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Real Time Surgical Instrument Object Detection Using YOLOv7 1

6th EAI International Conference on Robotics and Networks, EAI ROSENET 2022

作者： Zheng, Laiwang Liu, Zhenzhong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (数字)9783031338267

ISBN: (纸本)9783031338250

With the rapid development of minimally invasive surgery (MIS) in the medical field, surgical robot technology has developed rapidly. Human-machine combined assisted surgical technology has begun to bring good news to the majority of doctors and patients who need surgery. It has gradually become a common medical treatment. Minimally invasive surgery can overcome the shortcomings of traditional surgery. MIS has the advantages of less trauma, less impact on patients, faster recovery, less intraoperative blood loss, and so on. For surgical robots, surgical instruments are important execution components that have been widely concerned and studied in recent years. One of the core technologies of surgical robots is the detection of surgical equipment based on deep learning, which can effectively assist doctors to complete the surgery. Current surgical instrument detection methods need to be improved in real-time performance and accuracy. Therefore, this paper proposes a new real-time detection algorithm, which is based on the deep learning object detection system YOLOv7. The real dataset, which contained information on seven surgical instruments, was selected for training and validation. Experiments show that the method has good precision, recall rate, and mAP, which can be used to improve the ability of robot-assisted doctors to identify instruments during surgery. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object recognition

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Feature Pyramid Network Based on Skip Connect for Vehicle Prediction 2

Feature Pyramid Network Based on Skip Connect for Vehicle Pr...

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2nd International Conference on Robotics, Automation and Intelligent control, ICRAIC 2022

作者： Li, Peixin Liu, Jiaqi Yang, Lu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China

The trajectory prediction of the target vehicle can improve the perception ability of autonomous driving vehicles in the open world environment and is an essential technology for realizing high-level fully automatic driving. The traditional vehicle trajectory prediction model based on image input is sensitive to the image style of the dataset and has weak generalization ability. The prediction model based on intermediate features can overcome the problem of different dataset styles. However, there are relatively few explorations on building models based on intermediate semantic features. Inspired by the feature pyramid in image processing, this paper proposes an FPSP (Feature Pyramid network based on Skip connect for vehicle Prediction) network. By adding the pyramid feature branch, the original network is improved. The initial coarse information is hierarchically introduced into corresponding abstract high-dimensional features. Experiments on the KITTI dataset prove that FPSP achieves considerable improvement with only a slight increase in time consumption. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Teaching Innovation and Practice of Mind Mapping Applied to engineering Drawing course 12

Teaching Innovation and Practice of Mind Mapping Applied to ...

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12th IEEE International Conference on Educational and Information Technology, ICEIT 2023

作者： Xue, Yahong Mu, Haozhi Xue, Lijun Wang, Xiaofei Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9781665475518

engineering drawing is a compulsory technical foundation course for mechanical majors. Its main task is to cultivate students' ability to draw and read engineering drawings. The content of this course is complicated and abstract and not easy to understand, which makes it difficult for students to learn. Mind mapping is a visual thinking tool to systematize and organize abstract and complicated knowledge. Taking the application of mind mapping to various teaching processes of engineering drawing course, such as the construction of framework, the sorting out of fragmented knowledge, the solution of drawing geometry and sectional view, and the group project for important and difficult content as examples, we illustrate the importance of mind map in cultivating students' knowledge generalization ability, independent learning ability, enhancing students' logical thinking, creative thinking, divergent thinking, and stimulating students' interest in learning. © 2023 IEEE.

关键词： Students

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Anomaly Detection of Logistics Packages Based on CNN and Image Recognition Technology 4

Anomaly Detection of Logistics Packages Based on CNN and Ima...

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4th IEEE International Conference on Data Science and Computer Application, ICDSCA 2024

作者： Liang, Kun Zhang, Hang School of Management Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350368239

To address abnormal situations such as packaging damage, liquid leakage, and item displacement during logistics package transportation, this paper introduces Convolutional Neural Network (CNN) and image recognition technology to achieve real-time anomaly detection and alarm, improving the response speed and accuracy of the logistics system. First, by designing multiple layers of convolution and pooling layers, adding Batch Normalization layers and Dropout layers to prevent overfitting, a CNN deep learning model suitable for logistics package anomaly detection is constructed. Key features are extracted through image preprocessing methods such as normalization and data enhancement to ensure that the model has high recognition adaptability to various abnormal situations such as damage and leakage. Secondly, through data enhancement methods such as rotation, scaling, brightness adjustment, and transfer learning using pre-trained models, the model's adaptability in different lighting, angles, and occlusion conditions is improved. Finally, the model is applied to actual monitoring, and real-time alarms are issued for abnormalities such as damage and leakage, which are then fed back to the system closed-loop management. This method is significantly better than traditional methods in terms of detection accuracy and response speed. Under natural light environment, the model detection accuracy is as high as 98.4%, reducing false positives and false negatives. Combining CNN's anomaly detection technology effectively improves the accuracy and efficiency of logistics monitoring and provides technical support for intelligent logistics management. ©2024 IEEE.

关键词： Convolutional neural networks

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Gait Planning and Simulation of 3-RRP Legged Mobile Robot 20

Gait Planning and Simulation of 3-RRP Legged Mobile Robot

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

作者： Wang, Jinyuan Li, Bin Ma, Yue Wang, Xinjie Peng, Pai Peng, Wei Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350320831

In order to meet the requirements of keeping the body posture level with the ground during the movement of the quadruped robots, this paper designs a quadruped robot with three joints and three degrees of freedom in each leg, which is a 3-RRP kinematic chain. The legs and body of the quadruped robot are virtually modeled by SolidWorks. Combining the forward and inverse kinematics analysis, the reasonable and ideal foot trajectory and body motion trajectory are planned in Matlab. The gait stability is based on the ZMP stability criterion and is quantified by the stability margin. According to the structural characteristics of the quadruped robot in this paper, the body posture adjustment strategy is proposed. Finally, the simulation is carried out under the two gait plannings of straight driving and turning using ADAMS. The simulation results show that the quadruped robot has a reasonable walking gait on the flat road surface with little impact on the body. The minimum stability margin of the strategy with body adjustment is improved compared with the strategy without body adjustment. © 2023 IEEE.

关键词： Stability criteria

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Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Structure design and kinematics modeling of a new continuum parallel robot 20

Structure design and kinematics modeling of a new continuum ...

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

作者： Wang, Xinjie Li, Bin Ma, Yue Peng, Wei Peng, Pai Wang, Jinyuan Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350320831

Compared with the traditional rigid robots, the continuum robot has been widely studied because of its advantages of compact design and flexible motion. The design of continuum parallel robots are similar to that of the traditional rigid-link parallel robot, and the precision, stability and strength characteristics of rigid-link parallel robots are combined with the compactness and flexibility characteristics of continuum robots. In recent research advances, it is well appreciated to suggest that the use of parallel continuum robots with passive supports is supported by elastic rods. The passive branch undergoes deformation along its entire length and uses complex formulas to describe its shape and kinematics. According to different methods, this paper proposes the design of a parallel robot dual continuum translation passive branch chain. This continuum joint will assume a constant curvature bend and use this assumption for kinematic modeling. Since the continuum joint is a flexible joint that utilizes the characteristics of new materials, it uses material deformation to replace the motion pair, which successfully realizes that the passive branch joint can replace the universal joint and the ball hinge in the parallel robot, and the joint can be bent more than 90 0 to achieve a larger range of workspace. Each passive branch of the new continuum robot is a continuum structure composed of two mutually coupled flexible hinge joints, and the translational motion of the end effector is inherently realized by using its material properties. The paper includes a new mechanism description and kinematics modeling. © 2023 IEEE.

关键词： Kinematics

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A Model-Data Compound Driven Method For Compensating Robot Tracking Error 20

A Model-Data Compound Driven Method For Compensating Robot T...

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

作者： Peng, Pai Liu, Qi Li, Bin Peng, Wei Wang, Xinjie Wang, Jinyuan Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350320831

Industrial robots are widely used in industrial production because of their high work efficiency and high flexibility, but their low tracking accuracy makes them unable to be applied on a large scale in high-precision manufacturing. Considering the modeling error of robot, the problem of low tracking accuracy should be solved by combining model-based methods and data-based methods. Thus, a model-data compound approach is proposed for compensating robot tracking error. This method comprehensively considers two error compensation methods of model-driven and data-driven, which constructed the input matrix by using the model-based information and the data-based information. The former includes the desired position, velocity, acceleration, torque and friction torque;and the latter includes the actual torque. For the purpose of predicting the correlation between the joint error and the historical joint motion state, the historical information of the joint motion is also added in the input matrix for improving the error prediction accuracy. Then, a convolutional neural network prediction model is constructed for predicting and compensating the tracking error of each actuated joint. The experimental results show that the proposed method has good prediction accuracy and compensation effect. Compared to joint control without using the proposed method, the root mean square of joint tracking errors was reduced by up to more than 69%. © 2023 IEEE.

关键词： Error compensation

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Small-Target Infrastructure Detection with Spatial Tracking and Multi-Level Feature Extraction of Railway Track Scenes

Small-Target Infrastructure Detection with Spatial Tracking ...

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2024 International Conference on Intelligent Communication, Sensing and Electromagnetics, ICSE 2024

作者： Du, Heng Cang, Huaiming Bai, Yiwen Wang, Xinyi Beijing Elephant Technology Co. Ltd Beijing China School of Transportation Science and Engineering Beihang University Beijing102206 China State Key Lab of Intelligent Transportation System Beijing100191 China School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9798350354935

In the field of railway transportation, with the continuous improvement of train running speed and the continuous increase of operating mileage, it becomes particularly important to ensure the safety and integrity of small-Target infrastructure along the railway train. Although many small-Target detection methods have been proposed, the research on small-Target infrastructure detection along rail trains is very rare. To solve this problem, this paper proposes a small-Target infrastructure detection network with spatial tracking and multi-level feature extraction based on Yolov8n. The experimental results show that ST-YOLO has a 3.6% mAP improvement on the OSDaR23 dataset compared to the baseline Yolov8n, and shows significant advantages over other state-of-The-Art methods. © 2024 IEEE.

关键词： Railroads

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The effect of different gravity fields on mass transfer in the rat bone lacunar-canalicular system

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Medicine in Novel Technology and Devices 2023年第1期17卷 141-149页

作者： Hao Wang Jiaming Wang Kangning Li Lilan Gao Aiguo Wang Shuping Wei Linwei Lyu Chunqiu Zhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering EducationSchool of Mechanical EngineeringTianjin University of TechnologyTianjin300384PR China Tianjin Academy of Traditional Chinese Medicine Affiliated Hosptial PR China

The bone lacunar-canalicular system(LCS)is an important microscopic infrastructure for signaling and solute transport in bone tissue,which guarantees normal physiological processes of the tissue,but the mass transfer laws in the LCS under different gravity fields have not yet been *** rats were injected intraperitoneally with different concentrations of sodium fluorescein tracer and subjected to mass transfer experiments in the LCS under normal gravity and *** fluorescence distribution in the osteon was observed using laser scanning confocal *** hypergravity environment was provided by a self-designed high-G loading *** fluorescence intensity of the Haversian canal in the osteon was the *** fluorescence intensity of lacunae farther away from the Haversian canal was lower,and the fitted curve was *** the increasing distance from the Haversian canal,the curve first rapidly decreased,and then the decreasing trend gradually became *** promoted mass transfer in the LCS,and the 10 G hypergravity showed varying degrees of fluorescence intensity in each layer of the osteon relative to normal gravity,with intensity enhancements in the range of 132.7–249.0%.The fluorescence intensity was also significantly increased when the tracer concentration was halved and the gravity field magnitude was increased to *** conclusion,hypergravity promoted the transport of solute molecules,nutrients,and signaling molecules within the *** effect of hypergravity on mass transfer in the LCS was greater than that of tracer *** may help to understand bone diseases from a mass transfer perspective.

关键词： Bone Lacunar-canalicular system Mass transfer Hypergravity

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