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7th International Conference on Data Mining and Big Data, DMBD 2022

作者： Li, Ding Zhang, Qichao Lu, Shuai Pan, Yifeng Zhao, Dongbin School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Baidu Inc. Beijing100085 China

ISBN: (纸本)9789811992964

Predicting the future trajectories of surrounding vehicles plays a vital role in ensuring the safety of autonomous driving. It is extremely challenging for the pure imitation method due to the high degree of multimodality and uncertainty in the future. In fact, when driving in most traffic scenarios, vehicles should obey some traffic rules such as "vehicles follow the lane and do not collide with each other". Inspired by this, this paper proposes a goal-aware prediction (GAP) framework to predict the multimodal trajectories, where goals are chosen in the lanes with hierarchical interactive representation and a multi-task loss. Based on the graph-based vectorized input, a novel hierarchical interactive representation module is first designed to obtain the fine-grained goal features, which progressively models interactions between goal-to-goal, goal-to-lane, and lane-to-agent, corresponding to the individual, local and global levels, respectively. Then, an auxiliary collision loss is developed to take into account learning from demonstration and injecting common sense of collision avoidance, and is served as a part of the multi-task loss to guide the generation of multimodal plausible trajectories. In the end, the proposed method is verified on the Baidu In-house Cut-in dataset, which includes more than 370K interactive scenarios collected in the real road testing. The comparative results demonstrate the superior performance of our proposed GAP model than the mainstream prediction methods. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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Hydrodynamic Analysis and Verification of an Innovative Whale Shark-like Underwater Glider

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Journal of Bionic Engineering 2020年第1期17卷 123-133页

作者： Huijie Dong Zhengxing Wu Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents an innovative design for a biomimetic whale shark-like underwater glider aiming at the combination of high maneuverability and long *** a hybrid of the underwater glider and the robotic fish,its pectoral fins and tail can serve as not only the external control surfaces for attitude regulation during gliding but also the propellers for agile fish-like swimming *** verify the gliding capability of the whale shark-like glider and prepare for future dynamic analysis,the hydrodynamic coefficients,including drag,lift,sliding force,and corresponding moments are estimated through computational fluid dynamics *** addition,the hydrodynamic analyses of the proposed glider and an equivalent conventional glider during steady gliding motion are executed for *** experiments are performed to verify the downward gliding *** results reveal that the whale shark-like glider has less drag as well as higher lift-to-drag ratio and a markable gliding capability in *** may offer important inspiration for improving the gliding efficiency and performance of an underwater glider in biomimetic shape design.

关键词： biomimetic robot CFD hydrodynamic analysis underwater glider

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A Vehicle-to-Vehicle Cooperative control Method for Intersections with Cav- Dedicated Lane

SSRN

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SSRN 2024年

作者： Zhang, Xiqiao Cui, Leqi Yang, Longhai Lv, Yisheng School of Transportation Science and Engineering Harbin Institute of Technology Harbin150090 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

With the development of intelligent connected technology and autonomous driving technology, connected autonomous vehicles (CAV) and connected human-driven vehicles (CHV) will coexist for a long time in the future. The popularization of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication enables the improvement of CAV platooning efficiency and the joint control of CAV trajectory and signal timing. Therefore, this paper proposes a CAV-dedicated lane-based vehicle-to-vehicle interactive intersection control method, which is suitable for managing mixed traffic flow of CHV and CAV at a single intersection. In the proposed method, the road capacity is enhanced by separating the mixed traffic flow with a CAV-dedicated lane. Through vehicle-to-vehicle interaction and CHV induction, the traffic flow spatiotemporal distribution is regulated by a limited number of controlled vehicles. Furthermore, by jointly controlling CAV trajectory and signal timing, vehicles can efficiently pass through the intersection in the CHV phase without the dedicated CAV phase. The optimization of signal timing and vehicle trajectory at the intersection aims to improve intersection capacity and smooth vehicle trajectories. In addition, the car-following and lane-changing models of CHV are revised based on the prospect theory to validate the performance of platooning strategies under cooperative induction information in practical traffic operations. Simulation results demonstrate that compared to control methods without considering vehicle-to-vehicle interaction, the proposed method in this paper has significant advantages in reducing average vehicle delay and improving intersection efficiency. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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EK-Net++: Real-time scene text detection with expand kernel distance and Epoch Adaptive Weight

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Expert systems with Applications 2025年 267卷

作者： Zhu, Boyuan Chen, Xi Tang, Quan Chen, C.L. Philip Liu, Fagui Computer Science and Engineering South China University of Technology Guangzhou510006 China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen518066 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Recently, scene text detection has received significant attention due to its wide applications. Accurate detection in complex scenes of multiple scales, orientations, and curvature remains a challenge. Component-based methods have emerged as the dominant approach for offering a more flexible way to achieve superior performance. However, Component-based methods employ the Vatti clipping algorithm for multi-instance training to handle the difficulty of arbitrary-shaped text. Yet we identify several bias results from these approaches called the "shrinked kernel" leading to decreased accuracy. Additionally, almost all text detection methods fail to consider the characteristics of different datasets and directly assign fixed loss weights to multi-instances. To address these limitations, we propose a new approach named Expand Kernel Network (EK-Net++), which presents the expand kernel distance map to compensate for the previous deficiency and incorporates three-stage regression to complete integral instance detection. Furthermore, we design the Epoch Adaptive Weight algorithm which dynamically distinguishes the characteristics of different datasets. EK-Net++ not only achieves precise positioning of arbitrary-shaped text but also strikes a balance between performance and speed. Evaluation results show that EK-Net++ attains state-of-the-art or competitive performance compared to other advanced methods, e.g., F-measure of 86.72% at 35.42 FPS on ICDAR 2015, F-measure of 85.83% at 40.13 FPS on CTW1500. © 2024 Elsevier Ltd

关键词： Epoch Adaptive Weight Expand kernel distance Real-time Scene text detection

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Kinematics Analysis of a Manipulator for the Power Transmission Line Maintenance Robot 42

Kinematics Analysis of a Manipulator for the Power Transmiss...

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42nd Chinese control Conference, CCC 2023

作者： Chen, Minghao Li, En Zhang, Feng Guo, Rui Liang, Zize Zhang, Yuwei Institute of Automation The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Shandong Luneng Intelligence Technology Co. Ltd. Jinan250001 China The State Grid Shandong Electric Power Company Jinan250001 China

ISBN: (纸本)9789887581543

With the remarkable development of the power grid, traditional manual maintenance modes cannot meet the requirement of efficiency and reliability. Robotic technology is applied for power line maintenance to bring down risks and ensure inspectors' safety. Based on the power transmission line maintenance platform, a 5-DOF manipulator is designed to perform the maintenance tasks for the quad bundle conductors. Then the kinematics analysis of the manipulator is analyzed. The manipulator doesn't meet the Pieper criterion. So an improved adaptive particle swarm optimization (APSO) is proposed for figuring out the inverse kinematics. The weights of the pose and the constraint of the prismatic joint are introduced to the algorithm. What's more, half of the particles are initialized around the incipient value of joints and half of the particles are randomly initialized with the constraint of joints in this algorithm. Results show that the manipulator is able to work in the environment of quad bundle conductors and the proposed algorithm can improve the precision of inverse kinematics and prevent the leap of joints. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Maintenance

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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Evaluating the Generalization of 3D Detectors with Hybrid Point Clouds 2

Evaluating the Generalization of 3D Detectors with Hybrid Po...

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2nd International Conference on Computer Science and management Technology, ICCSMT 2021

作者： Tian, Yonglin Wang, Xiao University of Science and Technology of China Department of Automation Hefei China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665420631

With the development of LiDAR technologies and deep learning algorithms, tremendous methods have been proposed for 3D detection in intelligent transportation. However, the generalization of 3D detectors under different environments is not fully evaluated due to the lack of diverse testing datasets. Two of the main obstacles in building testing benchmark of point clouds are the huge cost of the annotation of point clouds and the low flexibility in data collection. In this paper, we propose to use hybrid point clouds to evaluate the generalization of multiple 3D detectors when they are transferred from real data to hybrid data. Compared with evaluating 3D detectors with real point clouds dataset, our approach is much more flexible and demands less human labor. © 2021 IEEE.

关键词： Deep learning

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A broadly neutralizing antibody against the SARS-CoV-2 Omicron sub-variants BA.1,BA.2,BA.2.12.1,BA.4,and BA.5

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Signal Transduction and Targeted Therapy 2025年第2期10卷 926-933页

作者： Zhe Chen Leilei Feng Lei Wang Li Zhang Binyang Zheng Hua Fu Fengdi Li Ligai Liu Qi Lv Ran Deng YanLi Xu Yongfeng Hu Jianhua Zheng Chuan Qin Linlin Bao Xiangxi Wang Qi Jin NHC Key Laboratory of Systems Biology of Pathogens State Key Laboratory of Respiratory Health and MultimorbidityNational Institute of Pathogen Biologyand Center for Tuberculosis ResearchChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China CAS Key Laboratory of Infection and Immunity National Laboratory of MacromoleculesInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Department of Vaccine Clinical Evaluation Jiangsu Provincial Center for Disease Prevention and Control172 Jiangsu RoadGulou QuNanjing 210009China Institute of Laboratory Animal Sciences Chinese Academy of Medical Sciences(CAMS)and Comparative Medicine CenterPeking Union Medical Collage(PUMC)Key Laboratory of Human Disease Comparative MedicineMinistry of HealthBeijingChina Beijing Ditan Hospital Capital Medical UniversityBeijing 100015PR China Chronic Disease Management Center Beijing Ditan HospitalCapital Medical UniversityBeijing 100015PR China

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2.(SARS-CoV-2)and its variant strains,including Alpha,Beta,Gamma,Delta,and now Omicron,pose a significant *** the constant evolution of the virus,Omicron and its subtypes BA.1,BA.2,BA.3,BA.4,and BA.5 have developed the capacity to evade neutralization induced by previous vaccination or *** evasion highlights the urgency in discovering new monoclonal antibodies(mAbs)with neutralizing activity,especially broadly neutralizing antibodies(bnAbs),to combat the *** the current study,we introduced a fully human neutralizing mAb,CR9,that targets Omicron *** demonstrated the mAb’s effectiveness in inhibiting Omicron replication both in vitro and in *** analysis using cryo-electron microscopy(cryo-EM)revealed that CR9 binds to an epitope formed by RBD residues,providing a molecular understanding of its neutralization *** its potency and specificity,CR9 holds promise as a potential adjunct therapy for treating Omicron *** findings highlight the importance of continuous mAb discovery and characterization in addressing the evolving threat of COVID-19.

关键词： monoclonal antibodies mabs severe acute respiratory syndrome coronavirus Omicron SARS CoV BA broadly neutralizin

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Data-Driven Optimal control for Half-Vehicle Suspension System via Adaptive Dynamic Programming 11

Data-Driven Optimal Control for Half-Vehicle Suspension Syst...

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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Li, Hongyang Wei, Qinglai School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Systems Engineering Macau University of Science and Technology Macau999078 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In this paper, a data-driven optimal control method is provided for the half-vehicle suspension system via adaptive dynamic programming. The main contribution of this paper is that the data-driven adaptive dynamic programming method is applied to the optimal control problem of half-vehicle suspension system, which only requires the input-state data of the system. First, the structure of the half-vehicle suspension system is analyzed, and the optimal control problem is introduced. Next, the model-based adaptive dynamic programming method is provided. Based on the model-based method, a data-driven adaptive dynamic programming method is given. The properties of the provided methods are analyzed. Finally, simulation example is given to show the effectiveness of the data-driven adaptive dynamic programming method. © 2022 IEEE.

关键词： Dynamic programming

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META-IMITATION LEARNING BY WATCHING VIDEO DEMONSTRATIONS 10

META-IMITATION LEARNING BY WATCHING VIDEO DEMONSTRATIONS

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10th International Conference on Learning Representations, ICLR 2022

作者： Li, Jiayi Lu, Tao Cao, Xiaoge Cai, Yinghao Wang, Shuo School of Artificial Intelligence University of Chinese Academy of Sciences China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences China

Meta-Imitation Learning is a promising technique for the robot to learn a new task from observing one or a few human demonstrations. However, it usually requires a significant number of demonstrations both from humans and robots during the meta-training phase, which is a laborious and hard work for data collection, especially in recording the actions and specifying the correspondence between human and robot. In this work, we present an approach of meta-imitation learning by watching video demonstrations from humans. In comparison to prior works, our approach is able to translate human videos into practical robot demonstrations and train the meta-policy with adaptive loss based on the quality of the translated data. Our approach relies only on human videos and does not require robot demonstration, which facilitates data collection and is more in line with human imitation behavior. Experiments reveal that our method achieves the comparable performance to the baseline on fast learning a set of vision-based tasks through watching a single video demonstration. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

关键词： Robots

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