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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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Frequency Information Matters for image Matting 1

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Luo, Rongsheng Wei, Rukai Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Wuhan National Laboratory For Optoelectronics Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031476341

ISBN: (纸本)9783031476334

image matting aims to estimate the opacity of foreground objects in order to accurately extract them from the background. Existing methods are only concerned with RGB features to obtain alpha mattes, limiting the perception of local tiny details. To address this issue, we introduce frequency information as an auxiliary clue to accurately distinguish foreground boundaries and propose the Frequency Matting Network (FMN). Specifically, we deploy a Frequency Boosting Module (FBM) in addition to the Discrete Cosine Transform (DCT) to extract frequency information from input images. The proposed FBM is a learnable component that empowers the model to adapt to complex scenarios. Furthermore, we design a Domain Aggregation Module (DAM) to effectively fuse frequency features with RGB features. With the assistance of frequency clues, our proposed FMN achieves significant improvements in matting accuracy and visual quality compared with state-of-the-art methods. Extensive experiments on Composition-1k and Distinctions-646 datasets demonstrate the superiority of introducing frequency information for image matting. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Discrete cosine transforms

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Fast on-ship route planning using improved sparse A-star algorithm for UAVs

Fast on-ship route planning using improved sparse A-star alg...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yang, Xin Ding, Mingyue Zhou, Chengping Cai, Chao Yu, Qi Shao, Shuai Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

This paper presented improved Sparse A-Star Search (SAS) algorithm to pursue a fast route planner for Unmanned Aerial Vehicles (UAVs) on-ship applications. Our approach can quickly produce 3-D trajectories composed by a set of successive navigation points from certain known initial locations to predetermined target locations. The result routes are not only ensuring collision avoidance with the environmental obstacles, but also satisfying specific routes constraints and objectives. The experiment results demonstrated the feasibility of the method, which makes our route planner be more useful in real systems. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Ships

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Path planning for UAV based on quantum-behaved particle swarm optimization

Path planning for UAV based on quantum-behaved particle swar...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Fu, Yangguang Ding, Mingyue Zhou, Chengping Cai, Chao Sun, Yangguang Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Task Allocation and Path Planning for Multiple Destinations Oriented Towards Task Updates 6

Task Allocation and Path Planning for Multiple Destinations ...

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6th International Conference on Industrial Artificial intelligence, IAI 2024

作者： Yang, Yong He, Dingxin Mao, Huantao Chen, Hong Wu, Hongtao Liu, Zhi-Wei Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350356618

This study addresses the complexities of orchestrating multi-target transportation tasks within multi-agent systems, constrained by load capacity. The primary objective is to engineer an advanced path planning framework that assures collision avoidance and optimal load distribution. Diverging from conventional single-path strategies, this research incorporates load factors and requires continuous dynamic multi-target point and path planning to ensure agents can efficiently navigate through a series of predetermined key points. To address this complex requirement, a two-stage multi-agent task allocation and path planning method is proposed. First, an initial solution is obtained using a suboptimal algorithm, followed by optimization iterations using the large neighborhood search algorithm to improve task allocation. In the second stage, an accelerated algorithm based on priority search is used to plan optimal paths for each agent in a predetermined order. The proposed algorithm's effectiveness is comprehensively evaluated through a series of experimental evaluations and comparisons with the commercial solver Gurobi within a limited time. The results show that the proposed method achieves optimality in both running time and minimum path cost while ensuring the load balance of agents. © 2024 IEEE.

关键词： Motion planning

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Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-control for Intelligent Vehicles

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1658-1672页

作者： Hong Mo Yinghui Meng Fei-Yue Wang Dongrui Wu the College of Electric and Information Engineering Changsha University of Science and TechnologyChangsha 410114China the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Qingdao Academy of Intelligent Industries Qingda 266109 the Center of China Economic and Social Security University of Chinese Academy of SciencesBeijing 100190China the Ministry of Education Key Laboratory on Image Information Processing and Intelligent Control the School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Intelligent vehicles can effectively improve traffic congestion and road traffic *** cruise followingcontrol(ACFC)is a vital part of intelligent *** this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of ***,a traditional variable time headway model is improved considering the acceleration of the lead ***,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating *** reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control ***,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)***,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different ***,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

关键词： Adaptive cruise following-control(ACFC) feedforward+fuzzy proportion integration(PI)feedback(F+FPIF) type-2 fuzzy control variable time headway

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image fusion algorithm using nonsubsampled contourlet transform

Image fusion algorithm using nonsubsampled contourlet transf...

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MIPPR 2007: Multispectral image processing

作者： Yang, Xiao Zhiguo, Cao Kai, Wang Zhengxiang, Xu Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong Uni. of Sci. and Tech. Wuhan 430074 China

ISBN: (纸本)9780819469519

In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-sacle NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.

关键词： image fusion

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Speckle reduction of SAR images using support vector machine in wavelet domain

Speckle reduction of SAR images using support vector machine...

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MIPPR 2005: SAR and Multispectral image processing

作者： Cheng, Hui Yu, Qiuze Tian, Jinwen Liu, Jian Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China College of Information Science and Engineering Jianghan University Wuhan 430034 China

The granular appearance of speckle noise in synthetic aperture radar (SAR) imagery makes it very difficult to visually and automatically interpret SAR data. Therefore, speckle reduction is a prerequisite for many SAR image processing tasks. We develop a speckle reduction algorithm by fusing the wavelet denoising technique with support vector machine (SVM). Based on the least squares support vector machine (LS-SVM) with Gaussian radial basis function kernel, a new denoising operators used in the wavelet domain are obtained. Simulated SAR images and real SAR images are used to evaluate the denoising performance of our proposed algorithm along with another wavelet-based denoising algorithm, as well as the refined Lee speckle filter. Experimental results show that the that the proposed filter method outperforms standard wavelet denoising techniques in terms of the ratio images and the equivalent-number-of-looks measures in most cases. It also achieves better performance than the refined Lee filter.

关键词： image analysis

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A Smart Mathematic Morphology Method for Recognition and Understanding of Airfield

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Wuhan University Journal of Natural Sciences 2005年第5期10卷 867-872页

作者： WANG Zhi-cheng TIAN Yan TIAN Jin-wen LIU Jian LIANG Chao-sheng TAO Wen-bin State Education Commission Key Laboratory for Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 Hubei China Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Hubei China

A method used for recognition and understanding of airfield based on mathematical morphology is proposed in this paper. The new approach can he divided into three steps. First, to extract the typical geometric structure features of airfield, a segmentation method called recursive Otsu algorithm is employed on an airfield image. Second, thinning and shrinking algorithms are utilized to obtain the contour of airfield with single pixel and to remove diffused small particles. Finally, Radon transform is adopted to extract two typical and important components, primary and secondary runways of airfield exactly. At the same time, region growing algorithm is exploited to get the other components such as parking apron and garages. The experimental results demonstrate that the proposed method gives good performance.

关键词： mathematical morphology shrinking algorithm Radon transform Region growing

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Four development stages of collective intelligence

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Frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 903-916页

作者： Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

The new generation of artificial intelligence(AI)research initiated by Chinese scholars conforms to the needs of a new information environment changes,and strives to advance traditional artificial intelligence(AI 1.0)to a new stage of AI *** one of the important components of AI,collective intelligence(CI 1.0),i.e.,swarm intelligence,is developing to the stage of CI 2.0(crowd intelligence).Through in-depth analysis and informative argumentation,it is found that an incompatibility exists between CI 1.0 and CI ***,CI 1.5 is introduced to build a bridge between the above two stages,which is based on biocollaborative behavioral *** 1.5 is the transition from CI 1.0 to CI 2.0,which contributes to the compatibility of the two ***,a new interpretation of the meta-synthesis of wisdom proposed by Qian Xuesen is *** meta-synthesis of wisdom,as an improvement of crowd intelligence,is an advanced stage of bionic intelligence,i.e.,CI *** is pointed out that the dual-wheel drive of large language models and big data with deep uncertainty is an evolutionary path from CI 2.0 to CI 3.0,and some elaboration is *** a result,we propose four development stages(CI 1.0,CI 1.5,CI 2.0,and CI 3.0),which form a complete framework for the development of *** different stages are progressively improved and have good *** to the dominant role of cooperation in the development stages of CI,three types of cooperation in CI are discussed:indirect regulatory cooperation in lower organisms,direct communicative cooperation in higher organisms,and shared intention based collaboration in *** division is the main form of achieving cooperation and,for this reason,this paper investigates the relationship between the complexity of behavior and types of labor ***,based on the overall understanding of the four development stages of CI,the future development direction and research issues of CI are explored.

关键词： Collective intelligence Meta-synthesis of wisdom Incompatibility Labor division Cooperative behavior Collective intelligence emergence Large language model

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