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Mixed Motivation Driven Social Multi-Agent Reinforcement Learning for Autonomous Driving

IEEE/CAA Journal of Automatica Sinica 2025年第6期12卷 1272-1282页

作者： Long Chen Peng Deng Lingxi Li Xuemin Hu State Key Laboratory of Multimodal Artificial Intelligence Systems and the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing WAYTOUS Inc. Beijing Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China School of Computer Science and Information Engineering Hubei University Wuhan China Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA School of Artificial Intelligence Hubei University Wuhan Key Laboratory of Intelligent Sensing System and Security (Hubei University) Ministry of Education Wuhan China

Despite great achievement has been made in autonomous driving technologies, autonomous vehicles (AVs) still exhibit limitations in intelligence and lack social coordination, which is primarily attributed to their reliance on single-agent technologies, neglecting inter-AV interactions. Current research on multi-agent autonomous driving (MAAD) predominantly focuses on either distributed individual learning or centralized cooperative learning, ignoring the mixed-motive nature of MAAD systems, where each agent is not only self-interested in reaching its own destination but also needs to coordinate with other traffic participants to enhance efficiency and safety. Inspired by the mixed motivation of human driving behavior and their learning process, we propose a novel mixed motivation driven social multi-agent reinforcement learning method for autonomous driving. In our method, a multi-agent reinforcement learning (MARL) algorithm, called Social Learning Policy Optimization (SoLPO), which takes advantage of both the individual and social learning paradigms, is proposed to empower agents to rapidly acquire self-interested policies and effectively learn socially coordinated behavior. Based on the proposed SoLPO, we further develop a mixed-motive MARL method for autonomous driving combined with a social reward integration module that can model the mixed-motive nature of MAAD systems by integrating individual and neighbor rewards into a social learning objective for improved learning speed and effectiveness. Experiments conducted on the MetaDrive simulator show that our proposed method outperforms existing state-of-the-art MARL approaches in metrics including the success rate, safety, and efficiency. More-over, the AVs trained by our method form coordinated social norms and exhibit human-like driving behavior, demonstrating a high degree of social coordination.

关键词： Measurement Reinforcement learning Safety Driver behavior Autonomous vehicles Optimization

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3D printing for tissue/organ regeneration in China

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Bio-Design and Manufacturing 2025年第2期8卷 169-242,I0001,I0002页

作者： Chaofan He Jiankang He Chengtie Wu Changshun Ruan Qi Gu Yongqiang Hao Yang Wu Shuo Bai Xiaoxiao Han Liliang Ouyang Jun Yin Hongzhao Zhou Zhuo Xiong Maobin Xie Lei Shao Jing Nie Liang Ma Cijun Shuai Changchun Zhou Xin Zhao Xuetao Shi Mengfei Yu Jiayin Fu Peng Wen Huixia Xuan Yuan Pang Yan’en Wang Yuan Sun Ziqi Gao Abdellah Aazmi Jingbo Zhang Tianhong Qiao Qixiang Yang Ke Yao Mao Mao Jianxin Hao Pinpin Wang Jirong Yang Huawei Qu Xinhuan Wang Xin Liu Shen Ji Shasha Liu Jingke Fu Bingxian Lu Mohan Wu Feng Chen Zihao Zheng Boqing Zhang Muyuan Chai Chaoying Zhang Mouyuan Sun Bo Peng Huayong Yang Yong He State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050China Research Center for Human Tissue and Organ Degeneration Institute of Biomedicine and BiotechnologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Organ Regeneration and Reconstruction State Key Laboratory of Membrane BiologyInstitute of ZoologyChinese Academy of SciencesBeijing 100101China Beijing Institute for Stem Cell and Regenerative Medicine Beijing 100101China Shanghai Engineering Research Center of Innovative Orthopaedic Instruments and Personalized Medicine Clinical and Translational Research Center for 3D Printing TechnologyShanghai 200011China School of Biomedical Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Biochemical Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Key Laboratory of Biopharmaceutical Preparation and Delivery Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China National Engineering Research Centre for High Efficiency Grinding Hunan UniversityChangsha 410082China Biomanufacturing Center Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Tribology in Advanced Equipment Tsinghua UniversityBeijing 100084China The Fourth Affiliated Hospital of Guangzhou Medical University Guangzhou 511436China School of Biomedical Engineering Guangzhou Medic

As surgical procedures transition from conventional resection to advanced tissue-regeneration technologies,human disease therapy has witnessed a great leap *** particular,three-dimensional(3D)bioprinting stands as a landmark in this setting,by promising the precise integration of biomaterials,cells,and bioactive molecules,thus opening up a novel avenue for tissue/organ *** by the editorial board of Bio-Design and Manufacturing,this review brings together a cohort of leading young scientists in China to dissect the core functionalities and evolutionary trajectory of 3D bioprinting,by elucidating the intricate challenges encountered in the manufacturing of transplantable *** further delve into the translational pathway from scientific research to clinical application,emphasizing the imperativeness of establishing a regulatory framework and rigorously enforcing quality-control ***,this review outlines the strategic landscape and innovative achievements of China in this field and provides a comprehensive roadmap for researchers worldwide to propel this field collectively to even greater heights.

关键词： 3D printing Bioprinting Tissue engineering Regenerative medicine

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Visual Sensor-Based Trajectory Multimodality Prediction via Anchor-Free Query Attention Network

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Wang, Ruiping Cheng, Jun Yu, Junzhi Nanyang Technological University School of Computer Science and Engineering Jurong West Singapore639798 Singapore Peking University College of Engineering Beijing100871 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

As a core component of intelligent surveillance and autonomous driving systems, visual sensor-based trajectory multimodality prediction can significantly improve their perception and decision-making capabilities. Numerous existing trajectory prediction methods are dedicated to enhance prediction performance. However, they still fail to effectively model the complex spatiotemporal interactions among pedestrians and trajectory multimodality. To address the above challenges, this article presents one new trajectory multimodality prediction method via anchor-free query-based attention network, which can more effectively capture spatiotemporal interactions and model trajectory multimodality. First, the initial trajectory proposal module employs target-centered query-based attention to capture complex spatiotemporal interactions and generate multiple trajectory proposals corresponding to the multiple modes of the future trajectory, which allows the model to use different interaction information when decoding trajectory points at different time steps. Second, the novel trajectory refinement module utilizes the learnable trajectory proposals to construct proposal-level interaction mechanisms to refine future trajectories. Experimental results conducted on ETH and UCY datasets demonstrate that the proposed model can provide the state-of-the-art prediction performance. © 1963-2012 IEEE.

关键词： Prediction models

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Cross-Scale Synthesis of Organic High-k Semiconductors Based on Spiro-Gridized Nanopolymers

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Research 2022年第2期2022卷 111-122页

作者： Dongqing Lin Wenhua Zhang Hang Yin Haixia Hu Yang Li He Zhang Le Wang Xinmiao Xie Hongkai Hu Yongxia Yan Haifeng Ling Jin'an Liu Yue Qian Lei Tang Yongxia Wang Chaoyang Dong Linghai Xie Hao Zhang Shasha Wang Ying Wei Xuefeng Guo Dan Lu Wei Huang Centre for Molecular Systems and Organic Devices(CMSOD) State Key Laboratory of Organic Electronis and Information Displays&Institute of Advanced Materials(AM)Nanjing University of Posts.Telecommunications9 Wenyuan RoadNarnjing 210023China National Symnchrotron Radiationr Laboratory Anhui Provincial Engincering Laboratory of Advanced Functional Polymer FilmCAS Key Laboratory of Soft Matter ChemistryUniversity of Science and Technology of ChinaHgfei 230026China School of Plysics State Key Laboratory of Crystal MaterialsShandong UniversityJinanShardong 250100China Beijing National Laboratony for Molecular Scences National Biomedical Imaging CenterCollege of Chemistry and Molecular EngineeringPeking UniversityBejing 100871China Frontiers Science Center for Flexible Electronics(FSCFE) MIIT Key Laboratory of Flexible Electronics(KLoFE)Northwestern Polytechnical UntiversityXian 710072China State Key Laboratory of Supramolecular Structure and Materias College of Chemistyjilin University2699 Qianjin AvenueChangchun 130012China

High dielectric constants in organic semiconductors have been identified as a central challenge for the improvement in not only piexoelectric,preolecric,and freeltric efcts but also photoclecric conversion eficiency in OPVs,carrier mobility in OFETS,and charge density in charge-trapping ***,we report an ultralong persistence length(≈41 nm)efet of spiro-fused organic nanopolymers on dielectric properties,together with excitonic and charge carrier *** state-of-the-art nanopolymers,namely,nanopolyspirogrids(NPSGs),are synthesized via the simple crossscale Friedel-Crafts polygridlization of AjB-type *** high dielectric constant(k=8.43)of NPSG is firstly achieved by locking spiro-polygridization efect that results in the enhancement of dipole *** doping into a polystyrene-based dielectric layer,such a high-k feature of NPSG increases the feld-ffct carrier mobility from 0.20 to 0.90cm^(2)Vl s'in pentacene OFET ***,amorphous NPSG film exhibits an ultralow energy disorder(<50 meV)for an exellent zero-field hole mobility of 3.94×10^(-1)cm^(2)V^(-1)s^(-1).surpassing most of the amorphousπconjugated polymers Onganic nanopolymers with high dielectric constants open a new way to break through the bottleneck of eficiency and multifunctionality in the blueprint of the fourth generation semiconductors.

关键词： dielectric charge amorphous

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Trajectory Control of Multi-Axis Robotic Arms Based on Physics-Informed Neural Networks and Nonlinear Model Predictive Control

Trajectory Control of Multi-Axis Robotic Arms Based on Physi...

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Chinese Automation Congress (CAC)

作者： Yiqing Wang Changqing Xia Xi Jin Chi Xu Yanzhu Zhang School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Multi-axis robotic arms are extensively utilized in intelligent manufacturing scenarios, with trajectory control in flexible scenarios constituting a primary challenge. Physics-Informed Neural Networks (PINNs) represent advanced methods that integrate physical laws with data-driven approaches. Despite their outstanding performance in integrating theory and data, research on their application for controlling robotic arms in complex scenarios remains limited. This paper establishes a nonlinear dynamic model based on the physical relationships between the axes of robotic arms. In the absence of prior data, Sobol sequence random sampling is employed to generate data, which are subsequently trained using PINNs. Considering system noise, the Extended Kalman Filter (EKF) is utilized to predict the next state in noisy environments, and Nonlinear Model Predictive Control (NMPC) is implemented to control the robotic arm for trajectory tracking, achieving real-time control. Simulation results demonstrate that the proposed Discrete Physics-Informed Predictive Control (DPIPC) method exhibits smaller position and velocity errors with less fluctuation compared to the method in the reference, indicating superior control capabilities.

关键词： Fluctuations Trajectory tracking Simulation Noise Neural networks Manipulators Real-time systems Trajectory Manufacturing Predictive control

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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Acoustically Activated Nozzle for Microdroplet Generation and Dispensing

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Physical Review Applied 2023年第2期20卷 024067-024067页

作者： Qiu Yin Xiuyuan Li Zhichao Ma Wenming Zhang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai 200240 China Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University No. 800 Dongchuan Road Shanghai 200240 China

Droplet-based microfluidic has emerged as a versatile tool for widespread applications, such as biochemical analysis and synthesis, for which the generation and manipulation of the microdroplets are fundamental. Acoustic based droplet control has shown advantages of good biocompatibility and widescale tunability. Here, we demonstrate an acoustic controlled nozzle that is integrated with both generation and directed dispensing of microdroplets. The system can generate monodisperse microdroplets with tunable sizes (50–641 µm) at a highest throughput of 2000 droplets per second. Besides, by tuning the acoustic frequency, the droplets can be steered to different directions after their formation, realizing on-demand dispensing of the microdroplets. The controlled microdroplet generation and dispensing are both attributed to the acoustic streaming effect induced by the nozzle vibration. Two basic mechanisms for the droplet control were studied: (1) the correlation between the droplet size and the acoustic actuation time, (2) the dependence of the droplet dispensing direction on the acoustic frequency. This work paves the way towards programmable control over acoustic generation and dispensing of microdroplets, which has great potential in the applications of bio-chemical analysis and synthesis.

关键词： Drops

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Microfluidics-based strategies for molecular diagnostics of infectious diseases

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Military Medical Research 2022年第6期9卷 727-753页

作者： Xin Wang Xian-Zhe Hong Yi-Wei Li Ying Li Jie Wang Peng Chen Bi-Feng Liu The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics&Molecular Imaging Key Laboratory Systems Biology ThemeDepartment of Biomedical EngineeringCollegeof Life Science and TechnologyHuazhong University of Scienceand TechnologyWuhan 430074China State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics Wuhan National Laboratory for OptoelectronicsNational Centre for Magnetic Resonancein WuhanWuhan Institute of Physics and MathematicsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of Sciences-Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430071China Department of Radiology Canary Center at Stanford for Cancer Early DetectionSchool of MedicineStanford UniversityPalo AltoCA 94304USA

Traditional diagnostic strategies for infectious disease detection require benchtop instruments that are inappropriate for point-of-care testing(POCT). Emerging microfluidics, a highly miniaturized, automatic, and integrated technology,are a potential substitute for traditional methods in performing rapid, low-cost, accurate, and on-site *** diagnostics are widely used in microfluidic devices as the most effective approaches for pathogen *** review summarizes the latest advances in microfluidics-based molecular diagnostics for infectious diseases from academic perspectives and industrial outlooks. First, we introduce the typical on-chip nucleic acid processes,including sample preprocessing, amplification, and signal read-out. Then, four categories of microfluidic platforms are compared with respect to features, merits, and demerits. We further discuss application of the digital assay in absolute nucleic acid quantification. Both the classic and recent microfluidics-based commercial molecular diagnostic devices are summarized as proof of the current market status. Finally, we propose future directions for microfluidics-based infectious disease diagnosis.

关键词： Microfluidics Molecular diagnostics Infectious disease Point-of-care testing(POCT) Digital assay

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Cryo-EM structures of human m6A writer complexes

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细胞研究（英文版） 2022年第11期32卷 982-994页

作者： Shichen Su Shanshan Li Ting Deng Minsong Gao Yue Yin Baixing Wu Chao Peng Jianzhao Liu Jinbiao Ma Kaiming Zhang State Key Laboratory of Genetic Engineering Collaborative Innovation Center of Genetics and DevelopmentMultiscale Research Institute of Complex SystemsDepartment of Biochemistry and BiophysicsSchool of Life SciencesFudan UniversityShanghaiChina MOE Key Laboratory for Cellular Dynamics and Division of Life Sciences and Medicine University of Science and Technology of ChinaHefeiAnhuiChina MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhouZhejiangChina National Facility for Protein Science in Shanghai Zhangjiang LaboratoryShanghai Advanced Research InstituteChinese Academy of ScienceShanghaiChina State Key Laboratory of Genetic Engineering Collaborative Innovation Center of Genetics and DevelopmentMultiscale Research Institute of Complex SystemsDepartment of Biochemistry and BiophysicsSchool of Life SciencesFudan UniversityShanghaiChina Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Guangdong-Hong Kong Joint Laboratory for RNA MedicineRNA Biomedical InstituteMedical Research CenterSun Yat-Sen Memorial HospitalSun Yat-Sen UniversityGuangzhouGuangdongChina

N6-methyladenosine(m6A)is the most abundant ribonucleotide modification among eukaryotic messenger *** m6A"writer"consists of the catalytic subunit m6A-METTL complex(MAC)and the regulatory subunit m6A-METTL-associated complex(MACOM),the latter being essential for enzymatic ***,we report the cryo-electron microscopy(cryo-EM)structures of MACOM at a 3.0-A resolution,uncovering that WTAP and VIRMA form the core structure of MACOM and that ZC3H13 stretches the conformation by binding ***,the 4.4-? resolution cryo-EM map of the MACOM-MAC complex,combined with crosslinking mass spectrometry and GST pull-down analysis,elucidates a plausible model of the m6A writer complex,in which MACOM binds to MAC mainly through WTAP and METTL3 *** combination with in vitro RNA substrate binding and m6A methyltransferase activity assays,our results illustrate the molecular basis of how MACOM assembles and interacts with MAC to form an active m6A writer complex.

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Flapping-Wing Robot Achieves Multi-Domain Locomotion Using Transformable Wheel Mechanism

Flapping-Wing Robot Achieves Multi-Domain Locomotion Using T...

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IEEE International Conference on robotics and Biomimetics

作者： Xiangxiao Chai Shihua Wang Erzhen Pan Wenfu Xu School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

The difficulty of moving from aquatic to aerial environment is one of the major challenges limiting the development of trans-medium multi-domain locomotion vehicles. In this paper, the concept of the transformable wheel, a feature commonly found in autonomous land vehicles (AL V s), is introduced into the design. Additionally, a flapping-wing robot equipped with multi-domain locomotion capability, which can not only realize aerial flight and surface navigation on water, but also ascend from water to land for subsequent takeoff is presented. The paper first introduces the system design of the robot and proposes the corresponding multi-domain locomotion strategy. Subsequently, the design of the transformable wheel mechanism is described in detail and the force analysis for the water-exit is conducted. The feasibility of the proposed strategy is experimentally validated, confirming the prototype's multi-domain locomotion performance finally. This research explores the feasibility of introducing the transformable wheel mechanism into trans-medium multi-domain vehicle platforms and provides a design example.

关键词： Legged locomotion Torque Limiting Navigation Propellers Roads Wheels Prototypes Motors System analysis and design

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