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IEEE International Conference on Unmanned Systems (ICUS)

作者： Hu Zhang Shuai Wang Tonglin Liu Aimin Zhou Yi Zhang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China School of Mechanical Engineering Changzhou University Changzhou China Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University Shanghai China

In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP.

关键词： Missiles Optimization Path planning Turning Planning Target tracking Sociology

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Multisensor image adaptive fusion based on nonsubsampled contourlet

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Jisuanji Xuebao/Chinese Journal of Computers 2009年第11期32卷 2227-2238页

作者： Chang, Xia Jiao, Li-Cheng Jia, Jian-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Information Engineering Jingdezhen Ceramic Institute Jingdezhen Jiangxi 333002 China

An adaptive fusion method of multisensor images based on nonsubsampled contourlet transform is proposed in this paper, which can select the fusion weights of the low-frequency coefficients adaptively via golden section algorithm. The nonsubsampled contourlet transform is a flexible multi-scale, multi-direction and shift-invariant image decomposition, which is suitable for representing images bearing abundant detail and directional information. This is employed for fusing the directional high-frequency coefficients. For the directional high-frequency coefficients, the higher adding level of the directional subbands is used to select the better coefficient for fusion. The nonsubsampled contourlet transform can also avoids introducing ringing artifacts to fused images compared to ordinary method. Experimental results show that the proposed method achieves better fusion efficiency compared to image fusion methods based on Laplacian pyramid transform, wavelet transform, stationary wavelet transform and contourlet transform respectively.

关键词： Contourlet transform

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Distributed Observer Design over Directed Switching Topologies

arXiv

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arXiv 2024年

作者： Xu, Haotian Liu, Shuai Wang, Bohui Wang, Jingcheng School of Control Science and Engineering Shandong University Jinan250061 China The School of Aerospace Science and Technology Xidian University Xi’an710071 China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

The distributed observer design problem holds significant importance in cases in which the output information of a system is decentralized across different subsystems. Each subsystem has a local observer and access to one part of the measurement outputs and information exchanged through communication networks. This paper focuses on the design of distributed observer with jointly connected directed switching networks. The problem presents challenges due to passive switching modes and the open-loop unboundedness that results from local observability. To overcome these challenges, we develop a network transformation mapping method whereby each local observer can classify itself into an independent subgraph based on independent judgment. Next, an observable decomposition and reorganization method is developed for the digraph case to ensure that each subgraph possesses independent dynamic properties. Asymptotic omniscience is then proven using a developed recursive proof method. This paper includes many previous results as special cases, because most are only suitable for undirected switching topologies or fast-switching cases. An adaptive coupling gain design is proposed to simplify the calculation and verification of conditions that guarantee asymptotic omniscience. Finally, simulation results with the power system show the validity of the developed theory. © 2024, CC BY.

关键词： Continuous time systems

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A registration-aided domain adaptation network for 3D Point cloud based place recognition

arXiv

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arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics 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 Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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An Improved Adaptive Exponential Smoothing Model for Short-term Travel Time Forecasting of Urban Arterial Street

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Acta Automatica Sinica 2008年第11期34卷 1404-1409页

作者： Zhi-Peng LI Hong YU Yun-Cai LIU Fu-Qiang LIU Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 P. R. China Intelligent Transportation System Department Shanghai Electrical Apparatus Research Institute Shanghai 200063 P. R. China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 P. R. China

Short-term forecasting of travel time is essential for the success of intelligent transportation system. In this paper, we review the state-of-art of short-term traffic forecasting models and outline their basic ideas, related works, advantages and disadvantages of each model. An improved adaptive exponential smoothing (IAES) model is also proposed to overcome the drawbacks of the previous adaptive exponential smoothing model. Then, comparing experiments are carried out under normal traffic condition and abnormal traffic condition to evaluate the performance of four main branches of forecasting models on direct travel time data obtained by license plate matching (LPM). The results of experiments show each model seems to have its own strength and weakness. The forecasting performance of IASE is superior to other models in shorter forecasting horizon (one and two step forecasting) and the IASE is capable of dealing with all kind of traffic conditions.

关键词： Travel time short-term forecasting license plate matching (LPM) exponential smoothing

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Constructing multi-modality and multi-classifier radiomics predictive models through reliable classifier fusion

arXiv

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arXiv 2017年

作者： Zhou, Zhiguo Zhou, Zhi-Jie Hao, Hongxia Li, Shulong Chen, Xi Zhang, You Folkert, Michael Wang, Jing Department of Radiation Oncology UT Southwestern Medical Center DallasTX United States High-Tech Institute of Xi'an Xi'an China Department of Information and Control Engineering Xi'an University of Technology Xi'an China School of Computer Science and Technology Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China School of Biomedical Engineering Southern Medical Unversity Guangzhou China Institute of Image Processing and Pattern Recognition Xi'an Jiaotong Unversity Xi'an China

Radiomics aims to extract and analyze large numbers of quantitative features from medical images and is highly promising in staging, diagnosing, and predicting outcomes of cancer treatments. Nevertheless, several challenges need to be addressed to construct an optimal radiomics predictive model. First, the predictive performance of the model may be reduced when features extracted from an individual imaging modality (e.g. PET, CT, MRI) are blindly combined into a single predictive model. Second, because many different types of classifiers are available to construct a predictive model, selecting an "optimal" classifier for a particular application is still challenging. In this work, we developed multi-modality and multi-classifier radiomics predictive models that address the aforementioned issues in currently available models. Specifically, a new reliable classifier fusion strategy was proposed to optimally combine output from different modalities and classifiers. In this strategy, modality-specific classifiers were first trained, and an analytic evidential reasoning (ER) rule was developed to fuse the output score from each modality to construct an optimal predictive model. One public datasets and two clinical case studies were performed to validate model performance. The experimental results indicated that the proposed ER rule based radiomics models outperformed the traditional models that rely on a single classifier or simply use combined features from different modalities. Copyright © 2017, The Authors. All rights reserved.

关键词： Diagnosis

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Sensing Matrix Design for MMV Compressive Sensing: An MVDR Approach

Sensing Matrix Design for MMV Compressive Sensing: An MVDR A...

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作者： Zhang, Liang Huang, Lei Li, Bo Yin, Jingwei Bao, Weimin School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Nuance Communication Inc. MontrealQCH3A 3S7 Canada Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology Harbin150001 China Science and Technology Council China Aerospace Science and Technology Cooperation Beijing100048 China College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China

Compressive sensing (CS) has been widely used in vehicular technology including compressive spectrum sensing, sparse channel estimation, and vehicular communications. The complete procedure of CS consists of sparse representation, sparse measurement, and sparse recovery. In the CS, measurement matrix Φ is utilized to sample a sparse signal, while sensing matrix Ψ is exploited for sparse recovery. It is important to properly design the sensing matrix that significantly affects the signal recovery performance. This paper addresses the issue of the sensing matrix design for the CS with multiple measurement vectors (MMV). We first study sufficient conditions for the MMV-CS and then develop three sensing matrix design approaches in different situations. The proposed methods have their roots in the principle of minimum variance distortionless response (MVDR) beamformer. This allows us to optimally determine the sensing matrix in the framework of the MVDR, which amounts to minimizing local cumulative cross-coherence between Φ and Ψ while keeping the columns of Ψ highly correlated to their counterparts of Φ. Simulation results are presented to verify the effectiveness of the proposed methods. © 1967-2012 IEEE.

关键词： Compressed sensing

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An Effective and Real-time Time-Slot Power Detection Method 23

An Effective and Real-time Time-Slot Power Detection Method

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Proceedings of the 3rd International Conference on Electronic Information Technology and Smart Agriculture

作者： Xian Zhang Xinhui Luo Taiguo Qu Dong Yin School of Computer and Artificial Intelligence (School of Software) Huaihua University China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China and Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China Department of Art Design Huaihua Tourism School China School of Computer and Artificial Intelligence (School of Software) Huaihua University China

ISBN: (纸本)9798400716775

To efficiently detect the time-slot power of the Time Division Multiple Access (TDMA) communication systems such as repeaters and base stations in real-time. This article designs a signal-sampling hardware circuit based on the Advanced RISC Machine (ARM) platform and proposes a comprehensive method to calculate the time-slot power values. The signal sampling circuit uses the ADC108S052 chip with an 8-channel linked to the ARM via the Serial Peripheral Interface (SPI), and the time-slot power detection approach consists of a signal timing sampling module, sampling data reading module, and sampling data processing module to compute the detected time-slot power comprehensively. We design experiments to evaluate the efficacy of the approach to detect the time-slot power with the system power-on and normality running condition, the detection of the system CPU resource consumption for the time-slot power, the detection of the error value for the time-slot power, etc. The experimental results demonstrate that the approach can be efficient, and real-time detection of the time-slot power of the TDMA system, the system of repeaters and base stations and other systems of signal coverage, optimization and so on is of great significance.

关键词： ARM Analog-to-Digital Converter (ADC) Signal sampling Time division multiple access Time slot power

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Extended State Observer Based Fault-Tolerant Predictive control for a Four-Mecanum Wheels Mobile Robot

Extended State Observer Based Fault-Tolerant Predictive Cont...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent Systems

作者： Binghao Yang Dongliang Wang Ziling Wen Wu Wei Wenji Li Zhun Fan Key Lab of Digital Signal and Image Processing of Guangdong Province Shantou University Guangdong China School of Department of Electronic and Information Engineering Shantou University Guangdong China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou Guangdong China School of Automation Science and Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

The application of unmanned vehicles in industrial cargo transportation is becoming increasingly widespread, particularly playing a significant role in transporting heavy-duty goods. However, when performing such tasks, whether in single-vehicle transportation or multi-vehicle collaborative transportation, the occurrence of wheel failures can potentially lead to serious safety accidents. Therefore, this paper proposes a fault-tolerant control scheme, establishing a kinematic model considering disturbances and failures, and adopts model predictive control for trajectory tracking. Additionally, an extended state observer is introduced to observe system states and counteract disturbances. To address potential failure issues, a controller reconstruction strategy is proposed. Finally, the effectiveness and superiority of the controller is validated through numerical simulation and comparative experiment.

关键词： Fault tolerance Trajectory tracking Fault tolerant systems Wheels Transportation Kinematics Predictive models Safety State estimation Predictive control

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Chinese Summary Generation Algorithm Based on Contrastive Attention Mechanism

Chinese Summary Generation Algorithm Based on Contrastive At...

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Computer Engineering and intelligent Communications (ISCEIC), International Symposium on

作者： Liupeng Guo Yannan Xiao Yayuan Wen Peizhi Wen School of Computer and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China School of Computer and Information Security Guilin University of Electronic Technology Guilin China School of Electronic and Information Engineering/School of Integrated Circuits GUANGXI Normal University Guilin China

Generative summarization based on the seq2seq model has gained widespread adoption due to the advancements and efficacy of the sequence-to-sequence framework. However, these models encounter challenges in handling out-of-vocabulary words and may produce summaries with factual inaccuracies. This paper addresses these issues by proposing a summarization generation model, MBC, which is built upon the Transformer as the baseline model. Additionally, it incorporates the BERT pre-trained model, pointer generation network, contrastive attention mechanism, and coverage loss. The model employs a pointer generation network to augment its vocabulary coverage capabilities by generating new terms. To enhance the representation of key information from the source text, a contrastive attention mechanism is employed during summary generation. In addition, by introducing coverage loss, the model can reduce repetitive content in the summary. To assess the model’s performance, this paper employs ROUGE values as evaluation metrics and conducts comparative experiments with other models using the LCSTS dataset. The experimental results demonstrate that, in comparison with other models, this model is more adept at attending to salient information within the source text and generating summaries of greater accuracy.

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