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Soft Robotics:Morphology and Morphology-inspired Motion Strategy

IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1500-1522页

作者： Fan Xu Hesheng Wang Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

Robotics has aroused huge attention since the *** of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental ***,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured *** decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing *** presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific *** paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

关键词： Soft continuum manipulator soft gripper soft mobile robot soft robot control method soft robot modeling method soft robotics

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Collision-Free Path Planning with Kinematic Constraints in Urban Scenarios

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Journal of Shanghai Jiaotong university(Science) 2021年第5期26卷 731-738页

作者： WANG Liang WANG Bing WANG Chunxiang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China

In urban driving scenarios,owing to the presence of multiple static obstacles such as parked cars and roadblocks,planning a collision-free and smooth path remains a challenging *** addition,the path-planning problem is mostly non-convex,and contains multiple local ***,a method for combining a sampling-based method and an optimization-based method is proposed in this paper to generate a collision-free path with kinematic constraints for urban *** sampling-based method constructs a search graph to search for a seeding path for exploring a safe driving corridor,and the optimization-based method constructs a quadratic programming problem considering the desired state constraints,continuity constraints,driving corridor constraints,and kinematic constraints to perform path *** experimental results show that the proposed method is able to plan a collision-free and smooth path in real time when managing typical urban scenarios.

关键词： autonomous vehicle path planning dynamic searching quadratic programming

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Distributed Identification With Input Design for Network systems

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IEEE Transactions on control of Network systems 2025年

作者： Mao, Xiangyu He, Jianping Fang, Chongrong Shanghai Jiao Tong University The Dept. of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

The distributed identification of network systems under local observation has recently become one of the research hot spots. Due to the unobservable influence of other subsystems and the noise, it is difficult for local subsystems to achieve convergent identification under local observations. This paper proposes a distributed identification algorithm for local subsystems to identify their parameter matrices under local observation with a guarantee of convergence. We obtain the necessary and sufficient conditions for the convergence of local identification. We prove that by injecting an independent random signal to the local subsystem, which is easy to implement, using a simple least-squares method to identify local systems can achieve convergent identification for a certain probability. Meanwhile, we give the minimal level of variance of the injected signal that can still guarantee the convergence of the identification. Next, we add the designed input as a vector of Gaussian noises with decreasing variance to a known controller, proving that it can converge to the original controller. Simulations demonstrate the effectiveness of the proposed algorithms. © 2025 IEEE.

关键词： Least squares approximations

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Jointly Learning Time-Structure-History Graph Embedding for Temporal Knowledge Graph Reasoning 19

Jointly Learning Time-Structure-History Graph Embedding for ...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Duan, Hao Jin, Haoyu Chen, Kang Du, Shaochong Fang, Tao Huo, Hong Shanghai Jiao Tong University Department of Automation Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9798350346558

The Temporal Knowledge Graph(TKG) reasoning is an imperative task for various applications of TKG. However, reasoning over TKGs which aims to predict future facts has been less explored. Intuitively, entities and relations in TKG change differently over time, and the variations are different. It also can be observed that what happens in the past may affect the future. Apart from these, structure information that exists in the neighborhood of a given entity in a KG has been proven to be important. Inspired by these, a novel graph embedding method for TKG reasoning, called time-structure-history graph embedding (TSHGE), is proposed in this paper. TSHGE consists of three progressive learning units. The first time information learning unit employs a novel time-aware mechanism to encode the time influence on entities and relations. Then a relation-aware GAT (Graph Attention Network) is used in the structure information learning unit to model the 1-hop neighborhoods of all entities in a KG at each timestamp in TKG. Finally, the history information learning unit utilizes GRU (Gated Recurrent Unit) to learn history information from various facts. Then the ultimate embedding representations of entities and relations can be obtained for the prediction of future facts. The evaluations on three public TKG datasets have demonstrated the effectiveness and superiority of TSHGE for predicting future facts. © 2022 IEEE.

关键词： Forecasting

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A Secure Parameter Self-Tuning control Scheme for Vehicle Platoons under DoS Attacks 13

A Secure Parameter Self-Tuning Control Scheme for Vehicle Pl...

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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2023

作者： Han, Qiaoni Cheng, Guowen Tang, Zhenning Liu, Chang School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Center for Biomedical Engineering School of Information Science and Technology Fudan University Shanghai200433 China

ISBN: (纸本)9798350315196

In order to mitigate the adverse impact of denial of service (DoS) attacks, this work designs a parameter self-tuning controller based on fuzzy rules for vehicle platoons with vehicle-to-vehicle (V2V) communications. Aiming at achieving the cooperative adaptive cruise control (CACC) of the vehicles with a required inter-vehicle distance and the same velocity, while considering the possible DoS attacks, we propose a parameter self-tuning longitudinal controller combining linear control and fuzzy control to enhance the stability and resilience of the platoon systems. Firstly, by analyzing the dynamic characteristics of vehicles and the mechanism of DoS attacks, we establish the dynamic model of vehicle platoons and model the impact of random DoS attacks as a constant data transmission delay, whose probability distribution can be defined using the Bernoulli random variable. Then, a linear controller based on fuzzy control is designed for longitudinal control to guarantee that the platoon keeps a reference velocity and the specified inter-vehicle distance under DoS attacks. Finally, thorough simulations are performed and the detailed results show the performance of the secure longitudinal control scheme for vehicle platoons in terms of stability and security. © 2023 IEEE.

关键词： Fuzzy control

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Curvature Adaptive control Based Path Following for Automatic Driving Vehicles in Private Area

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Journal of Shanghai Jiaotong university(Science) 2021年第5期26卷 690-698页

作者： SHI Qiang ZHANG Jianlin YANG Ming Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China

Path following refers to traveling along the desired path with automatic steering control,which is a crucial technology for automatic driving *** in private areas are highly irregular,resulting in a large curvature variation,which reduces the control accuracy of the path following.A curvature adaptive control(CAC)based path-following method was proposed to solve the problem mentioned ***,CAC takes advantage of the complementary characteristics in response to the path curvature fluctuation of pure pursuit and front-wheel feedback and by combining the two methods further enhances the immunity of the control accuracy in response to a curvature *** CAC,the quantitative indices of the path curvature fluctuation and control accuracy were *** model between the path curvature fluctuation and a dynamic parameter was identified using the quantitative index of the control accuracy as the optimization *** experimental results of a real vehicle indicate that the control accuracy of path following is further enhanced by its immunity in response to curvature fluctuation improved by the *** addition,CAC is easy to deploy and requires low demand for hardware resources.

关键词： automatic driving vehicles path following adaptive control

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Self-Supervised Depth Estimation Based on the Consistency of Synthetic-real Image Prediction 8

Self-Supervised Depth Estimation Based on the Consistency of...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Tong, Wei Gao, Yubing Wu, Edmond Q. Zhu, Li-Min School of Mechanical Engineering Nanjing University of Science and Technology Jiangsu210014 China Ministry of Education Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China

ISBN: (纸本)9798350300178

Learning-based multi-view stereo aims to restore the real scene from multiple images with overlapping areas. The mainstream self-supervised MVS method trains the model based on the assumption that spatial points from different perspectives share the same color information. To further suppress the interference from specular reflection and illumination noise, this work proposes a self-supervised MVS network based on the consistency of synthetic-real image prediction. The network first applies the coarse-to-fine manner to gradually refine the depth map, and the source images are projected to the reference view to generate the synthesized reference image. Then the synthesized image with real source images are re-input into the network to form a cycled network, and the consistency constraint of the prediction results of the two periods is introduced to improve the color anti-interference of the self- supervised MVS model. The comprehensive experiments on the public dataset show that the proposed work can further improve the reconstruction performance of the benchmark model, which verifies the effectiveness of the proposed work. © 2023 IEEE.

关键词： Forecasting

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Fault Diagnosis and Prognosis in Partially-Observed Discrete Event systems with Delayed Observations 63

Fault Diagnosis and Prognosis in Partially-Observed Discrete...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Wang, Jiwei Baldi, Simone Yu, Wenwu Yin, Xiang Southeast University School of Cyber Science and Engineering Nanjing210096 China Southeast University School of Mathematics Nanjing210096 China Shanghai Jiao Tong University Department of Automation Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9798350316339

Fault diagnosis and prognosis in discrete event systems are studied in the scenario where the observations are possibly received with delay. To address this scenario, two conditions for diagnosis and prognosis with delayed observations are proposed, where we show that the state-of-the-art notion of prognosability must be revised to avoid conservativeness. Diagnosability and prognosability conditions are then verified by introducing a delay observer and a new verification function. Theoretical analysis indicates the effectiveness of the verification method for fault diagnosis and prognosis in the system. © 2024 IEEE.

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Joint Design of control and Transmission for Industrial CPS under Time Sensitive Networking 48

Joint Design of Control and Transmission for Industrial CPS ...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Lu, Xuanzhao Xu, Qimin Zhang, Jinglong Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

To improve the performance of industrial cyber-physical systems (ICPS), the joint design of control and transmission has been shown to be an effective mechanism. However, the existing joint design work lack completeness and accuracy, which brings challenges to improving the stability and network resource utilization of ICPS. In this paper, we propose a control and transmission joint design architecture for integrated multi-subsystem ICPS for multi-hop networks. We consider the timeliness of information through state delays, input delays, and event-triggered states in ICPS. To avoid the instability caused by input delay, we design an LQR-based controller and derive the feasible region of delay to guarantee the stability of the control system. Finally, we propose an event-triggered strategy that represents control and transmission costs to minimize the amount of data transfer while ensuring system stability. The evaluation results show that our strategy improves the stability of the control system while reducing the network burden compared with the traditional joint design method. © 2022 IEEE.

关键词： Cyber Physical system

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Infrastructure-Based Vehicle Localization system for Indoor Parking Lots Using RGB-D Cameras

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 61-69页

作者：曹炳全贺越生庄瀚洋杨明 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong UniversityShanghai 200240China

Accurate vehicle localization is a key technology for autonomous driving tasks in indoor parking lots,such as automated valet ***,infrastructure-based cooperative driving systems have become a means to realizing intelligent *** this paper,we propose a novel and practical vehicle localization system using infrastructure-based RGB-D cameras for indoor parking *** the proposed system,we design a depth data preprocessing method with both simplicity and efficiency to reduce the computational burden resulting from a large amount of ***,the hardware synchronization for all cameras in the sensor network is not implemented owing to the disadvantage that it is extremely cumbersome and would significantly reduce the scalability of our system in mass ***,to address the problem of data distortion accompanying vehicle motion,we propose a vehicle localization method by performing template point cloud registration in distributed depth ***,a complete hardware system was built to verify the feasibility of our solution in a real-world *** in an indoor parking lot demonstrated the effectiveness and accuracy of the proposed vehicle localization system,with a maximum root mean squared error of 5 cm at 15Hz compared with the ground truth.

关键词： infrastructure-based RGB-D camera vehicle localization point cloud registration

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