the subtractive manufacturing system, whose precision can reach the micron level easily by using a servo system. For the AM, there usually exist shrinkage and curling effects which lead to deformation. In this paper, we focus on the in-plane shape deformation problem, and we build the PredNet and CompNet, using deep neural networks for the error prediction and compensation. We test our methods on dental crown models. We generate deformed models by simulation of the translation, scaling down and rotation deformation. The minimum F1 scores of error prediction and compensation can be up to 0.982.

关键词： Strain Neural networks Shape Three-dimensional printing Deformable models Three-dimensional displays

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Parallel Vehicular Networks: A CPSS-Based Approach via Multimodal Big Data in IoV

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IEEE INTERNET OF THINGS JOURNAL 2019年第1期6卷 1079-1089页

作者： Han, Shuangshuang Wang, Xiao Zhang, Jun Jason Cao, Dongpu Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Shandong Peoples R China Vehicle Intelligence Pioneers Inc Qingdao 266000 Peoples R China Univ Denver Dept Elect & Comp Engn Ritchie Sch Engn & Comp Sci Denver CO 80210 USA Univ Waterloo Mech & Mechatron Engn Waterloo ON N2L 3G1 Canada Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Technol Changsha 410073 Hunan Peoples R China

Vehicular networks (VNs) have received great attention as one of the crucial supportive techniques for intelligent transportation systems (ITSs). However, the introduction of dynamic and complex human behaviors into VNs makes it a cyber-social-physical system. Thus, artificial systems, computational experiments, parallel executions-based parallel VNs (PVN) are proposed in this paper. The framework of PVN is then designed and presented, its characteristics and applications are demonstrated, and its related research challenges are discussed. PVN uses software-defined artificial VNs for modeling and representation, computational experiments for analysis and evaluation, and parallel execution for control and management. Thus, more reliable and efficient traffic status and ultrahigh data rate communications are obtained among vehicles and infrastructures, which is expected to achieve the descriptive intelligence, predictive intelligence, and prescription intelligence for VNs. The proposed PVN offers a competitive solution for achieving a smooth, safe, and efficient cooperation among connected vehicles in future ITSs.

关键词： Cyber-social-physical system (CPSS) Internet of Vehicles (IoV) parallel system social networks

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An efficient 3D pedestrian detector with calibrated RGB camera and 3D LiDAR

An efficient 3D pedestrian detector with calibrated RGB came...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Pang, Lei Cao, Zhiqiang Yu, Junzhi Liang, Shuang Chen, Xuechao Zhang, Weimin State Key Lab Management and Control for Complex Systems Institute of Automation CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Dept. Mech. Eng. Sci. BIC-ESAT College of Engineering Peking University Beijing100871 China BAICIRS Beijing100081 China Intell. Robot. Inst. Beijing Inst. Technol. Beijing100081 China

ISBN: (纸本)9781728163215

Pedestrian detection plays an important role in the environmental perception and autonomous navigation for robotics, which provides critical information for the safe operation in complex environments. In this paper, a 3D pedestrian detector with calibrated LiDAR and RGB Camera is proposed, which takes full advantage of the precise range information of 3D LiDAR scanner and semantic information acquired from RGB image. The proposed approach integrates the segmented object clusters of point cloud and 2D bounding boxes generated by a visual object detector. The point cloud is segmented by a three-step segmentation approach, which can segment point cloud with both high precision and high efficiency. By fusion multi-sensor information in the image domain, the proposed approach provides 3D information of pedestrians in both LiDAR and camera coordinate systems. Experiments was conducted to evaluate the performance of the proposed approach. © 2019 IEEE.

关键词： Cameras

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