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IEEE International Conference on Unmanned Systems (ICUS)

作者： Xiaowei Wang Zixian Qiu Yang Li Hongmao Qin Ming Gao State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Wuxi Intelligent Control Research Institute of Hunan University Changsha China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Changsha China

To meet the requirements of low latency and high reliability of vehicular computing, vehicular services need to be offloaded to multi-access edge computing (MEC) servers. However, due to the mobility of connected vehicles and the limited coverage of roadside units (RSUs), vehicular services need to be adaptively switched. In order to ensure the quality of service (QoS) in the process of vehicular service switching, a service switching approach based on deep reinforcement learning is proposed in this paper. Firstly, the optimization problem model is established by considering the QoS, service migration cost, and latency. Secondly, the problem is decomposed into several subproblems and transformed into Markov decision processes (MDPs). Finally, a deep reinforcement learning-based algorithm is employed to find the optimal service migration strategy. Simulation results indicate that the proposed approach can effectively ensure the QoS compared to the baseline approaches.

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A Binary Function Name Prediction Method Based on Variable Alignment and Translation Model 23

A Binary Function Name Prediction Method Based on Variable A...

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Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application

作者： Bing Xia Jiabin Yin Yunxiang Ge Ruinan Yang Key Laboratory of Mathematical Engineering and Advanced Computing ZhongYuan University of Technology China Henan Key Laboratory on Public Opinion Intelligent Analysis ZhongYuan University of Technology China ZhongYuan University of Technology China

ISBN: (纸本)9798400709449

Binary function naming is a code analysis task that generates functional descriptions of functions, and its results can be applied in the fields of malicious code analysis, vulnerability causation analysis, and algorithm governance. Aiming at the shortcomings of the pseudocode abstract syntax tree being difficult to extract and the binary function naming scheme having low accuracy rate, a binary function naming prediction model A2N based on variable alignment and sequence translation model is proposed. First, A2N extracts the function variable features of binary files from debugging information and performs variable alignment with the pseudocode obtained from decompiling; then, it obtains the hierarchical structure of the binary functions and designs the node extraction rules to generate an abstract syntax tree AST for each function; then, extract the paths between the leaf nodes of the AST and serialize the tree structure to represent it; finally, with the help of the neural network translation model, establish a mapping between the AST and the binary function names to realize the prediction function. The experimental results show that compared with Dire, Nero and XFL models, the F1 value of A2N is improved by 84%, 44% and 14% on file-level isolation experiments respectively, and the F1 value reaches 80.94% on function-level isolation experiments.

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design and Analysis of 8R-Folding Metamorphic Mechanism and Metamorphic Robot 16th

Design and Analysis of 8R-Folding Metamorphic Mechanism an...

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16th International Federation of Theory of Machines and Mechanisms World Congress, IFToMM WC 2023

作者： Li, Mi Shi, Wujie Chen, Junpeng Zhuang, Zheming Dai, Jian S. Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and Technology Shenzhen518055 China Centre for Advanced Mechanisms and Robotics Key Laboratory of Mechanism Theory and Equipment Design of the Ministry of Education Tianjin University Tianjin300350 China Centre for Robotics Research King’s College London LondonWC2R 2LS United Kingdom

ISBN: (纸本)9783031457081

After completing the design of the rigid torso structure robot, the mobility and topology of the torso are fixed. As a result, it becomes challenging to meet the requirements of robots in multiple working conditions. By applying the torso structure of the reconfigurable metamorphic mechanism, we can address the above-mentioned problems in robot designing. In this paper, based on the reconfigurable mechanism design method of motion bifurcation, the 2-URU mechanism and its derived 8R-Folding mechanism are designed. The 8R-Folding mechanism is innovatively applied to the torso design of the wheel-legged robot, and kinematic analysis, model simulation, and prototype experiments are conducted. The results show that the robot can realize two deployments/folds, and the ratio can reach 3. The waist can achieve left and right rotation and up and down pitching effects after the folding process, allowing it to adapt to a variety of working environments. The article provides a new solution for the robot to achieve one machine with multiple functions. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Robots

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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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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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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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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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WiViPose: A Video-aided Wi-Fi Framework for Environment-Independent 3D Human Pose Estimation

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IEEE Transactions on Multimedia 2025年

作者： Zhang, Lei Ning, Haoran Tang, Jiaxin Chen, Zhenxiang Zhong, Yaping Han, Yahong Tianjin University College of Intelligence and Computing the Tianjin Key Laboratory of Advanced Network Technology and Application Tianjin300050 China Key Laboratory of Computing Power Network and Information Security Ministry of Education China University of Jinan Shandong Provincial Key Laboratory of Ubiquitous Intelligent Computing the School of Information Science and Engineering Jinan250022 China Wuhan Sports University Sports Big-data Research Center Wuhan430079 China Tianjin University College of Intelligence and Computing the Tianjin Key Laboratory of Machine Learning Tianjin300350 China

The inherent complexity of Wi-Fi signals makes video-aided Wi-Fi 3D pose estimation difficult. The challenges include the limited generalizability of the task across diverse environments, its significant signal heterogeneity, and its inadequate ability to analyze local and geometric information. To overcome these challenges, we introduce WiViPose, a video-aided Wi-Fi framework for 3D pose estimation, which attains enhanced cross-environment generalization through cross-layer optimization. Bilinear temporal-spectral fusion (BTSF) is initially used to fuse the time-domain and frequency-domain features derived from Wi-Fi. Video features are derived from a multiresolution convolutional pose machine and enhanced by local self-attention. Cross-modality data fusion is facilitated through an attention-based transformer, with the process further refined under a supervisory mechanism. WiViPose demonstrates effectiveness by achieving an average percentage of correct keypoints (PCK)@50 of 91.01% across three typical indoor environments. © 2025 IEEE.

关键词： Frequency domain analysis

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Application and Practice of Smart Education Technology in Blended Teaching of Engineering Drawing Course 24

Application and Practice of Smart Education Technology in Bl...

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9th International Conference on Distance Education and Learning, ICDEL 2024

作者： Xu, Jinyou Tian, He Wang, Xiaofei Xue, Yahong Li, Ling Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin University of Technology China School of Environmental Science and Safety Engineering Tianjin University of Technology Tianjin China

ISBN: (纸本)9798400716805

The expeditious progress of information technology has encouraged the digital enhancement of the educational sector. To remedy the issues of the traditional teaching mode, a blended teaching mode of engineering drawing course has been developed with the use of smart education technology. Based on the Outcomes-based Education ( OBE ), the teaching objectives and teaching contents of the course are reconstructed by using the method of reverse design and forward implementation. By leveraging the synergy of online and offline, virtual and real, and quantitative and qualitative evaluation, a blended teaching approach that is both student-centered and teacher-guided is realized. A course knowledge graph has been built, offering fresh concepts for accomplishing personalized learning for students. The teaching practice shows that the blended teaching mode based on intelligent education has created a multi-dimensional autonomous learning space and personalized learning path for students, which effectively improves the enthusiasm and initiative of students to participate in teaching activities, and also improves the information level of teaching process and management, and promotes the organic integration of teaching and learning. © 2024 ACM.

关键词： Contrastive Learning

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DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation

arXiv

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arXiv 2024年

作者： Yan, Junkai Gao, Yipeng Yang, Qize Wei, Xihan Xie, Xuansong Wu, Ancong Zheng, Wei-Shi School of Computer Science and Engineering Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Institute for Intelligent Computing Alibaba Group China

Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed. However, a challenge arises when the specific appearances need customizing at designated viewpoints but referring solely to the overall description for generating 3D objects. For instance, ambiguity easily occurs when producing a T-shirt with distinct patterns on its front and back using a single overall text guidance. In this work, we propose DreamView, a text-to-image approach enabling multi-view customization while maintaining overall consistency by adaptively injecting the view-specific and overall text guidance through a collaborative text guidance injection module, which can also be lifted to 3D generation via score distillation sampling. DreamView is trained with large-scale rendered multi-view images and their corresponding view-specific texts to learn to balance the separate content manipulation in each view and the global consistency of the overall object, resulting in a dual achievement of customization and consistency. Consequently, DreamView empowers artists to design 3D objects creatively, fostering the creation of more innovative and diverse 3D assets. Code and model will be released at here. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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