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arXiv 2024年

作者： Chen, Zizhao Qian, Yeqiang Yang, Xiaoxiao Wang, Chunxiang Yang, Ming Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Multispectral pedestrian detection has been shown to be effective in improving performance within complex illumination scenarios. However, prevalent double-stream networks in multispectral detection employ two separate feature extraction branches for multi-modal data, leading to nearly double the inference time compared to single-stream networks utilizing only one feature extraction branch. This increased inference time has hindered the widespread employment of multispectral pedestrian detection in embedded devices for autonomous systems. To efficiently compress multispectral object detection networks, we propose a novel distillation method, the Adaptive Modal Fusion Distillation (AMFD) framework. Unlike traditional distillation methods, the AMFD framework fully leverages the original modal features from the teacher network, thereby significantly enhancing the performance of the student network. Specifically, a Modal Extraction Alignment (MEA) module is utilized to derive learning weights for student networks, integrating focal and global attention mechanisms. This methodology enables the student network to acquire optimal fusion strategies independent from that of teacher network without necessitating an additional feature fusion module. Furthermore, we present the SMOD dataset, a well-aligned challenging multispectral dataset for detection. Extensive experiments on the challenging KAIST, LLVIP and SMOD datasets are conducted to validate the effectiveness of AMFD. The results demonstrate that our method outperforms existing state-of-the-art methods in both reducing log-average Miss Rate and improving mean Average Precision. The code is available at https://***/bigD233/***. Copyright © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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Cooperative formation tracking for heterogeneous multi-UAVs with faulty sensors of leader measurement 43

Cooperative formation tracking for heterogeneous multi-UAVs ...

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43rd Chinese control Conference, CCC 2024

作者： Lv, Yan Gong, Xiao Yang, Ruohan Fang, Jiayue Miao, Shuo Feng, Zhichao Yu, Yue Beijing Institute of Control and Electronic Technology Key Laboratory of Information System and Technology Beijing100038 China Northwestern Polytechnical University School of Electronics and Information Xi'an710072 China The Rocket Force University of Engineering Xi'an710025 China

ISBN: (纸本)9789887581581

This paper focuses on cooperative formation tracking problem of heterogeneous leader-following multi-UAVs with faulty sensors where the faulty sensors of the followers can only measure the partial output of the leader. First, the kinematic models of heterogeneous multi-UAVs based on the individual speed response time constants are established. Then, by utilizing the output regulation method, a formation controller based on a distributed observer is proposed based on partial outputs obtained by the faulty sensors of the followers. It should be noted that the proposed controller can achieve formation tracking of UAVs with faulty sensors to the leader UAV. Finally, a simulation example is performed to check out the validation of the proposed methods. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Unmanned aerial vehicles (UAV)

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Carrier Frequency Offset Estimation for MIMO OCDM Underwater Acoustic Communications Based on Null Symbols

Carrier Frequency Offset Estimation for MIMO OCDM Underwater...

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第43届中国控制会议

作者： Buyiyi Wang Peishuo Huang Yichen Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of information and Communication Engineering Hainan University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Orthogonal chirp division multiplexing(OCDM) has emerged as a promising approach for underwater acoustic(UWA)*** the constraints of limited bandwidth resources in the underwater environment,enhancing the data transmission rate necessitates leveraging spatial resources ***,we should integrate multiple-input multipleoutput(MIMO) technology with OCDM UWA communication ***,existing MIMO OCDM systems ignore the interference caused by carrier frequency offset(CFO),which is a primary challenge faced by co-located MIMO systems in underwater *** this paper,we propose a CFO estimator based on the null symbols of the Fresnel domain tailored for MIMO OCDM *** estimator regards the energy leakage on null symbols as the objective function to identify the optimal CFO ***,we design pilot allocation strategies for different transmitters to mitigate co-channel interference in MIMO *** enables the estimation of the channel transfer matrix and simultaneous transmission of information,thereby enhancing adaptability to dynamic UWA ***,we derive a low-complexity equalizer *** simulations,the proposed algorithm demonstrates superior communication performance compared to existing algorithms with and without CFO interference.

关键词： Orthogonal chirp division multiplexing(OCDM) carrier frequency offset(CFO) multiple-input multiple-output(MIMO) underwater communications

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Thermally Drawn Monolithic Polymer Continuum Robot with Laser Cutting Profile

Thermally Drawn Monolithic Polymer Continuum Robot with Lase...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Liu, Huanghua Zou, Yun Xu, Zheng Gao, Anzhu Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9798350325706

Continuum robots have the great potential in endoluminal diagnosis and intervention toward narrow and confined workspace. However, fabrication of continuum robots still poses a grant challenge in its miniaturization. To solve this, this paper designs a thermally drawn monolithic polymer continuum robot with laser cutting profile. First, the continuum robot is designed with two degrees of freedom (DOF) for shape deflection, and it consists of four optical fibers with the fiber Bragg grating (FBG) sensor on each for tension sensing as driving cables. Second, its main body is a multi-channel polycarbonate (PC) tube produced by thermal drawing process, and a series of rectangular cutouts are made on it via laser cutting process. By combining these two fabrication processes, the developed continuum robot realizes the integration of the multi-channel structure and the notch feature. Third, a control framework of puller-follower controller using the integrated tension sensing is proposed for teleoperation control. Finally, experimental setup is built for the robot validation, and results show that the repeated positioning accuracy of the robot is 1.08 mm. Moreover, a micro endoscope and a needle are added to the end of the continuum robot, and a phantom study of auripuncture and drug delivery is completed to verify the preliminary feasibility. And the proposed fabrication approach enables the miniaturization and complex structure for the cable-driven continuum robots. © 2023 IEEE.

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Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Strengthened Dominance Relation NSGA-Ⅲ Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

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Computers, Materials & Continua 2024年第1期78卷 375-392页

作者： Liang Zeng Junyang Shi Yanyan Li Shanshan Wang Weigang Li School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan430068China Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan430068China School of Information Science and Engineering Wuhan University of Science and TechnologyWuhan430081China

The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing *** involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple *** Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling ***,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and *** enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence ***,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex *** validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test *** experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.

关键词： Multi-objective job shop scheduling non-dominated sorting genetic algorithm differential evolution simulated binary crossover

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Simultaneous segmentation and classification of colon cancer polyp images using a dual branch multi-task learning network

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Mathematical Biosciences and Engineering 2024年第2期21卷 2024-2049页

作者： Li, Chenqian Liu, Jun Tang, Jinshan School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430065 China Department of Health Administration and Policy College of Public Health George Mason University FairfaxVA22030 United States

Accurate classification and segmentation of polyps are two important tasks in the diagnosis and treatment of colorectal cancers. Existing models perform segmentation and classification separately and do not fully make use of the correlation between the two tasks. Furthermore, polyps exhibit random regions and varying shapes and sizes, and they often share similar boundaries and backgrounds. However, existing models fail to consider these factors and thus are not robust because of their inherent limitations. To address these issues, we developed a multi-task network that performs both segmentation and classification simultaneously and can cope with the aforementioned factors effectively. Our proposed network possesses a dual-branch structure, comprising a transformer branch and a convolutional neural network (CNN) branch. This approach enhances local details within the global representation, improving both local feature awareness and global contextual understanding, thus contributing to the improved preservation of polyp-related information. Additionally, we have designed a feature interaction module (FIM) aimed at bridging the semantic gap between the two branches and facilitating the integration of diverse semantic information from both branches. This integration enables the full capture of global context information and local details related to polyps. To prevent the loss of edge detail information crucial for polyp identification, we have introduced a reverse attention boundary enhancement (RABE) module to gradually enhance edge structures and detailed information within polyp regions. Finally, we conducted extensive experiments on five publicly available datasets to evaluate the performance of our method in both polyp segmentation and classification tasks. The experimental results confirm that our proposed method outperforms other state-of-the-art methods. ©2024 the Author(s), licensee AIMS Press.

关键词： Classification (of information)

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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Efficient Reinforcement Learning for 3D LiDAR Navigation of Mobile Robot 41

Efficient Reinforcement Learning for 3D LiDAR Navigation of ...

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第41届中国控制会议

作者： Yu Zhai Zhe Liu Yanzi Miao Hesheng Wang China University of Mining and Technology MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Developing an efficient automatic navigation system for mobile robots is challenging in the strange scenarios where robots can only observe the environment of the surrounding limited *** other distributed automatic navigation systems exist,they often require extracting semantic information to calculate navigation action,which requires extra modules to provide perceptual information and is not *** propose an end-to-end automatic navigation system based on the reinforcement learning *** particular,the raw 3 D LiDAR data is used to directly map an efficient navigation *** design a novel dense reward function to handle the reward sparsity issue and provide a graphical representation method to enable the efficient feature learning from the raw 3 D LiDAR data in our navigation *** addition,an imitation learning based policy initialization is introduced before the subsequent reinforcement learning,which increases the learning efficiency and,in the meantime,still encouraging the robot to explore all the potential states to achieve advanced performance than the imitated *** navigation model is trained in the Webots environment and the experimental results show that our model has efficient and flexible navigation performance in complex *** importantly,trained model can be easily extended to unfamiliar environments.

关键词： End-to-end Navigation Mobile robot Reinforcement Learning 3D LiDAR

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