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37th AAAI Conference on Artificial Intelligence (AAAI) / 35th Conference on Innovative Applications of Artificial Intelligence / 13th Symposium on Educational Advances in Artificial Intelligence

作者： Pan, Zhiyu Chen, Yinpeng Zhang, Jiale Lu, Hao Cao, Zhiguo Zhong, Weicai Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China Huawei CBG Consumer Cloud Serv Search Prod & Big Shenzhen Peoples R China

ISBN: (纸本)9781577358800

Automatic image cropping algorithms aim to recompose images like human-being photographers by generating the cropping boxes with improved composition quality. Cropping box regression approaches learn the beauty of composition from annotated cropping boxes. However, the bias of annotations leads to quasi-trivial recomposing results, which has an obvious tendency to the average location of training samples. The crux of this predicament is that the task is naively treated as a box regression problem, where rare samples might be dominated by normal samples, and the composition patterns of rare samples are not well exploited. Observing that similar composition patterns tend to be shared by the cropping boundaries annotated nearly, we argue to find the beauty of composition from the rare samples by clustering the samples with similar cropping boundary annotations, i.e., similar composition patterns. We propose a novel Contrastive Composition Clustering (C2C) to regularize the composition features by contrasting dynamically established similar and dissimilar pairs. In this way, common composition patterns of multiple images can be better summarized, which especially benefits the rare samples and endows our model with better generalizability to render nontrivial results. Extensive experimental results show the superiority of our model compared with prior arts.

关键词： image enhancement

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HTRNN: A New Protein Nuclear Localization Prediction Tool

HTRNN: A New Protein Nuclear Localization Prediction Tool

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IEEE Advanced Information Technology, Electronic and Automation control Conference (IAEAC)

作者： Xinyu Miao Wei Li School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of the Education Ministry of China Wuhan China

Current protein nuclear localization assays encounter multiple challenges that underscore the constraints of conventional biochemical assays and sequence-based procedures. This paper highlights the emerging interest in utilizing artificial intelligence to surmount these limitations. Specifically, a supervised deep learning algorithm, employing the HTRNN model, is presented to identify mechanisms responsible for the nuclear location of proteins. This methodology embraces an entire data-driven end-to-end structure, making expert experience or previous biological knowledge unnecessary. By utilizing amino acid sequence features from both the head and tail regions, the algorithm displays remarkable detection and generalization capabilities, which have been validated by experimental results on present tagged nuclear location protein datasets. Overall, the data-driven algorithm plays a crucial role in enhancing the identification of protein nuclear localization properties.

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Gray wolf optimization-based self-organizing fuzzy multi-objective evolution algorithm

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SOFT COMPUTING 2022年第22期26卷 12077-12092页

作者： Xie, Jialiang Zhang, Shanli Wang, Honghui Wu, Dongrui Jimei Univ Sch Sci Xiamen 361021 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist Educ Image Proc & Intelligent Control Key Lab Wuhan Peoples R China

Two goals of multi-objective evolutionary algorithms are effectively improving their convergence and diversity and making the Pareto set evenly distributed and close to the real Pareto front. At present, the challenges to be solved by the multi-objective evolutionary algorithm are to improve the convergence and diversity of the algorithm, and how to better solve functions with complex PF and/or PS shapes. Therefore, this paper proposes a gray wolf optimization-based self-organizing fuzzy multi-objective evolutionary algorithm. Gray wolf optimization algorithm is used to optimize the initial weights of the self-organizing map network. New neighborhood relationships for individuals are built by self-organizing map, which can maintain the invariance of feature distribution and map the structural information of the current population into Pareto sets. Based on this neighborhood relationship, this paper uses the fuzzy differential evolution operator, which constructs a fuzzy inference system to dynamically adjust the weighting parameter in the differential operator, to generate a new initial solution, and the polynomial mutation operator to refine them. Boundary processing is then conducted. Experiments on 15 problems of GLT1-6 and WFG1-9 and the algorithm proposed in this paper achieve the best on 18 values. And the result shows that the convergence and diversity of the proposed algorithm are better than several state-of-the-art multi-objective evolutionary algorithms.

关键词： Gray wolf optimization Fuzzy inference system Self-organizing map Evolutionary algorithm

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Coordinated Guiding Vector Field Design for Ordering-Flexible Multirobot Surface Navigation

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IEEE TRANSACTIONS ON AUTOMATIC control 2024年第7期69卷 4805-4812页

作者： Hu, Bin-Bin Zhang, Hai-Tao Yao, Weijia Sun, Zhiyong Cao, Ming Huazhong Univ Sci & Technol Engn Res Ctr Autonomous Intelligent Unmanned Syst Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Hunan Univ Sch Robot Changsha 410082 Hunan Peoples R China Univ Groningen Inst Engn & Technol NL-9747 AG Groningen Netherlands Eindhoven Univ Technol Dept Elect Engn NL-5612 AZ Eindhoven Netherlands Univ Groningen Inst Engn & Technol NL-9747 AG Groningen Netherlands

In this article, we design a distributed coordinated guiding vector field (CGVF) for a group of robots to achieve ordering-flexible motion coordination while maneuvering on a desired 2-D surface. The CGVF is characterized by three terms, i.e., a convergence term to drive the robots to converge to the desired surface, a propagation term to provide a traversing direction for maneuvering on the desired surface, and a coordinated term to achieve the surface motion coordination with an arbitrary ordering of the robotic group. By setting the surface parameters as additional virtual coordinates, the proposed approach eliminates potential singularity of the CGVF and enables both the global convergence to the desired surface and the maneuvering on the surface from all possible initial conditions. The ordering-flexible surface motion coordination is realized by each robot to share with its neighbors only two virtual coordinates, i.e., that of a given target and that of its own, which reduces the communication and computation cost in multirobot surface navigation. Finally, the effectiveness of the CGVF is substantiated by extensive numerical simulations.

关键词： Robot kinematics Navigation Convergence Surface treatment Robot sensing systems Task analysis Aerospace electronics Agents and autonomous systems cooperative control network analysis and control ordering-flexible surface navigation

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Nested Saturated control of Uncertain Complex Cascade Systems Using Mixed Saturation Levels

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1163-1174页

作者： Meng Li Zhigang Zeng Wuhan National Laboratory for Optoelectronics Wuhan 430074 School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China

This study addresses the problem of global asymptotic stability for uncertain complex cascade systems composed of multiple integrator systems and non-strict feedforward nonlinear systems. To tackle the complexity inherent in such structures, a novel nested saturated control design is proposed that incorporates both constant saturation levels and state-dependent saturation levels. Specifically, a modified differentiable saturation function is proposed to facilitate the saturation reduction analysis of the uncertain complex cascade systems under the presence of mixed saturation levels. In addition, the design of modified differentiable saturation function will help to construct a hierarchical global convergence strategy to improve the robustness of control design scheme. Through calculation of relevant inequalities, time derivative of boundary surface and simple Lyapunov function,saturation reduction analysis and convergence analysis are carried out, and then a set of explicit parameter conditions are provided to ensure global asymptotic stability in the closed-loop systems. Finally, a simplified system of the mechanical model is presented to validate the effectiveness of the proposed method.

关键词： method saturation differentiable

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Optimal sizing, operation strategy and case study of a grid-connected solid oxide fuel cell microgrid

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APPLIED ENERGY 2022年 307卷 118214-118214页

作者： Jiang, Jianhua Zhou, Renjie Xu, Hao Wang, Hao Wu, Ping Wang, Zhuo Li, Jian Huazhong Univ Sci & Technol Educ Minist Image Proc & Intelligent Control Key Lab Sch Artificial Intelligence & Automat Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Mat Sci & Engn Wuhan Hubei Peoples R China

The microgrid (MG) system based on renewable energy generators plays a significant role in sustainable development and environmental protection, which has been developed rapidly. As a promising clean energy conversion technology, solid oxide fuel cell (SOFC) is a clean, efficient and controllable power generator, which is very suitable to be integrated in a distributed MG system. Finding the optimal size configuration and the beneficial operation strategy of the Grid-connected MG under different operation modes are critical issues for MG application. In this work, a single-dwelling MG incorporating solar photovoltaic (PV), wind turbine generator (WTG), SOFC and battery energy storage system (BESS) is studied by minimizing the system levelized cost of energy (LCOE) on the basis of system multi-constraints. The dispatching problem of MG is modeled as a quadratic programming problem and an improved GA-PSO algorithm is employed to explore the optimal configuration. Then, sensitivity analysis is carried out to identify the impact of different distributed energy resource size on the performance of MG. Based on the optimal configuration, the operation strategy of the proposed MG under both off-grid mode and grid-connected mode, as well as the influence of electricity price and fuel price on the operation of the MG are investigated. Finally, the economic and environmental benefits of the MG are studied and compared. The results show that, in Shanghai, Beijing, Wuhan and Hulunbuir, the costs of the MG in both off-grid mode and grid-connected mode are lower than the grid-supplied price by up to 13%-28% and 28%-37% separately.

关键词： Microgrids Solid oxide fuel cell Multiple constraints Optimal sizing method System economic analysis Application comparison

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Tuning curved DNA origami structures through mechanical design and chemical adducts

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NANOTECHNOLOGY 2022年第40期33卷 405603-405603页

作者： Xie, Chun Hu, Yingxin Chen, Zhekun Chen, Kuiting Pan, Linqiang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Educ Minist China Key Lab Image Informat Proc & Intelligent Control Wuhan Peoples R China Shijiazhuang Tiedao Univ Coll Informat Sci & Technol Shijiazhuang Hebei Peoples R China

The bending and twisting of DNA origami structures are important features for controlling the physical properties of DNA nanodevices. It has not been fully explored yet how to finely tune the bending and twisting of curved DNA structures. Traditional tuning of the curved DNA structures was limited to controlling the in-plane-bending angle through varying the numbers of base pairs of deletions and insertions. Here, we developed two tuning strategies of curved DNA origami structures from in silico and in vitro aspects. In silico, the out-of-plane bending and twisting angles of curved structures were introduced, and were tuned through varying the patterns of base pair deletions and insertions. In vitro, a chemical adduct (ethidium bromide) was applied to dynamically tune a curved spiral. The 3D structural conformations, like chirality, of the curved DNA structures were finely tuned through these two strategies. The simulation and TEM results demonstrated that the patterns of base pair insertions and deletions and chemical adducts could effectively tune the bending and twisting of curved DNA origami structures. These strategies expand the programmable accuracy of curved DNA origami structures and have potential in building efficient dynamic functional nanodevices.

关键词： DNA structures curved nanostructures chirality molecular dynamics DNA intercalator

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Online Learning Based Shape control for a Soft Manipulator Based on Spatial Features Feedback

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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年第11期9卷 10081-10088页

作者： Shen, Yi Zhang, Jinghao Yuan, Ye Zhang, Fumin Ding, Han Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipmentand Technol Wuhan 430074 Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Clear Water Bay Hong Kong 430074 Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn StateKey Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

Although soft manipulators are endowed with compliance and flexibility, most control strategies focus on end-effector control and lack shape control ability. This letter aims to design a shape controller for the soft manipulator. Firstly, we establish a modified forward kinematics model (FKM) based on the long-short-term-memory (LSTM) neural network to describe the mapping between actuation inputs and spatial features. The spatial features consist of the backbone curve and contour features. The backbone curve is represented by the piecewise Bezier curve under geometrically continuous constraint. The contour features are extracted from the camera-generated point cloud. Besides, an adaptive online learning based shape controller (OLSC) is designed by online back-propagating shape error. The stability of OLSC is proved based on the Lyapunov theorem. Finally, the random excitation model validation experiment demonstrates the prediction accuracy of the proposed modified FKM, and the shape control experiments in air and water validate the effectiveness of the proposed OLSC.

关键词： Shape Shape control Atmospheric modeling Vectors Adaptation models Feature extraction Deformation Analytical models Visualization Kinematics Soft manipulator shape control learning-based control contour feature

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Learning Second-Order Attentive Context for Efficient Correspondence Pruning

arXiv

引用

arXiv 2023年

作者： Ye, Xinyi Zhao, Weiyue Lu, Hao Cao, Zhiguo Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology China

Correspondence pruning aims to search consistent correspondences (inliers) from a set of putative correspondences. It is challenging because of the disorganized spatial distribution of numerous outliers, especially when putative correspondences are largely dominated by outliers. It is more challenging to ensure effectiveness while maintaining efficiency. In this paper, we propose an effective and efficient method for correspondence pruning. Inspired by the success of attentive context in correspondence problems, we first extend the attentive context to the first-order attentive context and then introduce the idea of attention in attention (ANA) to model second-order attentive context for correspondence pruning. Compared with first-order attention that focuses on feature-consistent context, second-order attention dedicates to attention weights itself and provides an additional source to encode consistent context from the attention map. For efficiency, we derive two approximate formulations for the naive implementation of second-order attention to optimize the cubic complexity to linear complexity, such that second-order attention can be used with negligible computational overheads. We further implement our formulations in a second-order context layer and then incorporate the layer in an ANA block. Extensive experiments demonstrate that our method is effective and efficient in pruning outliers, especially in high-outlier-ratio cases. Compared with the state-of-the-art correspondence pruning approach LMCNet, our method runs 14 times faster while maintaining a competitive accuracy. Copyright © 2023, The Authors. All rights reserved.

关键词： Efficiency

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Structure-free containment control for uncertain underactuated multiple Euler-Lagrange systems

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Science China(Information Sciences) 2023年第11期66卷 150-168页

作者： Housheng SU Yali WU Liren ZHANG Xia CHEN Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology

This article studies the problem of structure-free distributed containment control for uncertain underactuated multiple Euler-Lagrange systems(MELSs) considering disturbances by using a layered approach. First, the second layer is the virtual layer constructed artificially for hierarchical control. We move all virtual nodes to the convex hull formed by leaders in the first layer by implementing containment control algorithms on all virtual nodes. Then, the third layer is the following layer, and we propose an adaptive robust tracking controller to ensure that each follower in the third layer tracks the corresponding virtual node in the second layer. So far, the underactuated MELSs can achieve containment control. Furthermore,through the theoretical derivation, sufficient conditions are obtained to achieve the objective of structure-free containment control. Finally, the effectiveness of the proposed stratified structure-free containment control method is verified by a simulation example.

关键词： Euler-Lagrange systems underactuated system containment control adaptive-robust control

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