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2019 Jiangsu Annual Conference on Automation, JACA 2019

作者： Wang, Xinzhi Fang, Yifan Li, Changdi Gong, Shenjian Yu, Lei Fei, Shumin School of Mechanical and Electric Engineering Soochow University Suzhou China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China State Key Lab of CAD&CG Zhejiang University Hangzhou China School of Automation Southeast University Nanjing China

The gesture recognition technology based on computer vision can provide a more natural way of human–computer interaction, and become a research hotspot in the field of gesture recognition. This study proposes an improved Sobel operator which is used for static hand contour extraction. The method is based on the noise existing in the picture, and a bilateral filtering algorithm is employed to denoise and preserve the edges to a large extent. Based on the colour space, the elliptical skin colour model is used to extract the skin colour domain, and the hand is separated according to the block domain feature. Finally, in order to solve the oblique indirection problem of the traditional Sobel operator, two oblique direction templates are added and the weights are reassigned. Then the improved Sobel operator is used to extract the gesture edges, and compared with the classical extraction edge operator Laplace and Canny extraction effects. The experimental results show that the proposed algorithm has high efficiency and accuracy in static gesture segmentation in a simple environment. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Extraction

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Regional Semantic Learning and Mapping Based on Convolutional Neural Network and Conditional Random Field

Regional Semantic Learning and Mapping Based on Convolutiona...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Kai Li Kun Qian Rui Liu Fang Fang Hai Yu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China State Grid Corporation of China Global Energy Interc onnection Research Institute Company Ltd Nanjing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

Semantic information of objects and environment is a basis for robots to effectively complete complicated tasks. However, scene recognition methods based on image descriptors or convolutional neural networks often have misclassifications in actual environment. One reason is that highly complex environment has inconspicuous physical boundaries. In this paper, we propose a regional semantic learning method based on convolutional neural networks (CNNs) and conditional random fields (CRFs). The method combines global information obtained by scene classification network and local object information obtained by object detection network to train a CRF scene recognition model. Then the model can be used to infer the semantics of the region. After that, the regional semantic information is applied to build a sparse semantic map based on ORB-SLAM2. The proposed method was tested on a self-built environment dataset which contains four regional categories. Experimental results have demonstrated that the proposed method is effective and can obtain better classification results.

关键词： Feature extraction Semantics Erbium Training Three-dimensional displays Robots Real-time systems

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Development of a propeller with undulating fins and its characteristics

Development of a propeller with undulating fins and its char...

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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Ma, Ruichen Wang, Yu Wang, Rui Wang, Shuo 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

ISBN: (纸本)9781728137261

This paper addresses some experiments about measurements of thrust and heave force generated by a modular designed biomimetic underwater propeller. The propeller has a ribbon fin that consists of twelve rays linked by a latex membrane. Different forms of waves can be generated by the propeller. A measurement platform is constructed to obtain the thrust and heave force generated by the waves along with the input power of the propeller. Three types of waves are performed on the platform, including sinusoidal waves, fusiform sinusoidal waves and inward counter-propagating sinusoidal waves. By changing the parameters of undulating waves, a total of three hundred series of experiments are implemented. The measurement results of three types of waves are analyzed and the differences among three types of waves are compared. © 2019 IEEE.

关键词： Fins (heat exchange)

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Exponential input-to-state stability of impulsive stochastic fuzzy Cohen-Grossberg neural networks with distributed infinite transmission delays

Exponential input-to-state stability of impulsive stochastic...

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第三十八届中国控制会议

作者： Weisong Zhou Dan Shi Wei Zhu Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications

In this paper, we study a class of impulsive stochastic fuzzy delayed Cohen-Grossberg neural networks with distributed infinite transmission delays. By Razumikhin technique and differential inequalities, some sufficient conditions ensuring the mean-square exponential input-to-state stability of our considered Cohen-Grossberg neural networks are obtained. These results can include constant delay and bounded distributed delay as its special cases, and generalize and improve some earlier publications. A numerical example is demonstrated to verify the theoretical results.

关键词： Impulsive Stochastic Infinite delays Cohen-Grossberg neural networks Exponential input-to-state stability

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Preface——Special Issue on New Directions in Nonlinear and Distributed control

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Journal of systems Science & Complexity 2018年第1期31卷 1-3页

作者： LIU Tengfei XIN Bin JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China Tandon School of Engineering New York University Brooklyn NY 11201 USA

Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha... 详细信息

关键词：控制问题非线性分布式工程应用程序电子物理自然系统生产线相互作用

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Localization and Surface Characterization by Zhurong Mars Rover at Utopia Planitia

Research Square

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Research Square 2021年

作者： Ding, Liang Zhou, Ruyi Yu, Tianyi Gao, Haibo Yang, Huaiguang Li, Jian Yuan, Ye Liu, Chuankai Wang, Jia Zhao, Yuyan Wang, Zhengyin Wang, Xiyu Bao, Gang Deng, Zongquan Huang, Lan Li, Nan Cui, Xiaofeng He, Ximing Jia, Yang Yuan, Baofeng Liu, Guangjun Zhang, Hui Zhao, Rui Zhang, Zuoyu Cheng, Ziqing Wu, Fan Xu, Qian Lu, Hao Richter, Lutz Liu, Zhen Niu, Fuliang Qi, Huanan Li, Shu Feng, Wenhao Yang, Chaojie Chen, Baichao Dang, Zhaolong Zhang, Mingming Li, Lichun Wang, Xiaoxue Huang, Zhao Zhang, Jitao Xing, Hongjun Wang, Guanyu Niu, Lizhou Xu, Peng Wan, Wenhui Di, Kaichang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China Beijing Aerospace Control Center Beijing100094 China Center for Lunar and Planetary Sciences Institute of Geochemistry Chinese Academy of Science Guiyang550081 China CAS Center for Excellence in Comparative Planetology Hefei230026 China University of Chinese Academy of Sciences Beijing100049 China Beijing Institute of Spacecraft System Engineering Beijing100094 China Department of Aerospace Engineering Ryerson University TorontoONM5B 2K3 Canada Hauptstrasse 1e Eching Germany State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100101 China

China’s first Mars rover, Zhurong, has successfully touched down on the southern Utopia Planitia of Mars at 109.925° E, 25.066° N, and since performed cooperative multiscale investigations with the Tianwen-1 orbiter. Here we present primary localization and surface characterization results based on complementary data of the first 60 sols. The Zhurong rover has traversed 450.9 m southwards over a flat surface with mild wheel slippage (less than 0.2 in slip ratio). The encountered crescent-shaped sand dune indicates a NE-SW local wind direction, consistent with larger-range remote-sensing observations. Soil parameter analysis based on terramechanics indicates that the topsoil has high bearing strength and cohesion, and its equivalent stiffness and internal friction angle are ~1390-5872 kPa∙m-n and ~21°-34° respectively. Rocks observed strewn with dense pits, or showing layered and flaky structures, are presumed to be involved in physical weathering like severe wind erosion and potential chemical weathering processes. These preliminary observations suggest great potential of in-situ investigations by the scientific payload suite of the Zhurong rover in obtaining new clues of the region’s aeolian and aqueous history. Cooperative investigations using the related payloads on both the rover and the obiter could peek into the habitability evolution of the northern lowlands on Mars. © 2021, CC BY.

关键词： Sols

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Generalized Visual-Tactile Transformer Network for Slip Detection

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IFAC-PapersOnLine 2020年第2期53卷 9529-9534页

作者： Shaowei Cui Junhang Wei Xiaocan Li Rui Wang Yu Wang Shuo Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Future Technology University of Chinese Academy of Sciences Beijing 100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai 200031 China

Slip detection plays a vital role in robotic dexterous grasping and manipulation, and it has long been a challenging problem in the robotic community. Different from traditional tactile perception-based methods, we propose a Generalized Visual-Tactile Transformer (GVT-Transformer) network to detect slip based on visual and tactile spatiotemporal sequences. The main novelty of GVT-Transformer is its ability to address unaligned vision and tactile data in various formats captured by various tactile sensors. Furthermore, we train and test our proposed network on a public and our visual-tactile grasping datasets. The experimental results show that our method is more suitable for sliding detection tasks than previous visual-tactile learning methods and more versatile.

关键词： Information sensor fusion Perception sensing Intelligent robotics Deep neural networks Visual-tactile fusion perception

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A registration-aided domain adaptation network for 3D Point cloud based place recognition

arXiv

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arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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A Guide for Human Walking Model and control — Insights from Mechanical Property Analysis of Human Walking

A Guide for Human Walking Model and Control — Insights from...

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Chinese control and Decision Conference, CCDC

作者： Guangrong Chen Bowen Hou Sheng Guo Junzheng Wang Robotics Research Center Beijing Jiaotong University Beijing P.R. China Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention Beijing P.R. China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P.R. China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This paper aims to establish the simplest human walking model and provide a guide for controlling biped robots. Firstly, a human motion capture system was utilized to sample the motion data of human walking and a representative subject was selected. Secondly, one of the simplest human walking model was set up. The mechanical property analysis of human walking was done based on the established walking model via fitting. Thirdly, the feasibility and effectiveness of proposed walking model were validated by numerical simulations. Finally, the intrinsical relationships among human walking, biped walking model and control were discussed to provide a guide and insight for controlling biped robots.

关键词： Legged locomotion Numerical models Force Analytical models Numerical simulation

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LocNet: Global Localization in 3D Point Clouds for Mobile Vehicles

LocNet: Global Localization in 3D Point Clouds for Mobile Ve...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Yin, Huan Tang, Li DIng, Xiaqing Wang, Yue Xiong, Rong State Key Laboratory of Industrial Control and Technology Zhejiang University Hangzhou China IPlus Robotics Hangzhou China

ISBN: (纸本)9781538644522

Global localization in 3D point clouds is a challenging problem of estimating the pose of vehicles without any prior knowledge. In this paper, a solution to this problem is presented by achieving place recognition and metric pose estimation in the global prior map. Specifically, we present a semi-handcrafted representation learning method for LiDAR point clouds using siamese LocNets, which states the place recognition problem to a similarity modeling problem. With the final learned representations by LocNet, a global localization framework with range-only observations is proposed. To demonstrate the performance and effectiveness of our global localization system, KITTI dataset is employed for comparison with other algorithms, and also on our long-time multi-session datasets for evaluation. The result shows that our system can achieve high accuracy. © 2018 IEEE.

关键词： Learning systems

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