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17th International Conference on intelligent robotics and Applications, ICIRA 2024

作者： Li, Meng Yun, Juntong Jiang, Du Tao, Bo Li, Gongfa Liu, Rong Liu, Ying Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China School of Medicine Wuhan University of Science and Technology No. 1 Huangjia Lake University Town Wuhan430065 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

Image segmentation plays a crucial role in target recognition as it provides an essential prerequisite for identifying targets. However, UNet cannot acquire comprehensive information about the image, which limits its ability to effectively segment small and discrete objects. A new network structure, called MorNet, is proposed. It applies dilation and erosion operations in morphological opening and closing for connected and discrete region segmentation. MorNet effectively integrates global segmentation images, emphasizing small and discrete area segmentation and enhancing the segmentation of large continuous areas. This method enhances the understanding of the location of organs and diseased sites, enabling accurate segmentation. A side-out (SO) monitoring mechanism is introduced into the decoder to provide monitoring information for the original image and the predicted results. Compared with current UNet-like networks, our proposed method achieved the highest Dice scores (96.4635%, 94.0514%, 94.3444%) and PPV scores (94.2226%, 90.2361%, 91.5582%) for liver tumor, brain tumor, and liver segmentation tasks, respectively. The experimental results show that MorNet successfully combines the segmentation of connected and discrete regions. MorNet locates organs and lesions more accurately than current state-of-the-art medical image segmentation models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Gesture Recognition of sEMG Based on Res-LSTM 17th

Gesture Recognition of sEMG Based on Res-LSTM

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17th International Conference on intelligent robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Maximum ladle shell temperature prediction based on GABP neural network

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International Journal of Wireless and Mobile Computing 2023年第2期24卷 120-126页

作者： Sun, Ying Huang, Peng Tao, Bo Yun, Juntong Zhao, Guojun Liu, Xin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China

intelligent manufacturing is the main development trend of today's manufacturing industry, and talents are the first resource. Through the analysis of the current situation of cultivating talents in mechanical engineering in colleges and universities, it is found that most students of this major have difficulty in involving in knowledge of other fields outside their specialties, and their knowledge structure is relatively single. In response to the above problems, this paper proposes the training mode of multidisciplinary cross-integration of talents in mechanical engineering, which is analysed through the study of maximum temperature prediction of steel ladle shell. The BP neural network based on the improved genetic algorithm is trained on the experimental data samples to achieve the maximum temperature prediction of ladle shell under different thickness combinations of insulation layer, safety layer and working layer. By learning the knowledge of target prediction, students' overall development is promoted. © 2023 Inderscience Enterprises Ltd.

关键词： Forecasting

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A tactile sensor based on photoelasticity

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International Journal of Wireless and Mobile Computing 2024年第3期27卷 281-289页

作者： Tao, Bo Huang, Zhili Zhu, Wenqiong Li, Gongfa Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China

In the new industrial revolution, the market demands integrated talents in new engineering fields. To meet the requirements of the new era for cultivating high-level talents in integrated disciplines, this paper takes the photoelastic tactile sensor as a carrier, developing a task-driven teaching method oriented to student achievement. Combining society’s need with professional knowledge learning and innovation ability cultivation of students, a practical and innovative platform is built to meet the needs of different stages of integrated graduate education for bachelor’s and master’s degrees. Achieving simultaneous enhancement of learning, scientific research and innovation capabilities, it proposes a multi-dimensional assessment mechanism for integrated graduate education, involving long-term assessment of students at different stages and levels. It implements a strict entry and exit policy and comprehensively improves the quality of talent cultivation. The results show very obvious effects, significantly improving the quality of graduates and promoting student development. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Tactile sensors

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Design of intelligent tracking robot

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International Journal of Wireless and Mobile Computing 2020年第3期19卷 307-314页

作者： Liu, Yibo Sun, Ying Jiang, Du Yun, Juntong Liu, Ying Bai, Dongxu Li, Gongfa Zhou, Dalin Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan Hubei China School of Computing University of Portsmouth Portsmouth Hampshire United Kingdom

With the trend of world trade entering a period of rapid growth, the logistics industry is developing very rapidly. At the same time, it also has higher requirements for logistics handling and work efficiency. Therefore, this article designs a robot with mechanical arm and claw crawler tracking for unmanned logistics warehouse and production workshop. The robot has the functions of detecting signals, identifying signals, autonomously grasping objects, and transporting objects. intelligent tracking robot is an industrial robot that can be automated for handling operations such as flexible grasping and handling of materials. The robot can automatically do tracking, self-grasping objects, and independent transportation of objects. Compared with the traditional crawler transport robot, the robot has the characteristics of fewer sensors, high accuracy, sensitive response and good adaptability. This article details the robot design process and functional module analysis. © 2020 Inderscience Enterprises Ltd.

关键词： Machine design

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Trajectory tracking of 4-DOF assembly robot based on quantification factor and proportionality factor self-tuning fuzzy PID control

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International Journal of Wireless and Mobile Computing 2020年第4期18卷 361-370页

作者： Li, Cuiqiao Sun, Ying Li, Gongfa Jiang, Du Zhao, Haoyi Jiang, Guozhang Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan Hubei China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan Hubei China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Institute of Precision Manufacturing Wuhan University of Science and Technology Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Institute of Precision Manufacturing Wuhan University of Science and Technology Wuhan Hubei China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan Hubei China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan Hubei China

When the manipulator performs the assembling task, the performance of the system is easily affected by external interference and parameter changes, resulting in slow tracking response speed and low tracking accuracy. In order to improve the stability and robustness of the controller, a self-tuning fuzzy PID controller with quantification factor and proportionality factor is designed based on the fuzzy PID control. The parameters of the PID controller are dynamically fine-tuned by the fuzzy controller 1, and the quantification factor and proportionality factor are adjusted online by the modifying fuzzy controller 2 to fine-tune the parameters of PID controller. The control effect and robustness of the improved fuzzy PID controller to the manipulator system are simulated and verified on the MATLAB/Simulink platform. The simulation results show that the proposed method significantly improves the transient response speed, tracking accuracy and follower characteristics of the system, and has good dynamic performance. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Manipulators

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Indoor object segmentation based on YOLACT++

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International Journal of Wireless and Mobile Computing 2023年第2期24卷 127-133页

作者： Sun, Ying Zhao, Zichen Tao, Bo Liu, Xin Yun, Juntong Liu, Ying Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Wuhan University of Science and Technology Hubei Wuhan China

intelligent Manufacturing originates from the research of artificial intelligence, which can not only reduce operating costs, but also improve product quality, and has become the way to cultivate new advantages in forging international competition in manufacturing. With the transformation of traditional manufacturing to intelligent manufacturing, the course of intelligent manufacturing should also be different from the traditional teaching mode, but through the survey, it has been found that the course of intelligent manufacturing still has a single teaching mode, insufficient innovative guidance for students and insufficient combination of theory and practice. In order to solve the issues mentioned above, the Project-Analysis-Evaluation (PAE) structure is proposed in this paper, and it is combined with constructivist theory and analysed through the study of indoor object instance segmentation detection. The YOLACT++ algorithm is pre-trained on SUNRGBD dataset and applied to indoor environment detection in this paper. © 2023 Inderscience Enterprises Ltd.

关键词： Operating costs

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Bimanual gesture recognition based on convolution neural network

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International Journal of Wireless and Mobile Computing 2020年第4期18卷 311-319页

作者： Wu, Hao Li, Gongfa Sun, Ying Jiang, Guozhang Jiang, Du Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan Hubei China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan Hubei China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Institute of Precision Manufacturing Wuhan University of Science and Technology Wuhan Hubei China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan Hubei China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan Hubei China

Gesture recognition is a key research field in the human-computer interaction. At present, most of researchers focus on one-handed gesture recognition, but do not pay much attention to bimanual (two hands) gesture recognition. This paper presents a deep learning-based solution to tackle the self-occlusion and self-similarity. To solve this problem, this paper uses Kinect to collect many colour and depth images of different gestures, and each gesture contains multiple sample individuals. Colour images and depth images are used to train the recognition model of bimanual gesture respectively, and then the colour image and depth image are fused, and the bimanual gesture recognition model is trained based on colour image and depth image fusion. Then, the bimanual recognition effects of the three models are compared. The experimental results show that, regardless of the single gesture precision or the mean average precision, the bimanual gesture recognition effect of the fused model is better than the gesture recognition models based on either colour image or depth image. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Deep learning

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A 7DOF redundant manipulator inverse kinematic solution algorithm based on bald eagle search optimization algorithm

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Soft Computing 2024年第23期28卷 13681-13699页

作者： Zhao, Guojun Sun, Ying Jiang, Du Liu, Xin Tao, Bo Jiang, Guozhang Kong, Jianyi Yun, Juntong Liu, Ying Li, Gongfa Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China

Solving inverse kinematics (IK) is an excellent challenge for redundant manipulators due to their highly non-linear and complex coupling, which is not amenable to analytical solutions by conventional methods. In this paper, the conventional solution was replaced by the optimization process of a fitness function. The fitness function aims to obtain a set of solutions for the desired position of the end effector (EE). The function is based on forward kinematics;hence, this method can avoid singularities and be suitable for solving redundant manipulators. For solving this optimization problem, the bald eagle search (BES) optimization algorithm was chosen due to its easy principle and excellent performance. BES integrates the advantages of evolutionary and swarm techniques. On the one hand, BES maximizes the advantages offered by swarm intelligence (SI) in terms of searching within the best position in the swarm. On the other hand, BES capitalizes on the capability of evolutionary techniques to explore the search space frequently and avoid the local optimum. In this study, two 7-degree of freedom (DOF) manipulators were used to test the performance of BES. Meanwhile, several evolutionary and SI optimization algorithms were selected to compare with BES. The experimental results demonstrate that the BES optimization algorithm can efficiently and accurately solve the IK problem of 7DOF redundant manipulators. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Inverse kinematics

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Multi-objective optimisation design of cross-shaft based on Kriging response surface optimisation model

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International Journal of Wireless and Mobile Computing 2024年第2期26卷 207-214页

作者： Xie, Yuanmin Xiong, Sijie Yun, Juntong Mao, Yanfeng Li, Boao Tang, Xinjie Cao, Yongcheng Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Technology Research and Development Hubei Jingmen Wusan Machinery Equipment Manufacturing Co. Ltd. Hubei Jingmen China

Cross-universal coupling is a key component of the mechanical transmission system and the cross-shaft is the core component of the coupling for torque transmission. Under normal circumstances, cross-shafts are most susceptible to fatigue and deformation, mainly due to the large torques they carry and the irrationality of their structure. Traditional design methods rely on practical experience to determine the key dimensions of the cross-shaft, resulting in long design cycles and low reliability. To address this problem, parametric modelling of the cross-shaft is carried out in this paper and imported into ANSYS Workbench. In addition, static and finite element analyses are carried out to find the weak parts of the cross shaft as the objective function. Finally, sensitivity analysis is carried out using the main structural parameters of the cross-shaft as design variables. Based on the linear correlation matrix and sensitivity graph, the three design variables that have the greatest impact on the objective function, journal height, thickness and body length, are selected. © 2024 Inderscience Enterprises Ltd.

关键词： Sensitivity analysis

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