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Infrared Dim Small Target Detection Algorithm Based on Adaptive Attention Transformer Network

Journal of Shanghai Jiaotong University (Science) 2025年 1-13页

作者： Ding, Leqi Xia, Yilin Wang, Biyun Cai, Yunze Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China National Key Laboratory of Air-based Information Perception and Fusion Henan Luoyang471009 China Shanghai Institute of Aerospace Control Technology Infrared Detection Technology R & D Center of China Aerospace Science and Technology Corporation Shanghai201109 China

This paper presents a novel algorithm for detecting infrared dim small targets in complex backgrounds by integrating both global and local feature information. The proposed method employs an adaptive attention transformer network which addresses challenges associated with computational complexity and information redundancy in traditional self-attention mechanisms. A global context aggregation module is designed to address the loss of small target features in high-level feature maps. This module compensates for spatial distribution information during the multi-scale feature fusion process, ensuring the preservation of target features. Comparison experiments were conducted on two datasets, NUAA-SIRST and IRSTD-1k. The proposed algorithm achieved 0.784 for mIoU and 0.878 for F-measure on NUAA-SIRST, 0.632 for mIoU and 0.807 for F-measure on IRST-1k, all of which are the highest values. The proposed algorithm shows a significant improvement over other existing detection algorithms, demonstrating its capability to accurately extract both local and global features of targets with high recall rates and low false alarm rates across various scenarios. The ablation study results highlight the significant improvements contributed by the key modules to the proposed algorithm. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： A adaptive attention global context aggregation module infrared dim small target detection TP391.4 Transformer network

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Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 702-711页

作者： YAN Congqiang GUO Zhengyun CAI Yunze Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240China China Airborne Missile Academy Luoyang471009HenanChina National Key Laboratory of Air-Based Information Perception and Fusion Luoyang471000HenanChina

The study on ship wakes of synthetic aperture radar(SAR)images holds great importance in detecting ship targets in the *** this study,we focus on the issues of low quantity and insufficient diversity in ship wakes of SAR images,and propose a method of data augmentation of ship wakes in SAR images based on the improved cycle-consistent generative adversarial network(CycleGAN).The improvement measures mainly include two aspects:First,to enhance the quality of the generated images and guarantee a stable training process of the model,the least-squares loss is employed as the adversarial loss function;Second,the decoder of the generator is augmented with the convolutional block attention module(CBAM)to address the issue of missing details in the generated ship wakes of SAR images at the microscopic *** experiment findings indicate that the improved CycleGAN model generates clearer ship wakes of SAR images,and outperforms the traditional CycleGAN models in both subjective and objective aspects.

关键词： synthetic aperture radar(SAR) ship wake data augmentation cycle-consistent generative adversarial network(CycleGAN) attention mechanism

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Path Planning Based on A-Star and Dynamic Window Approach Algorithm for Wild Environment

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 725-736页

作者： DONG Dejin DONG Shiyin ZHANG Lulu CAI Yunze Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai200240China Shanghai Electro-Mechanical Engineering Institute Shanghai201109China

The path planning problem of complex wild environment with multiple elements still poses *** paper designs an algorithm that integrates global and local planning to apply to the wild environmental path *** modeling process of wild environment map is *** optimization strategies are designed to improve the A-Star in overcoming the problems of touching the edge of obstacles,redundant nodes and twisting paths.A new weighted cost function is designed to achieve different planning ***,the improved dynamic window approach(DWA)is designed to avoid local optimality and improve time efficiency compared to traditional *** the necessary path re-planning of wild environment,the improved A-Star is integrated with the improved DWA to solve re-planning problem of unknown and moving obstacles in wild environment with multiple *** improved fusion algorithm effectively solves problems and consumes less time,and the simulation results verify the effectiveness of improved algorithms above.

关键词： path planning path re-planning wild environment A-Star algorithm dynamic window approach

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Multi-Objective Loosely Synchronized Search for Multi-Objective Multi-Agent Path Finding with Asynchronous Actions

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 667-677页

作者： DU Haikuo GUO Zhengyu ZHANG Lulu CAI Yunze Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai200240China China Airborne Missile Academy LuoyangHenan471000China National Key Laboratory of Air-based Information Perception and Fusion LuoyangHenan471000China

In recent years,the path planning for multi-agent technology has gradually matured,and has made breakthrough *** main difficulties in path planning for multi-agent are large state space,long algorithm running time,multiple optimization objectives,and asynchronous action of multiple *** solve the above problems,this paper first introduces the main problem of the research:multi-objective multi-agent path finding with asynchronous action,and proposes the algorithm framework of multi-objective loose synchronous(MO-LS)*** combining A*and M*,MO-LS-A*and MO-LS-M*algorithms are respectively *** completeness and optimality of the algorithm are proved,and a series of comparative experiments are designed to analyze the factors affecting the performance of the algorithm,verifying that the proposed MO-LS-M*algorithm has certain advantages.

关键词： multi-agent path finding multi-objective path planning asynchronous action loosely synchronous search

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AIoT for Aircraft Final Assembly:An Intelligent and Collaborative Framework

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Journal of Communications and information Networks 2024年第3期9卷 262-276页

作者： Cheng Ren Xiaojing Wen Xinping Guan Cailian Chen Yehan Ma Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Aircraft final assembly line(AFAL)involves thousands of processes that must be completed before ***,the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery *** the advent of artificial intelligence of things(AIoT)technologies has introduced advancements in certain AFAL scenarios,systematically enhancing the intelligence level of the AFAL and promoting the widespread deployment of artificial intelligence(AI)technologies remain significant *** address these challenges,we propose the intelligent and collaborative aircraft assembly(ICAA)framework,which integrates AI technologies within a cloud-edge-terminal *** ICAA framework is designed to support AI-enabled applications in the AFAL,with the goal of improving assembly efficiency at both individual and multiple process *** analyze specific demands across various assembly scenarios and introduce corresponding AI technologies to meet these *** three-tier ICAA framework consists of the assembly field,edge data platform,and assembly cloud platform,facilitating the collection of heterogeneous terminal data and the deployment of AI *** framework enhances assembly efficiency by reducing reliance on manual labor for individual processes and fostering collaboration across multiple *** provide detailed descriptions of how AI functions at each level of the ***,we apply the ICAA framework to a real AFAL,focusing explicitly on the flight control system testing *** practical implementation demonstrates the effectiveness of the framework in improving assembly efficiency and promoting the adoption of AIoT technologies.

关键词： intelligent aircraft final assembly line AIoT cloud-edge-terminal framework design

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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Synthesis of Failure-Robust Plans for Multi-Robot systems Under Temporal Logic Specifications 19

Synthesis of Failure-Robust Plans for Multi-Robot Systems Un...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Huang, Feifei Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Department of Automation Shanghai200240 China

ISBN: (纸本)9798350320695

In this study, we address the multi-robot path planning problem for tasks specified by linear temporal logic (LTL) formulae. Unlike existing studies, we take into account the possibility of robot failures, where a failed robot can no longer contribute to the completion of the LTL task. Our objective is to find a failure-robust path, which ensures that the LTL task can always be fulfilled, even if a maximum number of robots fail at any point during execution. To achieve this, we extend the mixed-integer linear programming (MILP) approach to the failure-robust setting. To overcome the computational complexity, we identify a fragment of LTL formulae called the free-union-closed LTL, which allows for more scalable synthesis without considering the global combinatorial issue. We present case studies to demonstrate our findings. Our approach provides a novel solution to the problem of multi-robot path planning under robot failures, offering a practical and efficient way to achieve robustness in the face of unforeseen events. © 2023 IEEE.

关键词： Multipurpose robots

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Boosting Explore-Exploit Behavior for Navigating Vehicle by Maintaining Informative Topological Frontier

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Liu, Qiming Cui, Xinru Liu, Zhe Wang, Hesheng Department of Automation Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

Target search in unknown environments places high demands not only on an autonomous vehicle's ability to perceive and interpret target cues, but also on its conscious of collecting these cues by active exploration. While existing navigation methods have successfully built target-driven policies by maintaining memory of explored areas, there has been a lack of focus on facilitating target-aware exploration-the informative frontier information at unexplored yet visible areas is often overlooked. In this paper, we introduce a novel topology-based memory structure, Frontier-enhanced Topological Memory (FTM), and a Hierarchical Topology Encoding and Extraction (HTEE) module, fostering the autonomous vehicle's awareness of both environmental exploration and target approach. Specifically, FTM innovatively incorporates informative ghost nodes on traditional topological map to represent unexplored yet visible regions. We leverage an online-trained implicit scene representation to estimate the positions and generate features of these ghost nodes. The HTEE then employs implicit graph convolutions and attention mechanisms to extract cognitive information from FTM, taking into account the hierarchical memory structure, target cues, and current state. Our design bolsters cognitive navigation decisions. The experiments in the high-fidelity environments, including performance tests, visualizations, and interpretability experiments, validate the effectiveness of our approach in enhancing the vehicle's exploratory behavior. The improved exploration awareness for target cue collection, in turn, enhances the success rate and path efficiency of target search. Furthermore, we demonstrate the adaptability of our algorithm in real-world physical environments. IEEE

关键词： Data mining

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control Parameter Adjustment and Transmission Power Optimization for Vehicle Platoons with Communication Outage 41

Control Parameter Adjustment and Transmission Power Optimiza...

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第41届中国控制会议

作者： Qiaoni Han Chang Liu Hongjiu Yang Zhiqiang Zuo School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The advantage of vehicle platoons is reflected in their tighter inter-vehicle ***,under the non-ideal communication environment,communication outage occurs which may cause the distance between adjacent vehicles too close to result in a collision *** the communication outage with predecessor following between vehicles in a platoon,and applying the constant time headway policy,firstly,this paper quantifies the relationship among headway time,control parameter and communication reliability probability while satisfying plant stability and string ***,given a communication reliability probability,the parameter space method is used to obtain the range of the control parameter,so as to ensure platoon ***,we optimize the transmission power of vehicles to minimize the worst outage probability by some transformation and the adoption of the Perron-Frobenius *** this way,an iterative update rule is presented to obtain the optimal transmission ***,the simulation results demonstrate the effectiveness of the proposed control parameter adjustment method and power optimization scheme.

关键词： Plant stability String stability Outage probability Parameter adjustment Power optimization

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A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

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Energy and AI 2024年第4期18卷 368-379页

作者： Weipeng Li Yuting Chong Xin Guo Jun Liu School of Automation and Information Engineering Xi’an University of TechnologyNo.5 Jinhua South RoadXi’an710048ShaanxiChina Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No.5 Jinhua South RoadXi’an710048ShaanxiChina

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power *** data-driven forecasting methods are regarded as an effective ***,the inherent randomness and nonlinearity of wind power systems,along with the abundance of redundant information in measurement data,present challenges to forecasting *** integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced driven data-forecasting *** on the seasonal variation characteristics of wind energy,a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is *** effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

关键词： Wind power prediction Data-driven Hybrid model Seasonal feature decomposition Gated recurrent networks Attention mechanism

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