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2022 Workshop on Electronics Communication Engineering

作者： Hou, Aihu Liu, Jie Zhou, Kaibo Zhou, Wenli School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Digital River Basin Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China School of Optical and Electronic information Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510666634

The most commonly used implementation of handwritten digit recognition based on convolutional neural networks requires equipment with high computing power, which is not suitable for edge devices. Recently, spiking neural network (SNN) has received more attentions due to its low power consumption and real-time performance, but training SNN is very difficult. As a special SNN, liquid state machine (LSM) has the advantages of simple structure and easy training, so it is very suitable for handwritten digit recognition on edge devices. But it has no advantage in recognition accuracy. In order to improve the performance of LSM, its reservoir needs to be optimized. In this paper, an efficient local optimization strategy is proposed, improving the recognition accuracy of LSM by 11.8% with less the training time. In order to reduce the runtime, auto-encoder and feature screening are used to compress the input handwritten digit image. After feature compression, the input storage is reduced by 57%, and the runtime is reduced by 30%. This work provides an effective way to realize handwritten digit recognition on the edge devices. © 2023 SPIE.

关键词： Computing power

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Adaptive visual servoing using common image features with unknown geometric parameters

Adaptive visual servoing using common image features with un...

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作者： Liu, Yun-Hui Wang, Hesheng Chen, Weidong Zhou, Dongxiang Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Hong Kong Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China State Key Laboratory of Robotics Technology and System Harbin Institute of Technology Harbin 150001 China Joint Center for Intelligent Sensing and Systems National University of Defense Technology China

This paper generalizes the concept of the depth-independent interaction matrix, developed for point and line features in our early work, to generalized image features. We derive the conditions under which the depth-independent interaction matrix can be linearly parameterized by the geometric parameters of the generalized image features, and propose an adaptive visual servo controller for robot manipulators using the generalized image features whose geometric parameters are unknown. To estimate the unknown parameters on-line, we propose new error functions that are linear to estimation errors of the parameters and an algorithm that minimizes the error functions using multiple images. The Lyapunov theory is used to prove asymptotic stability of the proposed controller based on the nonlinear dynamics of the manipulator. It is also shown that in addition to points and lines, other common image features like distances, angles, areas, and centroids all satisfy the conditions for the linear parameterization. Experiments have been conducted to validate the proposed control method. © 2013 Elsevier Ltd. All rights reserved.

关键词： controllers

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T-S Fuzzy Logic control with Genetic Algorithm Optimization for Pneumatic Muscle Actuator

T-S Fuzzy Logic Control with Genetic Algorithm Optimization ...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Cheng Chen Jian Huang Dongrui Wu Zhikang Song Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Beijing Advanced Innovation Center of Intelligent Robots and Systems Beijing China School of Automation Huazhong University of Science and Technology Wuhan China

Based on the three elements model of pneumatic muscle actuators(PMA), this paper proposed a T-S fuzzy logic control with genetic algorithm optimization and achieved the trajectory tracking control of PMA. To guarantee the stability of control system, the Lyapunov direct method was used. And the LMI Toolbox of Matlab was used in this paper to solve linear matrix inequalities(LMls) and calculate the state feedback gains. Finally, the results of experiment demonstrated that, T-S fuzzy logic control with genetic algorithm optimization can achieve desired control performance, which overcome the chattering of trajectory tracking, reduced tracking error effectively and improved the accuracy of control.

关键词： Genetic algorithms Fuzzy logic Mathematical model Optimization Muscles Actuators Stability analysis

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Active Compliance Variable Impedance control of Lower Supernumerary Robotic Limb*

Active Compliance Variable Impedance Control of Lower Supern...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Jun Huo Xinyi Wang Bo Yang Qingyang Yan Zhaofan Yuan Jian Huang Hubei Key Laboratory of Brain-inspired Intelligent Systems and the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China China Telecom Research Institute Guangdong China China Ship Development and Design Centre Wuhan China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

In human-robot systems, ensuring user safety amidst external disturbances remains paramount. An efficient variable impedance control (VIC) technique is designed to enhance human-robot interaction, particularly in scenarios with external force disturbances. By dynamically adapting impedance parameters in response to detected changes in contact force, VIC achieves heightened system flexibility. The robust stability of the VIC system is rigorously established using the Lyapunov approach, with a parameter update law tailored for a lower limb supernumerary robotic limb robot. Through simulations and experiments, the efficacy of the system in maintaining a specific safety margin is demonstrated. Moreover, the technique offers a pragmatic solution to accommodate individual variations in walking gait and cross-user disparities in interaction. The proposed method contributes to advancing the safety and adaptability of cross-user human-robot systems.

关键词： Legged locomotion Adaptation models Mechatronics Robust stability Force Human-robot interaction Safety Impedance Robots Pragmatics

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Improving strategies on PSO for suborbit launch vehicle trajectory optimization

Improving strategies on PSO for suborbit launch vehicle traj...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Fuqiang Xie Ye Yang Songtao Chang Yongji Wang School of Electric Engineering University of South China Hengyang China Beijing AeroSpace Automatic Control Institute Beijing China 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 China

Solving the optimal control problem with a free final time, such as suborbital launch vehicle (SLV) trajectory optimization with two control variables and multi-constraints ones based on particle swarm optimization (PSO), the smoothness of control variable can not be satisfied by linear interpolation method. A novel method including some improving strategies based on PSO for trajectory optimization is proposed, named LCPSO which is a kind of Cooperate PSO based on Legendre orthogonal polynomials. An additional control variable is introduced and transcribes the original optimal problem to a problem with fixed final time, and one dimension searching method based on interval analysis is used to optimize the additional control variable. Furthermore, a theorem on how to find the boundaries of the coefficient of polynomials is proved. Compared with basic PSO, LCPSO has traits of lower dimensions and smoother control variable. An example of trajectory optimization shows the effectiveness of the LCPSO algorithm.

关键词： Polynomials Optimization Switches Trajectory Optimal control Vehicles Approximation methods

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Closer to Pre-trained Network Transfer Better

Closer to Pre-trained Network Transfer Better

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IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Siyu Chen Wei Li School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan People’s Republic of China Image Processing and Intelligent Control Key Laboratory Education Ministry of China Wuhan People’s Republic of China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

In recent years, Deep Neural Network (DNN) has been widely used in the domain of computer vision, but its further development is restricted because of the lack of train samples. Fine-tuning is one of deep transfer learning methods to solve this problem. Nowadays, some existing Fine-tuning approaches assume that if the fine-tuned network could be as close to the pre-trained network as possible, the source knowledge would be fully utilized to improve the study effect. Although these approaches work pretty well, the assumptions on which they are based have not been systematically proved. Due to the complexity of DNNs, offering a reasonable and accurate explanation of the performance of the network is significant for designing new algorithms. In this paper, we design a series of experiments with or without transfer learning respectively, to characterize the relationship between network differences and network performance. The results show that there is an obvious negative correlation between them under certain circumstances. This conclusion can not only provide a more reasonable explanation for the relevant transfer learning algorithm, but also provide support and inspiration for the future work.

关键词： Knowledge engineering Correlation Transfer learning Neural networks Task analysis Information technology Knowledge transfer

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Two-stage Train Components Defect Detection Based on Prior Knowledge

Two-stage Train Components Defect Detection Based on Prior K...

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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Gang Peng Zhiyong Li Shaowei Wan Zhang Deng Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Wuhan Lisai Technology Co. Ltd. Wuhan China

The existing method of detecting defects in train components, which relies on visual identification, requires extensive involvement from inspectors and presents certain limitations. In this study, a two-stage defect detection based on prior knowledge was developed, which first detects the types and positions of components, and then conducts targeted detection of possible existing defect types. The algorithm introduces the prior knowledge of the relative spatial position relationship of components and optimizes the detection of sub-components by cascaded convolutional neural networks and local scale-up. In this study, three methods were used, including deep learning, template matching, and quantitative evaluation based on prior knowledge, to perform targeted detection of defect types that may occur in components. Experiments have verified the adaptability and accuracy of the method, demonstrating its high value for engineering applications.

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Prescribed Performance control of Mobile Wheeled Inverted Pendulum Systems Under Arbitrary Initial Conditions

Prescribed Performance Control of Mobile Wheeled Inverted Pe...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Mengshi Zhang Yu Cao Bo Yang Jian Huang Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute ShenZhen China

Mobile wheeled inverted pendulum (MWIP) is a typical naturally unstable underactuated system and it is very necessary to constrain its transient response to improve the overall safety. Prescribed performance control (PPC) is an effective method, however the system initial conditions are usually required to be known and constraint, otherwise it can lead to singularity problems. In practical systems, it is often difficult to obtain the exact initial state leading to limitations in the application of PPC. To overcome this issue, this paper presented a composite error transformation function to address the problem of initial condition dependence. A continuous bounded function was designed to compress the arbitrary initial error into the predefined bound to avoid singularities. After a set time, it was degraded to an original system error. Based on this composite transformation, a state feedback controller was proposed for the underactuated MWIP system to achieve the constraint outputs. Then, by employing the Lyapunov theorem, it was guaranteed that the closed-loop system would remain stable. Various numerical simulations under different initial conditions were carried out to prove the validity of the proposed controller.

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Designing of laser marking software based on VC++6.0

Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/...

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Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) 2007年第1期31卷 154-156页

作者： Deng, Zhixiang Wang, Yongji Department of Control Science and Technology Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

Designing of universal software in laser-marking industry is introduced here. This software boasts versatile functions, from basic graphic drawing to input interface for files created in AutoCAD and CorelDRAW, Graphics and images showed in the user interface, which can be transformed by such methods as aligning, filling, node adjusting, are interpolated to discrete point data and then downloaded to control laser marking machine via PCI board card to accomplish total marking process. Object oriented programming methods are used, which make this software expansive and maintainable with a friendly interface easy to operate for clients.

关键词： Glyph filling Glyph import Laser marking VC++

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image Denoising Algorithm Based on Neighbouring Thresholding Classification in Wavelet Domain

Image Denoising Algorithm Based on Neighbouring Thresholding...

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International Conference on Signal processing Proceedings (ICSP)

作者： Jianhua Hou Chengyi Xiong Laboratory for State Key Image Processing & Intelligence Control Huazhong University of Science and Technology Wuhan China College of Electronic Information Engineering South Central University of Nationalities Wuhan China

This paper proposes a new image denoising method which exploits spatial correlation among image wavelet coefficients and classification technique. By extending the neighbouring threshold of wavelet coefficients for 1D signal to 2D image case, each coefficient in a subband is classified as "large" or "small" category, according to its corresponding neighbouring threshold. Different strategies are implemented to the classified coefficients. Simulation results show that although very simple, the performance of the proposed method can be competitive to the two excellent state of the art denoising algorithms with spatial adaptivity

关键词： image denoising Wavelet domain Wavelet coefficients Noise reduction Additive white noise image processing Wavelet transforms Clustering algorithms Random variables Maximum likelihood estimation

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