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检索条件"机构=Key Laboratory for Robot and Intelligent Technology"

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A distributed drive articulated robot control system based on steering control strategy

A distributed drive articulated robot control system based o...

引用

IEEE International Conference on Mechatronics and Automation

作者： Yunfei Su Hongchang Sun Yongxiang Jiang Longfei Wei Sanpeng Deng Hao Sun Dongcheng Ren Institute of Robot and Intelligent Equipment Tianjin Intelligent Robot Technology and Application Enterprise Key Laboratory School of Mechanical Engineering Tianjin University of Technology and Education China Engineering Research Center of the Ministry of Education of China in Intelligent Rehabilitation Equipment and Detection Technologies School of Artificial Intelligence Hebei University of Technology China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

In order to improve the motion control characteristics of articulated rock-drilling robot, an articulated robot chassis structure with encoder expansion link and distributed electric wheel is designed, and a steering control strategy based on push rod pose feedback is proposed. Based on Adams/Simulink co-simulation, the steering control strategy model is built. The motion of the articulated rock drilling robot in various working conditions is analyzed by co-simulation experiment. Compared with the traditional control strategy, the steering time of the articulated rock-drilling robot by the steering control strategy is increased to 13.87%, and the steering distance is reduced to 16.95%, which effectively improves the steering ability of the robot.

关键词： Drilling robot control Wheels Rocks Mathematical models Mobile robots Motion control

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Design of a Capsule robot System for Gastric Hemorrhage Detection using Luminol 20

Design of a Capsule Robot System for Gastric Hemorrhage Dete...

引用

20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Mao, Yuchen Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Application Complicated Systems Intelligent Robot Laboratory School of Electrical Engineering and Automation Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

Gastric hemorrhage in upper gastrointestinal bleeding is an obvious indicator of deteriorating gastric disease. This paper proposes a capsule robot system for detecting bleeding in the stomach. The patient ingests a capsule robot containing luminol reagent, which detects bleeding in the stomach via chemiluminescence. The MCU receives the optical sensor signal, and the data is transmitted via radio frequency. The external lower computer receives and forwards the data to the upper computer for processing and display. The data is used to determine the presence and amount of stomach bleeding. Chemiluminescence is an excellent sensor, requiring no external energy supply, and demonstrating excellent sensitivity and selectivity. Combining chemical and electronic sensors presents opportunities for further development. Capsule robot detection reduces the discomfort and risk of secondary injury associated with traditional endoscopy. This paper establishes an experimental platform using porcine blood to simulate human blood, demonstrating the feasibility of the system. © 2023 IEEE.

关键词： Chemiluminescence

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A Gesture Recognition Method Based on Improved YOLOv8 Detection

A Gesture Recognition Method Based on Improved YOLOv8 Detect...

引用

Chinese Automation Congress (CAC)

作者： Haiming Li Yanfei Chen Lei Yang Jiaoxing Shi Tao Liu Yihui Zhou Hubei Key Laboratory of Intelligent Robot School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan P. R. China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Aiming at the existing hand gesture estimation algorithms with large computation and poor real-time performance, this paper proposes an improved YOLOv8 algorithm for hand recognition, which combines the improved YOLOv8 detection algorithm for the detection of the hand and combines it with gesture analysis to realize gesture recognition. The improved algorithm not only reduces the amount of floating-point arithmetic, but also increases the accuracy and robustness of detection. In the gesture detection part, the traditional YOLOv8 algorithm is improved by firstly adding the p6 detection head, secondly replacing the CBS module with RFSE module, and thirdly replacing the C2f module with CFE module. The gesture analysis part is performed by training the yolov8 classification model for gesture recognition. The test results of the improved model in TV-Hand and COCO-Hand datasets confirm the effectiveness of the improved YOLOv8 algorithm in this paper, which improves the accuracy by 2.3% and reduces the computational volume by 13.5% compared to the original YOLOv8n, and the correct rates of gesture recognition are all over 90%, and the improved algorithm, which ensures the lightweight and at the same time realizes the further enhancement of accuracy The improved algorithm can realize further improvement of accuracy while ensuring lightweight, and the application prospect is broader.

关键词： Hands Training Analytical models Solid modeling Accuracy Computational modeling Gesture recognition Robustness Real-time systems Classification algorithms

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Study on Control Strategy of the Vascular Interventional Surgical robot Based on LADRC 20

Study on Control Strategy of the Vascular Interventional Sur...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Zhang, Wenqiang Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications Complicated Systems and Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

As a medical device used in surgery, the vascular interventional surgical robot itself needs to have good control accuracy to ensure the safety of the surgery process. Given this security problem, this paper selects the Line Active Disturbance Rejection Control (LADRC) as the control strategy of the vascular interventional robot, aiming at improving the master-slave tracking accuracy of the vascular interventional robot. This article compares the LADRC and PID(Proportional-Integral-Derivative) control strategies through simulation and experiments. The experimental results show that LADRC has good control performance for master-slave tracking and can be applied to the vascular interventional surgical robots. © 2023 IEEE.

关键词： robotic surgery

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Chinese Text Spotter Exploiting Spatial Semantic Information in Scene Text Images

Chinese Text Spotter Exploiting Spatial Semantic Information...

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robotics and Computer Vision (ICRCV), International Conference on

作者： Hao Wang Huabing Zhou College of Computer Science and Engineering Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

Chinese scene text spotting plays a significant role in computer vision applications as it involves extracting and interpreting Chinese information from scene images. However, existing methods often lack specialized designs for complex spatial semantic information in Chinese text images, leading to various degrees of false detections in Chinese scene text images. In this paper, we present SSTS, a novel Spatial Semantic Text Spotter for Chinese text image detection and recognition. SSTS utilizes a concise Transformer encoder and decoder architecture to effectively model spatial semantic information and predict the spatial orientation of Chinese text, reducing the likelihood of false detections caused by different combinations of Chinese characters in various orientations. Experimental results on Chinese scene public datasets demonstrate the superiority of our proposed method. In particular, SSTS achieves a new record of 78.5% in the 1-NED metric on the ReCTS dataset.

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A DDPG-Based Method of Autonomous Catheter Navigation in Virtual Environment 20

A DDPG-Based Method of Autonomous Catheter Navigation in Vir...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Tian, Wei Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

Vascular interventional surgery is the main method for treating cardiovascular diseases. But navigating endovascular catheters through the vascular tree is a highly challenging task even for highly trained specialists. Automation of this task can reduce the burden on surgeons and is expected to improve the surgical outcomes. Although there have been relevant studies utilizing reinforcement learning algorithms to realize autonomous navigation of catheter in the virtual environment Cathsim. However, the kinematics model of the catheter in Cathsim does not conform to the operating mode of the catheter in real vascular interventional surgery. Besides, there are problems such as low success rates of catheter autonomous navigation tasks. To address these issues, this paper modifies the kinematics model of the catheter in Cathsim and designs a catheter autonomous navigation model based on reinforcement learning DDPG (Deep Deterministic Policy Gradient) algorithm. The experimental results show that the agents trained through DDPG in this paper performs better than the agents trained through PPO (Proximal Policy optimization) in other studies in terms of navigation task success rate, completion time, and contact force between the catheter and vascular wall during the navigation process. © 2023 IEEE.

关键词： Reinforcement learning

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Study on Autonomous Surgical Control System of The Vascular Interventional Surgical robot Based on Catheter Tip Location Tracking 20

Study on Autonomous Surgical Control System of The Vascular ...

引用

20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Feng, Zhimin Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

The control system of vascular interventional surgical robot is a complex nonlinear system. When the catheter is inserted into human blood vessels, due to the irregular and curved shape of human blood vessels, the catheter will undergo small deformation, which will affect the displacement of the catheter. In order to reduce the displacement tracking error, a BP neural network PID controller was designed to compensate the displacement error of the autonomous vascular interventional surgical robot. Firstly, the dynamic analysis is carried out according to the axial displacement motion of the vascular interventional surgical robot, and the catheter displacement tracking controller was designed. According to the displacement error, BP neural network PID control is used to output three parameters of PID. Finally, in the experiment and PID control simulation comparison, the results show that the BP neural network PID control has a small displacement tracking error and superior tracking performance, which can meet the requirements. © 2023 IEEE.

关键词： Three term control systems

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Design of Control System for Lower Limb Rehabilitation robot on the Healthy Side sEMG Signal 20

Design of Control System for Lower Limb Rehabilitation Robot...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yu, Shiqin Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

With the number of stroke patients increasing year by year, rehabilitation exoskeleton robot has been paid more and more attention. For the rehabilitation exoskeleton robot, human-computer interaction ability is an important index, which affects the effect of rehabilitation therapy to a great extent. Surface Electromyography (sEMG) signals are the combined effect of sEMG signals and electrical activities on nerve stem on the skin surface, which can reflect neuromuscular activities in advance and can be used to predict movement intention by sEMG signals. Therefore, this article proposes to use sEMG signals to monitor the motion information of the healthy leg in real-time, extract the characteristics of the electromyography signals, use the sEMG of the healthy leg as the control signal, reflect the motion patterns reflected by the sEMG collected from the healthy side, and then use the motion intention recognition method of Long Short Term Memory(LSTM) neural network to identify the motion intention of the prosthetic limb by identifying the motion patterns of the swing phase of the healthy side. The results indicate that the predicted maximum Root Mean Squared Error(RMSE) is 5.3729, which proves the feasibility of using LSTM model for motion intention recognition and contributes to the real-time and accuracy of lower limb exoskeleton rehabilitation. © 2023 IEEE.

关键词： Long short-term memory

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GAN-Based Fusion of Infrared and Visible Images in Dark Light Environments

GAN-Based Fusion of Infrared and Visible Images in Dark Ligh...

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Chinese Automation Congress (CAC)

作者： Jiaoxing Shi Yanfei Chen Haiming Li Lei Yang Yangkai Liu Tong Yue Hubei Key Laboratory of Intelligent Robot School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan P. R. China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In low light conditions, the fused image generated by fusion of infrared and visible images is dark and lacks detailed texture information, resulting in low target detection accuracy, based on which a target detection network for fusion of infrared and visible images in low light conditions is proposed. Firstly, the dark light perception network is designed to enhance the brightness of the dark light image; secondly, the feature extraction module of the image fusion network introduces the gradient residual dense block to strengthen the ability of the image fusion network to extract the depth features and finegrained detail features of the source image; subsequently, the loss function incorporates the intensity loss and the structural similarity loss to enhance the ability of the image fusion network to extract the pixel intensities and the structural texture details of the source image; Finally, the optimal solution of the fusion network for target detection is achieved by joint training of the image fusion network and the target detection network. The experimental results show that the fusion network in the paper improves the mutual information, average gradient, visual fidelity, gradient-based fusion performance, and structural similarity by 0.142, 0.135, 0.043, 0.067, and 0.082 compared to the other network models, and improves the average precision mean and accuracy by 2.6% and 2.5%, respectively, in the YOLOV8 detection network.

关键词： Training Image quality Visualization Accuracy Brightness Object detection Feature extraction Real-time systems Image fusion Mutual information

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Landslide Susceptibility Mapping based on Swarm Optimization Gradient Boosting Decision Tree in Sanshui District(China)

Landslide Susceptibility Mapping based on Swarm Optimization...

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Software Engineering and Artificial Intelligence (SEAI), IEEE International Conference on

作者： Zhuang Liu Gonghao Duan School of Computer Science & Engineering Artificial Intelligence China Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350374346

ISBN: (纸本)9798350374353

This paper takes Sanshui District of Foshan City as the research object and proposes two GBDT(Gradient Boosted Decision Tree) models based on swarm optimization algorithm. Firstly, seven landslide influencing factors were selected as evaluation indexes. Secondly, the cost matrix was introduced at the algorithm level according to the imbalance of positive and negative samples of landslides. Finally, GBDT, ACO-GBDT(Ant Colony Optimization for Gradient Boosted Decision Tree) and GWO-GBDT(Grey Wolf Optimizer for Gradient Boosted De-cision Tree) were used to carry out landslide susceptibility mapping. The results show that:(1) The spatial distribution of landslides is controlled by multilevel factors. (2) The model prediction accuracy is: GWO-GBDT(AUC = 0.92) > ACO-GBDT(AUC = 0.90) > GBDT(AUC = 0.85). Therefore, the swarm optimization algorithm is effective for the optimization of GBDT model and improves the prediction performance of the model.

关键词： Software algorithms Urban areas Predictive models Prediction algorithms Terrain factors Decision trees Indexes

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