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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Guoliang Zhang Boyang Li Mingchao Ding College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781509041039

The granularity partition for functional modules is a fundamental research topic in robot distributed control technology. How to evaluate the module partition scheme with different granularity, and then obtain the optimum scheme is the urgent problem. In this paper, we proposed a novel evaluation strategy for the granularity partition of functional modules in robotic system using RTM as control platform based on D-S evidence theory. The fuzzy clustering algorithm is primarily used to get the collection of granularity partition schemes for RT Components encapsulated by the platform of OpenRTM. As the two source of evidence, the indices of cohesion and coupling for the robotic system are achieved to measure the degree of module independence by analyzing the correlation matrix of RT Components. Then the Dempster's combination rule and the priority method for utility intervals are applied to obtain the optimal partition granularity. In the end, the effectiveness and progressiveness of the novel evaluation strategy are verified by applying it to the robotic 3D mapping system.

关键词： Robots Correlation Couplings Partitioning algorithms Clustering algorithms Decentralized control Middleware

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Mechanical arm grasping and target recognition strategy based on the coarse-to-fine algorithm

Mechanical arm grasping and target recognition strategy base...

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Zengyue Ju Tao Xu Hui Zhang Xiuzhi Li College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781509041039

Target recognition is a fundamental research topic in the process of robot grasping. In this paper, we proposed an algorithm framework for object recognition based on local naive Bayes nearest neighbor with Kinect. With the emergence of local invariant feature detection, the method based on local invariant features gradually becomes the mainstream. Object recognition is realized through the feature matching of the model in the current scene and the models in the library based on local invariant property. Considering the number of models in the library may be as many as dozens or even hundreds, I divide the recognition process into coarse and fine recognition, the part of coarse recognition adopts the local naive Bayes nearest neighbor algorithm, just search for a number of the nearest neighbors of the object to be identified, it does not need to compare all models in the model library one by one, the computational complexity of the model increases with the number of models in the logarithmic growth, So we can effectively deal with the situation of large data in library. The process of fine recognition is a process of layers of verification, it mainly includes geometric verification, pose verification, projection verification, the model with the most matching points will be used as the final recognition result. In the end, a variety of performances were tested on the garage willow database and the grasping experiments of the robot arm demonstrate the superiority of my proposed method.

关键词： Feature extraction Object recognition Grasping Three-dimensional displays Robot sensing systems Libraries

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H∞ control of fractional-order singularly perturbed systems: The 1 < ν < 2 case

H∞ control of fractional-order singularly perturbed systems...

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Chinese control and Decision Conference, CCDC

作者： Long-Jun Zhu Jun-Guo Lu Department of Automation Shanghai Jiao Tong University School of Artificial Intelligence Shanghai Normal University Tianhua College Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

This paper addresses the problems of the H ∞ analysis and control of fractional-order singularly perturbed systems with the commensurate order 1 < ν < 2. Based on the bounded real lemma for fractional-order systems and singular fractional-order systems, the sufficient conditions for the H ∞ performance analysis of fractional-order singularly perturbed systems are firstly presented in terms of -independent linear matrix inequalities (LMIs). Then, the state feedback controllers are designed, and the sufficient -independent stabilization conditions are established via bilinear matrix inequalities(BMIs). Moreover, by the provided iterative algorithm, these BMI-based conditions can be solved based on LMIs. Finally, two numerical examples are exploited to verify the effectiveness of the proposed results.

关键词： Robust control State feedback Sufficient conditions Upper bound Perturbation methods Transfer functions Mathematical models

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A new motion control method for omnidirectional intelligent wheelchair based on improved Fuzzy Support Vector machine

A new motion control method for omnidirectional intelligent ...

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IEEE International Conference on Mechatronics and Automation

作者： Wentao Guo Songmin Jia Tao Xu Xiuzhi Li College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781479970995

This paper proposed the FSVM (Fuzzy Support Vector machine) based on affinity to achieve the intelligent wheelchair motion control. The gravity center, which can be computed by calculating the weights of four force sensors under the wheelchair seat, is the key factor to determine the intention of movement of the user. The improved fuzzy membership function of FSVM can reduce the effect of clustering gravity center caused by abnormal clustering gravity center data generated from malfunction. Comparing with the traditional SVM (Support Vector machine), the improved FSVM algorithm has lower error rate. This paper further validates the practical feasibility and validity of the proposed control algorithm. The experiment results show that the proposed algorithm can improve the precision of omnidirectional intelligent wheelchair motion control.

关键词： Wheelchairs Gravity Support vector machines Clustering algorithms Training Force sensors Noise

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Zhang Neurodynamics for Cholesky Decomposition of Matrix Stream Using Pseudo-Inverse with Transpose of Unknown

Zhang Neurodynamics for Cholesky Decomposition of Matrix Str...

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第40届中国控制会议

作者： Xiu Zeng Min Yang Jinjin Guo Yihong Ling Yunong Zhang School of Computer Science and Engineering Sun Yat-sen University School of Information and Communication Engineering Guangzhou Maritime University School of Electronics and Information Technology Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education

Cholesky decomposition is a well-known decomposition for positive definite matrix. On account of its significantly fundamental roles in linear algebra and matrix theory, there are a lot of researches and applications based on it. In recent years,solving time-varying problems has been a research hotspot, but Cholesky decomposition of matrix stream（i.e., continuous timevarying matrix） in a simple, direct and effective equation-solving manner remains a challenging issue. In this paper, the problem of Cholesky decomposition of matrix stream is attempted and solved. First, with the aid of Zhang neurodynamics（ZN）, the objective equation at time-derivative level, including the time derivatives of matrix variable and its transpose, is obtained. In order to handle the objective equation with transpose of unknown, Kronecker product, vectorization technique and vectorized transpose matrix are utilized for better derivation. Thus, a ZN solution model using pseudo-inverse is proposed and numerically experimented. Finally, numerical experiment results substantiate the efficacy of the pseudo-inverse type ZN solution model.

关键词： Cholesky decomposition Matrix stream Transpose of unknown Zhang neurodynamics Vectorized transpose matrix

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Human tracking method based on multi-template color-texture mean-shift algorithm

Human tracking method based on multi-template color-texture ...

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IEEE International Conference on Mechatronics and Automation

作者： Linfeng Wen Songmin Jia Lijia Wang College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781479970995

Human tracking is a hot topic and a challenging task during the past few decades. This paper present a multi templates based strategy for human detecting and tracking with a mobile robot. This method first determines the coarse location by using adaptive template matching algorithm (ATM) based on head-shoulder. Then, a multi-templates based method is presented to locate the person precisely. Multi templates considering the pose changes are obtained to represent the person. For each template, the mean-shift is proceeded. Then, the accurate position is obtained by fusing the results of the Mean-shift from all the templates. After detecting the person, the templates are updated by considering the likelihood of the tracking results and the old templates. Finally, the method is evaluated on a mobile robot in complex environment. The experiment result shows that our method performs well when there are unclear disparity image and pose variations.

关键词： Image color analysis Histograms Target tracking Mathematical model Cameras Mobile robots Robot vision systems

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ANOMALY MULTI-CLASSIFICATION IN INDUSTRIAL SCENARIOS: TRANSFERRING FEW-SHOT LEARNING TO A NEW TASK

arXiv

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arXiv 2024年

作者： Liu, Jie Wu, Yao Luo, Xiaotong Wu, Zongze National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University China School of Informatics Xiamen University China College of Mechatronics and Control Engineering Shenzhen University China

In industrial scenarios, it is crucial not only to identify anomalous items but also to classify the type of anomaly. However, research on anomaly multi-classification remains largely unexplored. This paper proposes a novel and valuable research task called anomaly multi-classification. Given the challenges in applying few-shot learning to this task, due to limited training data and unique characteristics of anomaly images, we introduce a baseline model that combines RelationNet and PatchCore. We propose a data generation method that creates pseudo classes and a corresponding proxy task, aiming to bridge the gap in transferring few-shot learning to industrial scenarios. Furthermore, we utilize contrastive learning to improve the vanilla baseline, achieving much better performance than directly fine-tune a ResNet. Experiments conducted on MvTec AD and MvTec3D AD demonstrate that our approach shows superior performance in this novel task. Copyright © 2024, The Authors. All rights reserved.

关键词： machine learning

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A hybrid monotone decision tree model for interval-valued attributes

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Advances in Computational intelligence 2021年第1期2卷 1-11页

作者： Chen, Jiankai Li, Zhongyan Wang, Xin Zhai, Junhai School of Control and Computer Engineering North China Electric Power University Beijing China Hebei Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University Baoding China School of Mathematics and Physics North China Electric Power University Beijing China

The existing monotonic decision tree algorithms are based on a linearly ordered constraint that certain attributes are monotonously consistent with the decision, which could be called monotonic attributes, whereas others, called non-monotonic attributes. In practice, monotonic and non-monotonic attributes coexist in most classification tasks, and some attribute values are even evaluated as interval numbers. In this paper, we proposed a fuzzy rank-inconsistent rate based on probability degree to judge the monotonicity of interval numbers. Furthermore, we devised a hybrid model composed of monotonic and non-monotonic attributes to construct a mixed monotone decision tree for interval-valued data. Experiments on artificial and real-world data sets show that the proposed hybrid model is effective.

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Energy management of solid oxide fuel cell/lithium battery hybrid system

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CSEE Journal of Power and Energy systems 2022年 1-14页

作者： Li, Dong Zhong, Xiao Bo Xu, Yuan Wu Wei, Chong Yang Zhao, Song Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China

The research of fuel cell and lithium battery hybrid system has attracted more and more researchers because of its advantages of low emission. However, the lower efficiency of energy management has been a critical factor that obstruct the commercialization of hybrid system. In this work, based on finite element ideas, a solid oxide full cell node model is developed to accurately estimate the operating status of the fuel cell. As for lithium battery, previous energy management studies generally only focused on state of charge, however, state of health is also a key parameter for lithium battery. In this paper, considering the strong coupling between variables we use particle filter algorithm to jointly estimate the state of charge and state of health. To reasonably distribute and manage the energy in the hybrid system, a T-S fuzzy controller for the hybrid system is designed by controlling the state variables in the SOFC model and the state of lithium battery. Finally, our algorithm is verified by DSPACE simulation platform. The result shows that the hybrid system with the energy management strategy not only meets the real-time sharply changing demand but also ensures the hybrid system working efficiently and safely. © 2022 China Electric Power Research Institute. All rights reserved.

关键词： Hybrid systems

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Robot-CT Scanning Oriented Synchronous Trajectory Planning of a Dual-Manipulator system

Robot-CT Scanning Oriented Synchronous Trajectory Planning o...

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Chinese control Conference (CCC)

作者： Shuaikang Zhang Mingxing Yuan Xuebo Zhang Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin P. R. China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing P. R. China

At present, most CT scanning systems adopt the traditional horizontal O-frame, suspension or C-arm structures, which can not balance the flexibility and functionality. With the development of robot technology, CT scanning systems based on manipulators have gradually emerged. However, limited by the motion accuracy of the manipulator, most researchers sacrifice the flexibility or increase the mass to improve the accuracy. To overcome this limitation, a new master-slave teaching-based scanning method is proposed to improve the scanning accuracy of the dual-manipulator Robot-CT system with the auxiliary function of rigid links. First, a rigid link is employed to connect the end effectors of the two manipulators. Next, the sampled trajectory of each joint of the slave-manipulator is recorded while the master-manipulator pulls the slave-manipulator to perform a circular motion. Finally, when carrying out the scanning, the dual-manilupator system reproduces the recorded joint trajectory without the rigid element, thereby improving the accuracy of the dual-manipulator CT scanning system to achieve a high-accuracy spatiotemporal synchronization and alignment of pose. To this end, a fifth-order spline interpolation is used to interpolate the sampled trajectory of each joint of the slave-manipulator, which allows it to perfectly reproduce the joint trajectory recorded during the teaching process and ensures the smoothness of the angular velocity and acceleration curves. Simulations are investigated and the corresponding results confirm the effectiveness of the trajectory planning method of the slave-manipulator.

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