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arXiv 2020年

作者： Qi, Hongsheng Li, Bo Jing, Rui-Juan Wang, Lei Proutiere, Alexandre Shi, Guodong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Mathematics Mechanization Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Faculty of Science Jiangsu University Zhenjiang212013 China Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering University of Sydney NSW2006 Australia Department of Automatic Control Kth Royal Institute of Technology Stockholm100-44 Sweden

In this paper, we propose distributed algorithms that solve a system of Boolean equations over a network, where each node in the network possesses only one Boolean equation from the system. The Boolean equation assigned at any particular node is a private equation known to this node only, and the nodes aim to compute the exact set of solutions to the system without exchanging their local equations. We show that each private Boolean equation can be locally lifted to a linear algebraic equation under a basis of Boolean vectors, leading to a network linear equation that is distributedly solvable using existing distributed linear equation algorithms as a subroutine. A number of exact or approximate solutions to the induced linear equation are then computed at each node from different initial values. The solutions to the original Boolean equations are eventually computed locally via a Boolean vector search algorithm. We prove that given solvable Boolean equations, when the initial values of the nodes for the distributed linear equation solving step are i.i.d selected according to a uniform distribution in a high-dimensional cube, our algorithms return the exact solution set of the Boolean equations at each node with high probability. Furthermore, we present an algorithm for distributed verification of the satisfiability of Boolean equations, and prove its correctness. Finally, we show that by utilizing linear equation solvers with differential privacy to replace the in-network computing routines, the overall distributed Boolean equation algorithms can be made differentially private. Under the standard Laplace mechanism, we prove an explicit level of noises that can be injected in the linear equation steps for ensuring a prescribed level of differential privacy. Copyright © 2020, The Authors. All rights reserved.

关键词： Linear equations

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A novel robot system assisting non-invasive positive pressure ventilation

A novel robot system assisting non-invasive positive pressur...

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2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Ma, Xuesong Zhu, Jiahua Gao, Wenpeng Fu, Yili State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin Heilongjiang Province China

ISBN: (纸本)9781538680698

Non-invasive positive pressure ventilation has the advantages of fewer complications and is beneficial to the patients. However, the anaesthesiologists must hold the mask covering the patients' mouth and nose, which is labour intensity and lack of not ergonomics. In this paper, we propose a concept of the anti-maxillary opening position (that is mandibular anti jaw position and the opening position implement step by step). A novel robot system assisting noninvasive positive pressure ventilation is designed to help the anaesthesiologist hold the mask, and meanwhile keep the anti-maxillary in the opening position for an optimal breathing condition without damaging the other tissues. The robot adopts the active and passive control mode. We have completed the structure design of the robot mechanical system and the processing and assembly of the prototype and designed the electronic control system for the robot, configured the electronic control hardware of each part of the robot, so that the robot has the ability to complete the auxiliary breathing capacity and limit protection. Finally, the experimental platform of robot system was built and the preliminary clinical trial was completed. © 2018 IEEE.

关键词： Machine design

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Programmable cell aggregation by a synthetic biosilicification approach

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iScience 2025年第6期28卷

作者： Qing Wang Jing Sun Lei Zang Huaxiong Yao Lin Wang Runtao Zhu Jie Li Simin Zeng Hongting Tang Teng Wang Ji Liu Bo Wang Bo Li Zhiyuan Liu Zhuojun Dai State Key Laboratory of Quantitative Synthetic Biology Shenzhen Institute of Synthetic Biology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 China Center of Neural Engineering CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen 518055 China Department of Civil Engineering University of Nottingham Ningbo China 199 Taikang East Road Ningbo 315100 China

Programmable cell aggregation offers valuable insights into the natural development of synthetic multicellular systems and enables precise control over spatial organization and material structuring. Previous efforts have focused on modifying cells with designed organic-based adhesive modules and assembling cells into defined patterns. Here, we present a different approach to guide cell assembly by tuning the organic-inorganic interactions. Our method involves engineering cells to express a silicifying peptide on their surfaces, which promotes silica deposition on the cell walls. This peptide simultaneously binds to the silica synthesized on adjacent cells, triggering cell clustering. The engineered cells exhibit rapid aggregation, with approximately 95% of cells assembling within 15 min. We further show that this capability can facilitate materials assembly and chemical production. Our biosilicification-based approach offers novel insights into natural multicellularity mechanisms and holds potential for applications in biomanufacturing and materials engineering.

关键词： Bioengineering Synthetic biology Biomaterials

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Non-Periodic Lower-Limb Motion Recognition with Noncontact Capacitive Sensing

Non-Periodic Lower-Limb Motion Recognition with Noncontact C...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Enhao Zheng Jinchen Zeng Dongfang Xu Qining Wang Hong Qiao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences No. 95 of Zhongguancun East Road Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing 30 Xueyuan Road Beijing Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

Noncontact captive sensing is a new sensing strategy that we proposed previously to compensate for the limitations of existing surface electromyography studies for exoskeleton control. It has been validated on locomotion mode recognition and gait phase estimation. However, our previous studies addressed the tasks of periodic ambulation based on machine learning algorithms. The performances of the capacitive sensing on non-periodical lower-limb motion recognition have never been evaluated. In this preliminary study, we designed a motion recognition method by fusing the capacitive sensing and the inertial sensors. The recognition algorithm was designed based on the combined logics, which freed the system from burdensome training procedures in the recognition tasks. The method was validated on three healthy subjects in performing 6 lower-limb motions and the transitions between them (10 in total). The capacitance-inertial fusion method produced an average precision/recall of >0.92 in static motions and >0.86 with transitions. The most prominent improvement of using the capacitance signals is that it increases the time-response ability during the motion transitions. Compared with purely using inertial sensors, the sensor fusion method reduced more than 100-ms latency on average. The pilot study extends the scope of the new sensing method in human motion recognition. Future efforts will be paid in this direction to get more promising results.

关键词： Robot sensing systems Capacitance Electrodes Task analysis Legged locomotion Exoskeletons

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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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Adaptive tracking control of flapping wing micro-air vehicles with averaging theory

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CAAI Transactions on Intelligence Technology 2018年第1期3卷 18-27页

作者： Chen Qian Yongchun Fang Institute of Robotics and Automatic Information Systems College of Computer and Control Engineering Tianjin 300353People's Republic of China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin 300353 People's Republic of China

An input constrained adaptive tracking controller is designed for flapping micro aerial vehicles, wherein the moving averaging filter is adopted to estimate the averaged states of the system. Specifically, in the outer loop controller, an observer is constructed to estimate the disturbances within the system. Moreover, the constrained thrust is designed to keep the frequency in a proper region so as to meet the requirement of average estimation. Then, a tracking differentiator is used to provide trackable trajectories for the inner loop. Subsequently, a new quaternion- based hybrid attitude tracking controller is designed which successfully deals with high-frequency noises and avoids possible chattering. As supported by mathematical analysis, the proposed control strategy guarantees the uniform ultimate boundedness of the closed-loop system, and it keeps the control torques within the permitted range to meet the application requirement. At last, numerical simulations are carried out to support the validity of the proposed controller, whose results are satisfactory even when the thrust and torques are saturated.

关键词：飞行器跟踪器人工智能发展现状

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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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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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