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Toward a Maneuverable Miniature Robotic Fish Equipped With a Novel Magnetic Actuator System

IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2020年第7期50卷 2327-2337页

作者： Chen, Xingyu Yu, Junzhi Wu, Zhengxing Meng, Yan Kong, Shihan Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Most existing robotic fish have a large body size driven by servo motor system, while conventional small-sized actuators hardly generate a high swimming performance. This paper reports a miniature untethered robotic fish, whose body length is 69 mm. In particular, a newly designed magnetic actuator system (MAS) is equipped, which guarantees both small-sized dimension and flexibility of the robot. More specifically, the magnetic field generated by a permanent magnet is first investigated based on Biot-Savart law. Then, a novel tail-beating rhythm called magnetically actuated pulse width modulation (MAPWM) is modeled for the new actuator system. Further, an MAPWM-based control method is presented, in which the duty ratio of MAPWAM is innovatively utilized to realize the turning maneuvers for the first time. In addition, Lagrangian method is employed to establish the dynamic model to assess the MAPWM-based control method and the turning performance of the robotic fish. To further improve the maneuverability, the effect of a shape-variable caudal fin is analyzed based on computational fluid dynamics and the built dynamic model. Finally, combined with the MAS, the MAPWM-based control method, and the optimally selected caudal fin, extensive aquatic experiments are conducted on the robotic prototype. The results indicate that the developed miniature robotic fish achieves a considerably higher level of maneuverability in terms of turning radius when compared to swimming robots with equivalent dimensions.

关键词： Magnetosphere Actuators Turning Vibrations Robot kinematics Solenoids Dynamic modeling magnetic actuator system (MAS) maneuverability robotic fish underwater robot

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Design and Visual Servoing control of a Hybrid Dual-Segment Flexible Neurosurgical Robot for Intraventricular Biopsy

Design and Visual Servoing Control of a Hybrid Dual-Segment ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Chen, Jian Chen, Mingcong Zhao, Qingxiang Wang, Shuai Wang, Yihe Xiao, Ying Hu, Jian Chan, Danny Tat Ming Yeung, Kam Tong Leo Chan, David Yuen Chung Liu, Hongbin Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci CASIA Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Chinese Acad Sci CAIR HKISI CAS Hong Kong Inst Sci & Innovat Ctr & Robot HKSAR Hong Kong Peoples R China City Univ Hong Kong Dept Biomed Engn HKSAR Hong Kong Peoples R China CAIR HKISI CAS HKSAR Hong Kong Peoples R China CASIA State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Chinese Univ Hong Kong Dept Surg HKSAR Hong Kong Peoples R China CASIA State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Kings Coll London Sch Biomed Engn & Imaging Sci London SE1 7EU England

ISBN: (纸本)9798350384581;9798350384574

Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgical manipulation deep in the brain. Taking into account the uncertainty of the control model, an image-based visual servoing with online robot Jacobian estimation has been implemented to enhance motion accuracy. Furthermore, the application of model predictive control with constraints significantly bolsters the flexible robot's ability to adaptively track mobile objects and resist external interference. Experimental results underscore that the proposed control system enhances motion stability and precision. Phantom testing substantiates its considerable potential for deployment in neurosurgery.

关键词： Visual servoing

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POLSAR IMAGE FEATURE EXTRACTION BASED ON CO-REGULARIZATION

POLSAR IMAGE FEATURE EXTRACTION BASED ON CO-REGULARIZATION

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Huang, Xiayuan Nie, Xiangli Qiao, Hong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (纸本)9781728163741

Wishart distance of covariance matrices and Euclidean distance of polarimetric features are two important similarity measurements for polarimetric synthetic aperture radar (PolSAR) image classification. This paper proposes a feature extraction method by combing the two distances for PolSAR image classification. Firstly, two weight graphs are constructed based on the two distances to represent the local information of the data. Specifically, the neighbouring samples are sought in a local region to reduce the computation burden and utilize the spatial information. Then the dimensionality reduction model is constructed based on the two weight graphs and co-regularization. The co-regularization aims to minimize the dissimilarity of low-dimensional features corresponding to two graphs. Finally, the obtained low-dimensional features are used for Po1SAR image classification. Experimental results on real PolSAR datasets demonstrate the effectiveness and superiority of the proposed method.

关键词： Wishart distance Euclidean distance of polarimetric features dimensionality reduction PolSAR image classification feature extraction

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Design and Tension Modeling of a Novel Cable-Driven Rigid Snake-Like Manipulator

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JOURNAL OF INTELLIGENT & ROBOTIC systems 2020年第2期99卷 211-228页

作者： Xu, Dawei Li, En Liang, Zize Gao, Zishu Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

In this study, a cable-driven snake-like manipulator with high load capacity and end-positioning accuracy is designed for applications in complex and narrow environments. The Hooke joint-like two degree-of-freedom joint design and the full actuation mode enhanced the rigidity of the robot. The modular link design increased the local flexibility of the robot. Because the cable tension cannot be ignored under high load on the basis of the kinematics model, a cable tension model is established based on rigid body static equilibrium to describe the relationship between posture and cable tension. This provided a foundation for follow-up studies on obstacle avoidance path planning with optimized tension. At the same time, in order to improve the response speed of the motor position controller to the tension change, this study introduces both the tension as the reference model input and the system state variable into the adaptive control method based on model identification and reinforcement learning. The kinematics model and the cable tension model were validated by experiments on the prototype. The practical results of the two adaptive control methods were compared and the result shows that the method based on model identification has a better effect.

关键词： Snake-like manipulator Cable-driven Kinematics Tension model Neural network Reinforcement learning

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Evolution of cooperation in Snowdrift game with Multi-memory mechanism

Evolution of cooperation in Snowdrift game with Multi-memory...

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第42届中国控制会议

作者： Yaojun Liu Xingwen Liu Nyima Tashi Lab.of Complex Systems & Intelligent Control Key Lab.of Electronic Information of State Ethnic Affairs CommissionCollege of Electrical EngineeringSouthwest Minzu University Engineering Research Center for Tibetan Information Processing School of Information Science and TechnologyTibet University

Cooperative behavior has been of great concern in evolutionary game researches because of its important role in social life and natural *** memory can greatly influence the emergence of cooperative behavior,memory-based research on evolutionary games has proliferated in recent *** the present paper,inspired by the well-known "Stanford marshmallow experiment"(SME),we proposed a multi-memory mechanism in Snowdrift game(SDG) on spatial lattice networks whose core lies in what follows:Players are divided into two groups according to individual self-control;different memory lengths are set by group and by time in a single *** simulation results show that our proposed mechanism promotes cooperation level of the considered evolutionary *** specifically,as memory length increases to an intermediate length,the cooperation level increases as *** mechanism with short memory length,the effect of population structure is obvious and small values of adjusting factor can intensively facilitate high-frequency cooperative *** findings may be helpful to understand the connection between population heterogeneity and the emergence of high cooperation.

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Data-Driven control of Distributed Event-Triggered Network systems

arXiv

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arXiv 2022年

作者： Wang, Xin Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70550 Germany Department of Control Science and Engineering Tongji University Shanghai201804 China State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems (a.k.a. network systems). To this end, we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling, under which a model-based stability criterion for the closed-loop network system is derived, by leveraging a discrete-time looped-functional approach. Marrying the model-based criterion with a data-driven system representation recently developed in the literature, a purely data-driven stability criterion expressed in the form of linear matrix inequalities (LMIs) is established. Meanwhile, the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input data. Finally, numerical results corroborate the efficacy of the proposed distributed data-driven ETS in cutting off data transmissions and the co-design procedure. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Online Progressive Instance-Balanced Sampling for Weakly Supervised Vibration Damper Detection

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷

作者： Chen, Minghao Tian, Yunong Li, Zhishuo Li, En Liang, Zize Inst Automat Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Academyof Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Engn Lab Ind Vis & Intelligent Equipment Technol Beijing 100190 Peoples R China

The detection of vibration dampers is important for power systems. Deep learning-based damper detection needs massive annotations, which are labor-intensive and time-consuming. Therefore, weakly supervised object detection (WSOD) is considered. Part domination is the main problem in weakly supervised vibration damper detection. Current WSOD methods neglect that overwhelming negative instances exist in each image during the training phase, which would mislead the training and make detection results stuck in the most discriminative parts of objects. To tackle this problem, an online progressive instance-balanced sampling (OPIS) algorithm based on hard sampling and soft sampling is proposed in this article. The algorithm includes two modules: a progressive instance balance (PIB) module and a progressive instance reweighting (PIR) module. The PIB module, combining random sampling and intersection over union (IoU)-balanced sampling, progressively mines hard negative instances while balancing positive instances and negative instances. The PIR module further utilizes classifier scores and IoUs of adjacent refinements to reweight the weights of positive instances to make the network focus on positive instances. Extensive experimental results on the vibration damper, pattern analysis, statistical modelling and computational learning visual object classes (PASCAL VOC) 2007, and PASCAL VOC 2012 datasets demonstrate that the proposed method can significantly improve the baseline, which is also comparable to many existing methods. In addition, compared with the baseline, the proposed method requires no extra network parameters, and the supplementary training overheads are small.

关键词： Shock absorbers Vibrations Object detection Proposals Training Sampling methods Convolutional neural networks Instance balance multiple instance learning (MIL) progressive sampling vibration damper detection weakly supervised object detection (WSOD)

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Learning control for Air Conditioning systems via Human Expressions

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2021年第8期68卷 7662-7671页

作者： Wei, Qinglai Li, Tao Liu, Derong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China

In this article, a deep reinforcement learning method is developed to solve air conditioning control problems through human expressions. The main contribution of this article is to design a deep reinforcement learning method for air conditioning control problems with human expressions as the input for the first time. The method aims to eliminate human sleepiness and improve people's work efficiency as much as possible. First, the air conditioning system and deep reinforcement learning methods are introduced. Second, the image processing algorithm for human expressions is described. Third, the deep Q-network method is designed to obtain the optimal control policy for air conditioning systems. Finally, simulation results are given to illustrate the present method that can effectively eliminate sleepiness and improve the work environment of people.

关键词： Adaptive dynamic programming air conditioning control deep learning (DL) deep Q-network (DQN) human expressions optimal control reinforcement learning (RL) Q-learning

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A negotiation-based right-of-way assignment strategy to ensure traffic safety and efficiency in lane changes

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IET INTELLIGENT TRANSPORT systems 2021年第11期15卷 1345-1358页

作者： Zhao, Can Li, Zhiheng Li, Li Wu, Xiangbin Wang, Fei-Yue Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen Peoples R China Intel Corp Intel Labs China Beijing Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China

It is widely acknowledged that verifying the safety of autonomous driving strategies requires a substantial body of simulation testing and road testing. In recent years, the formal safety methods represented by Responsibility-Sensitive Safety (RSS) have encouraged low-cost autonomous driving safety research, benefitting from its accurate assessment of safety and clear division of responsibilities. However, how to maintain traffic efficiency while ensuring safety remains a challenge. To address this problem, this paper proposes a formulized negotiation-based lane-changing strategy that makes a trade-off between safety and efficiency. Both theoretical analysis and numerical experimental results shows that compared to RSS, our strategy can noticeably improve the success rate of changing lanes on the premise of safety.

关键词： formal safety methods Traffic engineering computing negotiation-based right-of-way assignment strategy RSS road testing responsibility-sensitive safety assignment strategy autonomous driving strategies road safety traffic efficiency simulation testing road vehicles traffic safety road traffic lane changes low-cost autonomous driving safety research formulized negotiation-based lane-changing strategy

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Federated Services: A Smart Service Ecology with Federated Security for Aligned Data Supply and Scenario-Oriented Demands

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IEEE-CAA JOURNAL OF AUTOMATICA SINICA 2025年第5期12卷 925-936页

作者： Jia, Xiaofeng Li, Juanjuan Wang, Shouwen Qi, Hongwei Wang, Fei-Yue Qin, Rui Zhang, Min Liang, Xiaolong Beijing Big Data Ctr Beijing 100101 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Taipa 999078 Macao Peoples R China Datatang Beijing Technol Co Ltd Beijing 100190 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

This paper introduces federated services as a smart service ecology with federated security to align distributed data supply with diversified service demands spanning digital and societal contexts. It presents the comprehensive researches on the theoretical foundation and technical system of federated services, aiming at advancing our understanding and implementation of this novel service paradigm. First, a thorough examination of the characteristics of federated security within federated services is conducted. Then, a five-layer technical framework is formulated under a decentralized intelligent architecture, ensuring secure, agile, and adaptable service provision. On this basis, the operational mechanisms underlying data federation and service confederation is analyzed, with emphasis on the smart supply-demand matching model. Furthermore, a scenario-oriented taxonomy of federated services accompanied by illustrative examples is proposed. Our work offers actionable insights and roadmap for realizing and advancing federated services, contributing to the refinement and wider adoption of this transformative service paradigm in the digital era.

关键词： Adaptation models Biological system modeling Large language models Taxonomy Smart contracts Distributed databases Ecology Data models Security Research and development Decentralized autonomous organizations and operations decentralized physical infrastructure networks federated security federated services multimodal large language models smart contracts

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