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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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Robotic Electrospinning Actuated by Non-Circular Joint Continuum Manipulator for Endoluminal Therapy

arXiv

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arXiv 2021年

作者： Wu, Zicong Lou, Chuqian Jin, Zhu Huang, Shaoping Liu, Ning Zou, Yun Kovac, Mirko Gao, Anzhu Yang, Guang-Zhong Institute of Medical Robotics Department of Bioengineering Shanghai Jiao Tong University Shanghai200240 China Imperial College London Empa Swiss Federal Laboratories for Materials Science and Technology Limited Hong Kong999077 Hong Kong Aerial Robotics Laboratory Imperial College London LondonSW7 2AZ United Kingdom Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatments. © 2021, CC BY-NC-SA.

关键词： Electrospinning

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A Multivariate Time Series Classification based Multiple Fault Diagnosis Method for Hydraulic systems

A Multivariate Time Series Classification based Multiple Fau...

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第三十八届中国控制会议

作者： Xiaohang Zhao Ke Zhang Yi Chai Complex system safety and control Key Laboratory of Ministry of Education School of Automation Chongqing University IEEE Department of Electrical and computer engineering Duke University

Hydraulic systems is a class of nonlinear complex *** are many typical characteristics with the systems:multiple functional components,multiple operation modes,space-time coupling work,and monitoring signals for faults are multivariate time series data,*** of the characteristics,fault diagnosis for Hydraulic systems is not *** fault diagnosis methods mostly ignore the multivariable timing characteristics of monitoring signals,it has made many detection and diagnosis(especially for multiple fault)can not keep high accuracy,and some of the methods are not even be able to multiple fault *** at the problem,a multivariate time series classification based diagnosis method is ***,extracting timing characteristics(transformed features)from the time series data collected via sensors by 1-NN ***,training the transformed features by multi-class OVO-SVM to classify multivariate time *** of the method contains single fault and multiple faults conditions,the results show that the method has high accuracy,it can complete multiple-faults classification.

关键词： fault diagnosis hydraulic systems multivariate time series analysis classification

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The Performance Evaluation and Resilience Analysis of Supply Chain Based on Logistics Network

The Performance Evaluation and Resilience Analysis of Supply...

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Chinese control Conference (CCC)

作者： Weiqi Sun Yuanlong Li Liangren Shi Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing of the Ministry of Education Shanghai P. R. China Shanghai Key Laboratory of Navigation and Location-based Services and Academy of Information Technology and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

With the development of globalization, more and more enterprises are involved in the supply chain network with increasingly complex structure. In this paper, enterprises and relations in the logistics network are abstracted as nodes and edges of the complex network. A graph model for a supply chain network to specified industry is constructed, and the Neo4j graph database is employed to store the graph data. This paper uses the theoretical research tool of complex network to model and analyze the supply chain, and designs a supply chain network evaluation system which include static and dynamic measurement indexes according to the statistical characteristics of complex network. In this paper both the static and dynamic resilience characteristics of the the constructed supply chain network are evaluated from the perspective of complex network. The numeric experimental simulations are conducted for validation. This research has practical and theoretical significance for enterprises to make strategies to improve the anti-risk capability of supply chain network based on logistics network information.

关键词： Supply chains Complex networks Indexes Robustness Resilience

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A Formal Framework of Safety Monitoring of Cyber-Physical systems with Complex Temporal Logic Specifications

A Formal Framework of Safety Monitoring of Cyber-Physical Sy...

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第30届中国过程控制会议（CPCC 2019）

作者： Xiang Yin Zhaojian Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Mechanical Engineering Michigan State University

Safety has been becoming an increasingly important concern in modern control *** this paper, we propose a formal model-based framework for safety monitoring of Cyber-Physical systems(CPS) that are subject to complex logical *** model a CPS as a labeled transition system with a discrete state-space and event-triggered *** safe behavior of the system is described by a Linear Temporal Logic(LTL) *** goal is to monitor whether or not the execution of the dynamic system violates the desired safety *** consider a general setting where the measurement of the system can be imprecise with a threshold value.A new notion called-detectability is proposed to capture whether or not any violation of the temporal logic formula can be determined within a finite number of *** effective algorithm is provided for the verification of-detectability with a polynomial-time ***, we provide a systematic way for the design of online monitor that reports the violation of the safety ***, we apply the proposed framework to a Heating, Ventilation and Air Conditioning(HVAC) system to illustrate our result.

关键词： Safety Monitoring Fault Detection Cyber-Physical systems Temporal Logic Formal Methods

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Nonlinear-Periodic control system for One Class of Non-Affine Stationary Plants with Statement Delays 11

Nonlinear-Periodic Control System for One Class of Non-Affin...

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11th International Conference "Management of Large-Scale system Development", MLSD 2018

作者： Eremin, E.L. Shelenok, E.A. Information and Control Systems Department Amur State University Blagoveshchensk Russia Automation and System Engineering Department Pacific National University Khabarovsk Russia

ISBN: (纸本)9781538649244

Article deals with the problem of synthesis of the nonlinear-periodic control system for one class of control non-affine stationary plants with several statements delays, which are functioning under a priori parametric uncertainty conditions. With the help of computational experiments, the quality of the control system operation is illustrated. The results obtained in the article may be used in the practical implementation of the considered control system. In particular, they can be used for construction of the control systems for manipulation robots and other technical plants (for example, rotor systems) which are operates in the periodic modes. © 2018 IEEE.

关键词： Quality control

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Nonlinear-Periodic control system for Non-Affine Stationary Plant with Statement Delay

Nonlinear-Periodic Control System for Non-Affine Stationary ...

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2018 International Multi-Conference on Industrial engineering and Modern Technologies, FarEastCon 2018

ISBN: (纸本)9781538695357

The article deals with the problem of synthesis of nonlinear regulator of control system for non-affine stationary plant with known constant statement delay. The plant is functions in periodic modes in the presence of constantly acting external perturbations and parametric uncertainty. As solution methods the hyperstability criterion, the fast-acting dynamic corrector, and L-dissipativity conditions are used. The key stage of the synthesis is the receipt for V. M. Popov's inequality special integral estimates that are ensure the fulfillment of the control goal. In final part of the article with the help of simulation the dynamic processes taking place in the proposed management system, which indicate its high quality are being visually illustrated. © 2018 IEEE.

关键词： control system synthesis

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Anchor-based spatio-temporal attention 3D convolutional networks for dynamic 3D point cloud sequences

arXiv

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arXiv 2020年

作者： Wang, Guangming Chen, Muyao Liu, Hanwen Yang, Yehui Liu, Zhe Wang, Hesheng The Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment 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 The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge

With the rapid development of measurwement technology, LiDAR and depth cameras are widely used in the perception of the 3D environment. Recent learning based methods for robot perception most focus on the image or video, but deep learning methods for dynamic 3D point cloud sequences are underexplored. Therefore, developing efficient and accurate perception method compatible with these advanced instruments is pivotal to autonomous driving and service robots. An Anchor-based Spatio-Temporal Attention 3D Convolution operation (ASTA3DConv) is proposed in this paper to process dynamic 3D point cloud sequences. The proposed convolution operation builds a regular receptive field around each point by setting several virtual anchors around each point. The features of neighborhood points are firstly aggregated to each anchor based on the spatio-temporal attention mechanism. Then, anchor-based 3D convolution is adopted to aggregate these anchors' features to the core points. The proposed method makes better use of the structured information within the local region and learns spatio-temporal embedding features from dynamic 3D point cloud sequences. Anchor-based Spatio-Temporal Attention 3D Convolutional Neural Networks (ASTA3DCNNs) are built for classification and segmentation tasks based on the proposed ASTA3DConv and evaluated on action recognition and semantic segmentation tasks. The experiments and ablation studies on MSRAction3D and Synthia datasets demonstrate the superior performance and effectiveness of our method for dynamic 3D point cloud sequences. Our method achieves the state-of-the-art performance among the methods with dynamic 3D point cloud sequences as input on MSRAction3D and Synthia datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

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Online Supervisory control of Networked Discrete-Event systems with control Delays

Online Supervisory Control of Networked Discrete-Event Syste...

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IEEE Annual Conference on Decision and control

作者： Zhaocong Liu Xiang Yin Shaolong Shu Shaoyuan Li Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University China School of Electronics and Information Engineering Tongji University China

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

We investigate state estimation and safe controller synthesis for networked discrete-event systems (DES), where supervisors send control decisions to plants via communication channels subject to communication delays. Previous works on state estimation of networked DES are based on the open-loop system without utilizing the knowledge of the control policy. In this paper, we propose a new approach for online estimation and control of networked DES with control delays. We first propose a new state estimation algorithm for the closed-loop system utilizing the information of control decision history. Then we investigate how to predict the effect of control delays in order to calculate a control decision online at each instant. We show that the proposed online supervisor can be updated effectively and the resulting closed-loop behavior is safe.

关键词： Delays Supervisory control State estimation Safety Closed loop systems Discrete-event systems

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Local Pose optimization with an Attention-based Neural Network

Local Pose optimization with an Attention-based Neural Netwo...

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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Yiling Liu Hesheng Wang Fan Xu Yong Wang Weidong Chen Qirong Tang Department of Automation Shanghai Jiao Tong University Shanghai China State Key Laboratory of Robotics and System (HIT) Beijing Institute of Control Engineering Tongii University

In this paper, we propose a novel pose optimizer which can be inserted into either supervised or unsupervised end-to-end visual odometry for the purpose of local pose optimization. The pose optimizer is an analogue of the pose graph optimization used in traditional VSLAM algorithms. Local pose optimization is performed by an attention-based neural network which iteratively refines the predicted pose estimates of an image snippet. Instead of complicated graph convolutional network, the attention mechanism based on geometric consistency of trajectory constraint is utilized because pose features whose spatial distribution is not important can be flattened to vectors and then processed. The pose optimizer is aimed at improving pose estimation accuracy by redistributing errors of pose estimates. Quantitative and qualitative evaluation of the proposed approach on the KITTI Odometry dataset [1] is presented to demonstrate its effectiveness in improving pose estimation accuracy and minimizing pose drift.

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