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自动化学报（英文版）
中国自动化学会、中国科学院自动化研究所、中国科技出版传媒股份有限公司
自动化学报（英文版）

中国自动化学会、中国科学院自动化研究所、中国科技出版传媒股份有限公司

双月刊

2329-9266

yan.ou@ia.ac.cn

010-82544459

自动化学报（英文版）/Journal IEEE/CAA Journal of Automatica SinicaCSCDCSTPCD北大核心SCI
查看更多>>《自动化学报》（英文版），刊名为 IEEE/CAA Journal of Automatica Sinica (JAS)，创刊于2014年，由中国自动化学会、中国科学院自动化研究所主办，与IEEE合作，报道自动控制、人工智能、机器人等领域热点和前沿方向的研究成果。JAS被SCI, EI, Scopus等数据库收录，是ESI刊源期刊，也是自动化与控制系统领域唯一的中国主办Q1区SCI期刊。2019年首个JCR影响因子5.129，在自动化与控制领域全球63种SCI期刊中排名第11（前17%），位列Q1区。2019年CiteScore为8.3，位于所属各领域Q1区前列；国内外综合他引影响因子为6.688，在自动化、计算机领域的中国英文期刊中排名第1。
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    UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services:A Multi-Agent Deep Reinforcement Learning Approach

    Jiawen KangJunlong ChenMinrui XuZehui Xiong...
    430-445页
    查看更多>>摘要：Avatars,as promising digital representations and service assistants of users in Metaverses,can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses.However,avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications,e.g.,augmented reality navigation,which consumes intensive computing resources.It is inefficient and impractical for vehicles to process avatar tasks locally.Fortu-nately,migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV)for execution is a promising solution to decrease computation overhead and reduce task pro-cessing latency,while the high mobility of vehicles brings chal-lenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status.To address these challenges,in this paper,we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL)to execute immersive vehicular avatar tasks dynamically.Specifically,we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms.We then design the multi-agent proximal policy optimization(MAPPO)approach as the MADRL algo-rithm for the avatar task migration problem.To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO,we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representa-tion of relationships among agents.Finally,to motivate terrestrial or non-terrestrial edge servers(e.g.,RSUs or UAVs)to share computation resources and ensure traceability of the sharing records,we apply smart contracts and blockchain technologies to achieve secure sharing management.Numerical results demon-strate that the proposed approach outperforms the MAPPO approach by around 2％and effectively reduces approximately 20％of the latency of avatar task execution in UAV-assisted vehicular Metaverses.
      原文链接:
    • 万方数据

    Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space

    Nuo ChenLinjing LiWenji Mao
    446-458页
    查看更多>>摘要：The pursuit-evasion game models the strategic inter-action among players,attracting attention in many realistic sce-narios,such as missile guidance,unmanned aerial vehicles,and target defense.Existing studies mainly concentrate on the cooper-ative pursuit of multiple players in two-dimensional pursuit-eva-sion games.However,these approaches can hardly be applied to practical situations where players usually move in three-dimen-sional space with a three-degree-of-freedom control.In this paper,we make the first attempt to investigate the equilibrium strategy of the realistic pursuit-evasion game,in which the pursuer fol-lows a three-degree-of-freedom control,and the evader moves freely.First,we describe the pursuer's three-degree-of-freedom control and the evader's relative coordinate.We then rigorously derive the equilibrium strategy by solving the retrogressive path equation according to the Hamilton-Jacobi-Bellman-Isaacs(HJBI)method,which divides the pursuit-evasion process into the navigation and acceleration phases.Besides,we analyze the maxi-mum allowable speed for the pursuer to capture the evader suc-cessfully and provide the strategy with which the evader can escape when the pursuer's speed exceeds the threshold.We fur-ther conduct comparison tests with various unilateral deviations to verify that the proposed strategy forms a Nash equilibrium.
      原文链接:
    • 万方数据
    • 维普

    Sparse Reconstructive Evidential Clustering for Multi-View Data

    Chaoyu GongYang You
    459-473页
    查看更多>>摘要：Although many multi-view clustering(MVC)algo-rithms with acceptable performances have been presented,to the best of our knowledge,nearly all of them need to be fed with the correct number of clusters.In addition,these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space.The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects,likely leading to performance degradation.To address these issues,we propose a novel sparse reconstructive multi-view evidential clus-tering algorithm(SRMVEC).Based on a sparse reconstructive procedure,SRMVEC learns a shared affinity matrix across views,and maps multi-view objects to a 2-dimensional human-readable chart by calculating 2 newly defined mathematical met-rics for each object.From this chart,users can detect the number of clusters and select several objects existing in the dataset as cluster centers.Then,SRMVEC derives a credal partition under the framework of evidence theory,improving the fault tolerance of clustering.Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory.Besides,SRMVEC delivers effectiveness on benchmark datasets by out-performing some state-of-the-art methods.
      原文链接:
    • 万方数据
    • 维普

    Even Search in a Promising Region for Constrained Multi-Objective Optimization

    Fei MingWenyin GongYaochu Jin
    474-486页
    查看更多>>摘要：In recent years,a large number of approaches to constrained multi-objective optimization problems(CMOPs)have been proposed,focusing on developing tweaked strategies and techniques for handling constraints.However,an overly fine-tuned strategy or technique might overfit some problem types,resulting in a lack of versatility.In this article,we propose a generic search strategy that performs an even search in a promis-ing region.The promising region,determined by obtained feasi-ble non-dominated solutions,possesses two general properties.First,the constrained Pareto front(CPF)is included in the promising region.Second,as the number of feasible solutions increases or the convergence performance(i.e.,approximation to the CPF)of these solutions improves,the promising region shrinks.Then we develop a new strategy named even search,which utilizes the non-dominated solutions to accelerate conver-gence and escape from local optima,and the feasible solutions under a constraint relaxation condition to exploit and detect fea-sible regions.Finally,a diversity measure is adopted to make sure that the individuals in the population evenly cover the valuable areas in the promising region.Experimental results on 45 instances from four benchmark test suites and 14 real-world CMOPs have demonstrated that searching evenly in the promis-ing region can achieve competitive performance and excellent versatility compared to 11 most state-of-the-art methods tailored for CMOPs.
      原文链接:
    • 万方数据
    • 维普

    A Novel Tensor Decomposition-Based Efficient Detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

    Nianyin ZengXinyu LiPeishu WuHan Li...
    487-501页
    查看更多>>摘要：Unmanned aerial vehicles(UAVs)have gained sig-nificant attention in practical applications,especially the low-alti-tude aerial(LAA)object detection imposes stringent require-ments on recognition accuracy and computational resources.In this paper,the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net)is proposed,where the TT-format TD(tensor decomposition)and equal-weighted response-based KD(knowledge distillation)methods are designed to minimize redundant parameters while ensuring com-parable performance.Moreover,some robust network structures are developed,including the small object detection head and the dual-domain attention mechanism,which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features.Considering the imbalance of bounding box regression samples and the inaccuracy of regres-sion geometric factors,the focal and efficient IoU(intersection of union)loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy.The proposed TDKD-Net is comprehensively evaluated through extensive experiments,and the results have demonstrated the effectiveness and superiority of the developed methods in com-parison to other advanced detection algorithms,which also present high generalization and strong robustness.As a resource-efficient precise network,the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net,which provides useful insights on handling imbalanced issues and real-izing domain adaptation.
      原文链接:
    • 万方数据
    • 维普

    End-to-End Paired Ambisonic-Binaural Audio Rendering

    Yin ZhuQiuqiang KongJunjie ShiShilei Liu...
    502-513页
    查看更多>>摘要：Binaural rendering is of great interest to virtual reality and immersive media.Although humans can naturally use their two ears to perceive the spatial information contained in sounds,it is a challenging task for machines to achieve binaural rendering since the description of a sound field often requires multiple channels and even the metadata of the sound sources.In addition,the perceived sound varies from person to person even in the same sound field.Previous methods generally rely on indi-vidual-dependent head-related transferred function(HRTF)datasets and optimization algorithms that act on HRTFs.In prac-tical applications,there are two major drawbacks to existing methods.The first is a high personalization cost,as traditional methods achieve personalized needs by measuring HRTFs.The second is insufficient accuracy because the optimization goal of traditional methods is to retain another part of information that is more important in perception at the cost of discarding a part of the information.Therefore,it is desirable to develop novel tech-niques to achieve personalization and accuracy at a low cost.To this end,we focus on the binaural rendering of ambisonic and propose 1)channel-shared encoder and channel-compared atten-tion integrated into neural networks and 2)a loss function quan-tifying interaural level differences to deal with spatial informa-tion.To verify the proposed method,we collect and release the first paired ambisonic-binaural dataset and introduce three met-rics to evaluate the content information and spatial information accuracy of the end-to-end methods.Extensive experimental results on the collected dataset demonstrate the superior perfor-mance of the proposed method and the shortcomings of previous methods.
      原文链接:
    • 万方数据
    • 维普

    Fixed-Time Sliding Mode Control With Varying Exponent Coefficient for Modular Reconfigurable Flight Arrays

    Jianquan YangChunxi YangXiufeng ZhangJing Na...
    514-528页
    查看更多>>摘要：The modular system can change its physical struc-ture by self-assembly and self-disassembly between modules to dynamically adapt to task and environmental requirements.Rec-ognizing the adaptive capability of modular systems,we intro-duce a modular reconfigurable flight array(MRFA)to pursue a multifunction aircraft fitting for diverse tasks and requirements,and investigate the attitude control and the control allocation problem by using the modular reconfigurable flight array as a platform.First,considering the variable and irregular topological configuration of the modular array,a center-of-mass-indepen-dent flight array dynamics model is proposed to allow control allocation under over-actuated situations.Secondly,in order to meet the stable,fast and accurate attitude tracking performance of the MRFA,a fixed-time convergent sliding mode controller with state-dependent variable exponent coefficients is proposed to ensure fast convergence rate both away from and near the sys-tem equilibrium point without encountering the singularity.It is shown that the controller also has fixed-time convergent charac-teristics even in the presence of external disturbances.Finally,simulation results are provided to demonstrate the effectiveness of the proposed modeling and control strategies.
      原文链接:
    • 万方数据
    • 维普

    Multi-UAVs Collaborative Path Planning in the Cramped Environment

    Siyuan FengLinzhi ZengJining LiuYi Yang...
    529-538页
    查看更多>>摘要：Due to its flexibility and complementarity,the multi-UAVs system is well adapted to complex and cramped worksp-aces,with great application potential in the search and rescue(SAR)and indoor goods delivery fields.However,safe and effec-tive path planning of multiple unmanned aerial vehicles(UAVs)in the cramped environment is always challenging:conflicts with each other are frequent because of high-density flight paths,colli-sion probability increases because of space constraints,and the search space increases significantly,including time scale,3D scale and model scale.Thus,this paper proposes a hierarchical collab-orative planning framework with a conflict avoidance module at the high level and a path generation module at the low level.The enhanced conflict-base search(ECBS)in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock.And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety.Moreover,we specifically designed and published the cramped environment test set containing vari-ous unique obstacles to evaluating our framework performance thoroughly.Experiments are carried out relying on Rviz,with multiple flight missions:random,opposite,and staggered,which showed that the proposed method can generate smooth coopera-tive paths without conflict for at least 60 UAVs in a few minutes.The benchmark and source code are released in https://github.com/inin-xingtian/multi-UAVs-path-planner.
      原文链接:
    • 万方数据
    • 维普

    Dendritic Learning-Incorporated Vision Transformer for Image Recognition

    Zhiming ZhangZhenyu LeiMasaaki OmuraHideyuki Hasegawa...
    539-541页
      原文链接:
    • 万方数据
    • 维普

    Parallel Light Fields:A Perspective and A Framework

    Fei-Yue WangYu Shen
    542-544页
      原文链接:
    • 万方数据