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Chinese control Conference (CCC)

作者： Xiuxia Yin Dong Yue Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei CN

This paper investigates the consensus problem for a set of nonlinear multi-agent systems with nonlinear interconnections. First, in order to reduce the communication burden in the multi-agent network, a distributed event-triggered consensus control is designed by taking into account the effect of the nonlinear interconnections. Then, based on the Lyapunov functional method and the Kronecker product technique, sufficient conditions are obtained to guarantee the consensus in the form of linear matrix inequality (LMI). Finally, a simulation example is proposed to illustrate the effectiveness of the developed theory.

关键词： Tin Multi-agent systems control design Lead Bandwidth Ear Nickel

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Connectivity Exploration after Stroke with Structural Equation Modeling

Connectivity Exploration after Stroke with Structural Equati...

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2012 Third International Conference on Theoretical and Mathematical Foundations of Computer Science(ICTMF 2012)

作者： Wei Li Hongtao Tan Xiaojun Wang Zhiqiao Yan Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology

Neuroplasticity has been demonstrated to play an important role in function recovery *** this paper,stroke patients and controls were subjected to functional magnetic resonance imaging(fMRI) study for *** group independent componentanalysis was used to get the time courses of the interested regions in *** investigate the reorganization of cerebral cortex after stroke,Structural Equation Modeling(SEM) was applied to construct a locomotor brain network *** results were analyzed to investigate thebrain activity changes involved in the cerebral motor cortex circuitry aroused by the hand *** contrast to healthy people,we found that the brain activity changes of the stroke patientscould not onlyshow the local changes around injured regions,but also the global transformation of brain related to *** the differences were examined in terms of changes in path coefficients between brain regions.

关键词： fMRI,ICA,SEM,Stroke,Neuroplasticity

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Expanding Hyperspherical Space for Few-Shot Class-Incremental Learning

Expanding Hyperspherical Space for Few-Shot Class-Incrementa...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Yao Deng Xiang Xiang Key Lab of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

In today’s ever-changing world, the ability of machine learning models to continually learn new data without forgetting previous knowledge is of utmost importance. However, in the scenario of few-shot class-incremental learning (FSCIL), where models have limited access to new instances, this task becomes even more challenging. Current methods use prototypes as a replacement for classifiers, where the cosine similarity of instances to these prototypes is used for prediction. However, we have identified that the embedding space created by using the relu activation function is incomplete and crowded for future classes. To address this issue, we propose the Expanding Hyperspherical Space (EHS) method for FSCIL. In EHS, we utilize an odd-symmetric activation function to ensure the completeness and symmetry of embedding space. Additionally, we specify a region for base classes and reserve space for unseen future classes, which increases the distance between class distributions. Pseudo instances are also used to enable the model to anticipate possible upcoming samples. During inference, we provide rectification to the confidence to prevent bias towards base classes. We conducted experiments on benchmark datasets such as CIFAR100 and miniimageNet, which demonstrate that our proposed method achieves state-of-the-art performance.

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An improved optimal guidance law with impact angle constraints based on genetic algorithms

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International Journal of Modelling, Identification and control 2010年第1-2期10卷 94-100页

作者： Zheng, Zongzhun Wang, Yongji Wu, Hao Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

In this paper, an improved formulation of optimal guidance law (OGL) based on genetic algorithms (GAs) is proposed. Linear quadratic optimal control theory is derived to consider terminal velocity maximisation, also GAs are employed to search weight coefficient matrix of the linear quadratic performance index optimum process problem. In the GAs, a combination of the roulette wheel and elitism methods is adopted, and penalty function is added to performance index. Consequently, terminal position accuracy and impact angle constraints are satisfied. Numerical simulation results illustrate that the proposed OGL based on GAs shows better performance compared with conventional method and is rather robust. Copyright © 2010 Inderscience Enterprises Ltd.

关键词： Genetic algorithms

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Manifold Learning Inspired Mating Restriction for Evolutionary Constrained Multiobjective Optimization 11th

Manifold Learning Inspired Mating Restriction for Evolutiona...

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11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021

作者： Li, Lianghao He, Cheng Cheng, Ran Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783030720612

Mating restriction strategies are capable of restricting the distribution of parent solutions for effective offspring generation in evolutionary algorithms (EAs). Studies have shown the importance of these strategies in improving the performance of EAs for multiobjective optimization. Our previous study proposed a specific manifold learning inspired mating restriction (MLMR) strategy. It has shown promising capability of solving multiobjective optimization problems (MOPs) with complicated Pareto set shapes. However, the effect of mating restriction strategies in solving constrained MOPs is yet to be well studied. Here, we investigate the effectiveness of MLMR for solving constrained MOPs. The MLMR strategy is embedded into some representative multiobjective EAs and tested on various benchmark constrained MOPs. Experimental results indicate the encouraging performance of MLMR in constrained multiobjective optimization. © 2021, Springer Nature Switzerland AG.

关键词： Multiobjective optimization

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Cross-Domain Few-Shot Incremental Learning for Point-Cloud Recognition

Cross-Domain Few-Shot Incremental Learning for Point-Cloud R...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Yuwen Tan Xiang Xiang Key Lab of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

Sensing 3D objects is critical when 2D object recognition is not accessible. A robot pre-trained on a large point-cloud dataset will encounter unseen classes of 3D objects after deploying it. Therefore, the robot should be able to learn continuously in real-world scenarios. Few-shot class-incremental learning (FSCIL) requires the model to learn from few-shot new examples continually and not forget past classes. However, there is an implicit but strong assumption in the FSCIL that the distribution of the base and incremental classes is the same. In this paper, we focus on cross-domain FSCIL for point-cloud recognition. We decompose the catastrophic forgetting into base class forgetting and incremental class forgetting and alleviate them separately. We utilize the base model to discriminate base samples and new samples by treating base samples as in-distribution samples, and new objects as out-of-distribution samples. We retain the base model to avoid catastrophic forgetting of base classes and train an extra domain-specific module for all new samples to adapt to new classes. At inference, we first discriminate whether the sample belongs to the base class or the new class. Once classified at the model level, test samples are then passed to the corresponding model for class-level classification. To better mitigate the forgetting of new classes, we adopt the soft label and hard label replay together. Extensive experiments on synthetic-to-real incremental 3D datasets show that our proposed method can balance the performance between the base and new objects and outperforms the previous state-of-the-art methods.

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Uncalibrated Path Planning in the image Space for the Fixed Camera Configuration

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Acta Automatica Sinica 2013年第6期39卷 759-769页

作者： Xin-Wu LIANG Xin-Han HUANG Min WANG Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education of China Shanghai 200240 China Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Ministry of Education of China Wuhan 430074 China

image-based visual servoing can be used to efficiently control the motion of robot manipulators. When the initial and the desired configurations are distant, however, as pointed out by many researchers, such a control approach can suffer from the convergence and stability problems due to its local properties. By specifying adequate image feature trajectories to be followed in the image, we can take advantage of the local convergence and stability of image-based visual servoing to avoid these problems. Hence, path planning in the image space has been an active research topic in robotics in recent years. However, almost all of the related results are established for the case of camera-in-hand configuration. In this paper, we propose an uncalibrated visual path planning algorithm for the case of fixed-camera configuration. This algorithm computes the trajectories of image features directly in the projective space such that they are compatible with rigid body motion. By decomposing the projective representations of the rotation and the translation into their respective canonical forms, we can easily interpolate their paths in the projective space. Then, the trajectories of image features in the image plane can be generated via projective paths. In this way, the knowledge of feature point structures and camera intrinsic parameters are not required. To validate the feasibility and performance of the proposed algorithm, simulation results based on the puma560 robot manipulator are given in this paper.

关键词： Visual servoing path planning uncalibrated camera projective space fixed-camera configuration

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A NOVEL VISUAL SERVOING MICROASSEMBLY SYSTEM

A NOVEL VISUAL SERVOING MICROASSEMBLY SYSTEM

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2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems

作者： Xinhan Huang Shangqin Mao Min Wang The Key Laboratory of Image Processing and Intelligent Control of Ministry of Education of China Department of Control Science and EngineeringHuazhong University of Science and Technology

The focus of this paper is the design and development of an automatic system for microassembly. The automatic processing is made possible by (i) the development of a machine vision algorithm to identify the targets and end-effectors, (ii) an uncalibrated visual servoing algorithm to lead the end-effector to grasp the micro-pieces and then assemble the target. The experimental results demonstrate that this prototype microassembly system is effective and practicable for automatic microassembly applications.

关键词： microassembly target recognition visual servoing

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Robust Platoon control of Industrial Heavy-Load Autonomous Vehicles 12

Robust Platoon Control of Industrial Heavy-Load Autonomous V...

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12th International Conference on CYBER Technology in Automation, control, and intelligent Systems, CYBER 2022

作者： Liu, Zhe Li, Xiang Wang, Hesheng MoE Key Lab of Artificial Intelligence Ai Institute Shanghai Jiao Tong University China School of Mechanical Engineering and Electronic Information China University of Geosciences 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 Shanghai200240 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Platoon control of autonomous industrial vehicles contributes to improving the safety and reliability of cargo transportation in complex industrial scenarios, increasing traffic efficiency and saving energy. The platoon control of autonomous heavy-load industrial vehicles is much harder, as the high robustness requirements, low hardware ability and complex un-structural environments. This paper considers the platoon control task from the view-point of practical industrial applications. Firstly, the longitudinal dynamic model of the heavy-load industrial vehicle is transferred into a first-order damping acceleration response model by introducing the low-level feedback linearization control and compensations. Secondly, the synchronization control concept is introduced and a fully distributed control law is presented, which only requires the coupling information of the two nearest neighbors. In particular, in order to ensure the practical applicability, the information processing delays, data samplings and external control disturbances are explicitly modelled and the global stability analysis approach is presented. Finally, we provide real experiments using full-scale industrial heavy-load vehicles to demonstrate our effectiveness and robustness. © 2022 IEEE.

关键词： Accident prevention

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A research on human cognitive modeling in rumor spreading based on HTM

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 461卷 268-277页

作者： Li, Xiangchen Chen, X. Wang, Wei School of Automation Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan China

ISBN: (纸本)9783662452820

As a sociological phenomenon, rumor spreading has been widely researched by sociologists and other fields’ scholars. How do people generate those strange thinking about the rumor? This paper, from artificial intelligence view, focuses on an algorithm based on Hierarchical Temporal Memory (HTM) to simulate human cognitive process of generating rumors from individual heterogeneous living experience. Comparison with classical Bayesian Networks, our algorithm could effectively and really simulate human cognitive process of rumors, and in accordance with some typical psychology effects proved by sociologists and psychologists. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Bayesian networks

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