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controlling the depth of a gliding robotic dolphin using dual motion control modes

Science China(Information Sciences) 2020年第9期63卷 217-230页

作者： Jian WANG Zhengxing WU Min TAN Junzhi YU State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESAT College of Engineering Peking University

This paper investigates the performance of the dual mode, namely flipper mode and central pattern generator(CPG) mode, for controlling the depth of a gliding robotic dolphin. Subsequent to considering the errors in dynamic models, we propose a depth control system that combines the line-of-sight(LOS)method with an adaptive control approach(ACA) to deal with uncertainties in the model parameters. First,we establish a full-state dynamic model to conduct simulations and optimize the parameters used in later aquatic experiments. Then, we use the LOS method to transform the control target from the depth to the pitch angle and employ the ACA to calculate the control signal. In particular, we optimize the ACA’s control parameters using simulations based on our dynamic model. Finally, our simulated and experimental results demonstrate not only that we can successfully control the robotic dolphin’s depth, but also that its performance was better than that of the CPG-based control, thus indicating that we can achieve three-dimensional motion by combining flipper-based and CPG-based control. The results of this study suggest valuable ideas for practical applications of gliding robotic dolphins.

关键词： gliding robotic dolphin depth control dual motion adaptive control approach

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Target Defense with Multiple Defenders and an Agile Attacker via Residual Policy Learning

arXiv

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arXiv 2025年

作者： Tao, Jiyue Shen, Tongsheng Zhao, Dexin Zhang, Feitian Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering and the State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China National Innovation Institute of Defense Technology Beijing100071 China

The target defense problem involves intercepting an attacker before it reaches a designated target region using one or more defenders. This letter focuses on a particularly challenging scenario in which the attacker is more agile than the defenders, significantly increasing the difficulty of effective interception. To address this challenge, we propose a novel residual policy framework that integrates deep reinforcement learning (DRL) with the force-based Boids model. In this framework, the Boids model serves as a baseline policy, while DRL learns a residual policy to refine and optimize the defenders’ actions. Simulation experiments demonstrate that the proposed method consistently outperforms traditional interception policies, whether learned via vanilla DRL or fine-tuned from force-based methods. Moreover, the learned policy exhibits strong scalability and adaptability, effectively handling scenarios with varying numbers of defenders and attackers with different agility levels. Copyright © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

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A Multi-view Non-negative Matrix Factorization Single-cell Clustering Algorithm for Missing Data

A Multi-view Non-negative Matrix Factorization Single-cell C...

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2022 International Conference on Algorithms, Data Mining, and Information Technology, ADMIT 2022

作者： Yu, Ailian Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9781665454728

ISBN: (纸本)9781665454728

A significant study focus on the field of bioinformatics has been on how to quickly and accurately accomplish the cell clustering task using computational approaches for single-cell RNA sequencing (scRNA-seq) data. Technical issues with scRNA-seq data include missing values, high noise levels, and a large batch impact. While the single-cell data recovery method based on data filling can enhance data quality, it will subjectively alter the distribution of data. To address the above-mentioned issues, we propose a non-negative matrix factorization clustering algorithm (scMVNMF) based on multi-view data of scRNA-seq. Under the assumption of essentially unchanging original data distribution, it can not only identify the typical low-dimensional representation patterns of multi-view data but also produce final explicable clustering findings. The results of the experiments demonstrate that the suggested algorithm has some advantages over the filling approach in terms of clustering tasks and can maintain a certain level of stability when the quality of single-cell data varies. © 2022 IEEE.

关键词： Non-negative matrix factorization

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Circular Formation Flight control for Unmanned Aerial Vehicles With Directed Network and External Disturbance

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 505-516页

作者： Yangyang Chen Rui Yu Ya Zhang Chenglin Liu School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Advanced Process Control for Light Industry Ministry of EducationInstitute of AutomationJiangnan UniversityWuxi 214122China

This paper proposes a new distributed formation flight protocol for unmanned aerial vehicles(UAVs)to perform coordinated circular tracking around a set of circles on a target *** from the previous results limited in bidirectional networks and disturbance-free motions,this paper handles the circular formation flight control problem with both directed network and spatiotemporal disturbance with the knowledge of its upper *** from the design of a common Lyapunov fiunction for bidirectional cases,we separately design the control for the circular tracking subsystem and the formation keeping subsystem with the circular tracking error as *** the whole control system is regarded as a cascade connection of these two subsystems,which is proved to be stable by input-tostate stability(ISS)*** the purpose of encountering the external disturbance,the backstepping technology is introduced to design the control inputs of each UAV pointing to North and Down along the special sphere(say,the circular tracking control algorithm)with the help of the switching ***,the distributed linear consensus protocol integrated with anther switching anti-interference item is developed to construct the control input of each UAV pointing to east along the special sphere(say,the formation keeping control law)for formation *** validity of the proposed control law is proved both in the rigorous theory and through numerical simulations.

关键词： Directed network external disturbance flight control unmanned aerial vehicles(UAVs)

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Multi-Level Features Fusion for Zero-Shot Object Pose Estimation 26

Multi-Level Features Fusion for Zero-Shot Object Pose Estima...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Huang, Nanxin Xu, Chi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Driven by advancements in industrial production and artificial intelligence, the need for pose estimation of new ob-jects in areas like robotic manipulation and virtual reality is increasing. We introduce a zero-shot object pose estimation approach that identifies the poses of objects excluded from the training dataset, removing the requirement for re-modeling. The method is built around a multi-level features fusion framework de-signed to enhance generalization. First, a trainable feature extraction module filters and selects multi-level features extracted by the backbone network. Unlike traditional convolutional ker-nels, we incorporate a dynamic convolution kernel to enhance the feature extraction capability. Second, in the feature fusion module, we adopt a dynamic weight generation strategy to perform weighted fusion of multi-level features. This method enhances template matching by effectively describing similarities between unseen objects (those absent from the training set) and templates, leveraging robust and adaptive feature representations to narrow the gap with seen objects. Experimental results demonstrate that our approach achieves state-of-the-art performance on two popu-lar benchmark datasets, LineMod and LineMod-Occlusion, proves that our method has better generalization than previous models. © 2025 IEEE.

关键词： Industrial robots

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Conversational Crowdsensing: A Parallel Intelligence Powered Novel Sensing Approach

arXiv

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arXiv 2024年

作者： Zhu, Zhengqiu Zhao, Yong Chen, Bin Qiu, Sihang Xu, Kai Yin, Quanjun Huang, Jincai Liu, Zhong Wang, Fei-Yue College of Systems Engineering National University of Defense Technology Hunan Province Changsha410073 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

The transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 brings new requirements and opportunities to current sensing approaches, especially in light of recent progress in Chatbots and Large Language Models (LLMs). Therefore, the advancement of parallel intelligence-powered Crowdsensing Intelligence (CSI) is witnessed, which is currently advancing towards linguistic intelligence. In this paper, we propose a novel sensing paradigm, namely conversational crowdsensing, for Industry 5.0. It can alleviate workload and professional requirements of individuals and promote the organization and operation of diverse workforce, thereby facilitating faster response and wider popularization of crowdsensing systems. Specifically, we design the architecture of conversational crowdsensing to effectively organize three types of participants (biological, robotic, and digital) from diverse communities. Through three levels of effective conversation (i.e., inter-human, human-AI, and inter-AI), complex interactions and service functionalities of different workers can be achieved to accomplish various tasks across three sensing phases (i.e., requesting, scheduling, and executing). Moreover, we explore the foundational technologies for realizing conversational crowdsensing, encompassing LLM-based multi-agent systems, scenarios engineering and conversational human-AI cooperation. Finally, we present potential industrial applications of conversational crowdsensing and discuss its implications. We envision that conversations in natural language will become the primary communication channel during crowdsensing process, enabling richer information exchange and cooperative problem-solving among humans, robots, and AI. © 2024, CC BY.

关键词： Multi agent systems

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A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services

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Energy and AI 2022年第3期9卷 148-171页

作者： Caizhi Zhang Yuqi Qiu Jiawei Chen Yuehua Li Zhitao Liu Yang Liu Jiujun Zhang Chan Siew Hwa College of Mechanical and Vehicle Engineering The State Key Laboratory of Mechanical TransmissionsChongqing Automotive Collaborative Innovation CentreChongqing UniversityChongqing400044China College of Automation Chongqing UniversityKey Laboratory of Complex System Safety and ControlMinistry of EducationChongqing UniversityChongqing400044China School of Mechanical Engineering University of Science and Technology BeijingBeijing100083China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou310027China Institute for Sustainable Energy/College of Sciences Shanghai UniversityShanghai 200444China School of Mechanical and Aerospace Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore Sichuan Energy Internet Research Institute Tsinghua UniversityChengdu 610213Sichuan ProvinceChina

The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight;hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell,battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.

关键词： Unmanned aerial vehicles(UAVs) Power supply system Fuel cell system Artificial intelligence(AI) Energy management systems

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Design and Performance Analysis of a Series-Parallel Self-Aligning Index Finger Exoskeleton

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IEEE Robotics and Automation Letters 2025年第6期10卷 6456-6463页

作者： Sun, Ning Wang, Zelong Cheng, Long Li, Houcheng Niu, Ben Sun, Xijin Li, Ke Shandong Normal University School of Information Science and Engineering Jinan China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Shandong University Institute of Intelligent Medical Engineering School of Control Science and Engineering Jinan China

Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while providing sufficient assistance torque is still a challenge. This paper develops a series-parallel self-aligning index finger exoskeleton to assist the index finger in flexion/extension and adduction/abduction training. A series-parallel mechanism driven by two motors simultaneously was proposed for the metacarpophalangeal (MCP) joint, which can ensure human-robot joint axes self-alignment and increase the joint assistance torque. A kinematic compatibility analysis method was proposed, and the kinematic compatibility of the series-parallel mechanism was analyzed. The degrees of freedom and forward kinematics of the proposed mechanism were analyzed, and its workspace was calculated, which results show that the motion range of the MCP joint can meet the grasping training requirements. Preliminary experiments were carried out, and the results indicate that the motion trajectory coefficients of the marker points at the MCP, PIP, and DIP joints averaged for all subjects with and without the proposed exoskeleton are 0.993, 0.956, and 0.939, respectively, which can verify the kinematic transparency of the proposed mechanism. The assistance torque generated by the proposed mechanism on the MCP joint can meet the joint assistance torque requirements. In a word, the proposed exoskeleton can achieve flexion/extension and adduction/abduction training, human-robot joint axes self-alignment, and provide sufficient assistance torque. © 2016 IEEE.

关键词： Exoskeleton (Robotics)

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Simulation of High Temperature Thin Film Thermocouple on Engine Blade Surface

Simulation of High Temperature Thin Film Thermocouple on Eng...

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2022 International Conference on Mechatronics and Automation Technology, ICMAT 2022

作者： Zhang, Meiju Tian, Bian Ma, Rong Huang, Manguo Liang, Xiaobo Liu, Jiangjiang Zhang, Zhongkai Beijing Changcheng Aeronautic Measurement and Control Technology Research Institute Beijing101111 China Aviation Key Laboratory of Science and Technology on Special Condition Monitoring Sensor Technology Beijing101111 China State Key Laboratory for Mechanical Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9781643683669

In order to avoid the instability flutter of aero-engine blade and prevent the failure of thin film thermocouple caused by the blade in complex environment, the structural strength of the thermocouple on the actual blade surface was studied in this paper. Firstly, based on the 3D scanning of the real blade, the blade model is established after the point cloud graphics. The surface thermocouple model of the blade is established in Solidworks for simulation, and the modal and harmonic response analysis of the blade is simulated. Secondly, the vibration of the curved thin film thermocouple and the stress distribution of the blade under the acceleration shock were studied in Comsol, and the failure weakness was analyzed to avoid the failure of the thin film thermocouple caused by the bending, fracture or shedding of the thin film thermocouple on the blade due to vibration and shock, providing the most suitable thermocouple selection for the engine blade. © 2022 The authors and IOS Press.

关键词： Thermocouples

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DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network

DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatia...

引用

International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Shaokun Zhang Xinde Li Chuanfei Hu Jianping Xu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Science and Technology on Information Systems Engineering Laboratory Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Recent transformer-based methods for estimating 3D human pose have gained widespread attention, achieving state-of-the-art results. Previous methods have primarily focused on capturing motion patterns of the human body at a single scale or cascading multiple scales, such as joints, bones, and body-parts. However, they are difficult to simultaneously capture spatial-temporal motion patterns of the human body at different scales due to the complex motion patterns. To address this issue, we propose Dual-scale Spatial and Temporal transFormer (DSTFormer), which can concurrently explore the spatial dependencies and temporal motion patterns of human joints and bones. Additionally, we introduce a Gcn-Spatial Transformer Block (GSTB), which introduces Graph Convolutional Networks (GCN) into transformer to enhance the exploitation of local relationships and global information between adjacent joints or bones. Extensive experiments are conducted on the Human3.6M benchmark dataset, and superior results are reported when comparing to other state-of-the-art methods. More remarkably, our model achieves to-date the best published performance, with P1 errors of 37.9 mm and 15.6 mm, respectively.

关键词： Solid modeling Three-dimensional displays Mechatronics Graph convolutional networks Computational modeling Pose estimation Transformers Bones Joints Robots

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