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A Control Method of Robotic Arm Based on Improved Deep Deterministic Policy Gradient 20

A Control Method of Robotic Arm Based on Improved Deep Deter...

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

作者： Shao, Yanpeng Zhou, Haibo Zhao, Shuaishuai Fan, Xiaoyan Jiang, Jiayi Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China

ISBN: (纸本)9798350320831

With the continuous development of Machine Learning, Reinforcement Learning has achieved excellent results in many fields. An improved Deep Deterministic Policy Gradient (DDPG) algorithm is proposed in this paper to optimize Reinforcement Learning control performance, because of the issue of sparse rewards during training in continuous action spaces such as robotic arms, leading to slow convergence and low success rates. The algorithm merges the DDPG algorithm with the Hindsight Experience Relay (HER) algorithm, enabling the agent to learn from the failed experience when learning. Moreover, a double experience replay buffer is introduced, comprising a primary buffer and a secondary buffer containing high-reward experiences, which enhances the sampling probability of high-quality samples. At long last, a PyBullet simulation environment was utilized to execute a simulation experiment. The robotic arm using the improved DDPG algorithm achieved a success rate of nearly 100% in about 220 epochs of training, and the algorithm convergence speed was greatly improved. The trained robotic arm can reach any target point in the workspace. The efficacy of the improved DDPG algorithm is demonstrated by the outcomes, providing a valuable reference for further exploration into the intelligent control of robotic arms for object grasping. © 2023 IEEE.

关键词： Robotic arms

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Road Damage Detection and Classification Based on Multi-Scale Contextual Features

Road Damage Detection and Classification Based on Multi-Scal...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Yang, Lu He, Hualin Liu, Tao 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 Tianjin300384 China

ISBN: (纸本)9781665480451

Road damage detection is particularly essential for improving road traffic safety. Existing methods do not perform well due to complex road conditions and sparse features contained in road damage. Therefore, we propose a new road damage detection network - YPLNet, which could obtain more refined multi-scale contextual features. Specifically, the network proposed in this paper is based on YOLOv5, by adding the PSA module to the backbone network, the spatial information of the feature map at multi-scale is obtained to enrich the feature space, and the long-term information dependence between channels is further constructed. In addition, in the feature fusion stage, the LCFI module is utilized to obtain contextual features under the multi-scale receptive fields, and these contextual features include rich low-level and high-level information. Our proposed network achieves a Mean-F1 Score of 0.635 in the competition. The source code and model are publicly available at https://***/hehualin-tut/YPLNet © 2022 IEEE.

关键词： Damage detection

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Methodology for optimization of preload in a bolted-flange connection based on Markov theory 9

Methodology for optimization of preload in a bolted-flange c...

引用

9th International Conference on advanced Manufacturing Technology and Materials Science, AMTMS 2021

作者： Wang, Yuezhen Liu, Zhifeng Li, Ying Yang, Congbin Institute of Advanced Manufacturing and Intelligent Technology Beijing University of Technology Beijing Beijing100124 China Key Laboratory of CNC Equipment Reliability Ministry of Education Jilin University Jilin Changchun130012 China Mechanical Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Beijing University of Technology Beijing Beijing100124 China

The bolted-flange connection is one of the most popular detachable mechanical joints in mechanical flange connection. It is well known that bolted-flange joints need to be tightened to meet the assembly performance in practical engineering applications. However, the dispersion of the pre-tightening force caused by the elastic interaction between the bolts has a serious impact on the sealing and safety of the product, and therefore the optimization of bolt preload has always been a hot spot in the assembly research field. Combining mathematical theory and experimental data, this paper proposes an optimization model for uniformly distributed preload based on the Markov theory. The torque method was utilized to fasten the bolt-flange joint. The bolt pre-tightening force in the final state was collected and used as sample data. A state transition model was constructed to determine the state transition matrix. Ultimately, an iterative model of the preload was deduced, and the rationality of the model was verified through experimentation. The proposed optimization method of bolt preload can be applied to determine the initial preload of each bolt. This method improves the assembly efficiency and accuracy, which provides a theoretical approach to effectively guide the tightening work of bolted-flange connections. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Bolts

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Research on Control Strategy of Manipulator Based on Deep Reinforcement Learning 23

Research on Control Strategy of Manipulator Based on Deep Re...

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3rd International Conference on Artificial Intelligence, Automation and Algorithms, AI2A 2023

作者： Xu, Nuo Shao, Yanpeng Fan, Xiaoyan National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798400707605

Abstract: Today, the traditional control algorithm of the manipulator is difficult to meet in the complex and changing working environment, and the development of artificial intelligence has achieved remarkable results in the field of manipulator control. As a branch of artificial intelligence, deep reinforcement learning combines the perception ability of deep learning with the decision-making ability of reinforcement learning, which can greatly improve the work efficiency and adaptability of the manipulator. This paper expounds on the principle of deep reinforcement learning, compares and analyzes the application examples of the single manipulator and multi-manipulator control algorithms based on deep reinforcement learning, and demonstrates the achievements of deep reinforcement learning in the motion control of manipulators. The intelligent control research provides a reference. © 2023 ACM.

关键词： Reinforcement learning

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Direct Visual Odometry by Fusing Luminosity and Depth Information

Direct Visual Odometry by Fusing Luminosity and Depth Inform...

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2021 International Conference on Robotics Automation and intelligent Control, ICRAIC 2021

作者： Yin, Jinming Zhou, Haibo Zhang, Haoxin Li, Chenming Sun, Guoqing Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China

In the traditional direct visual odometry, it is difficult to satisfy the photometric invariant assumption due to the influence of illumination changes in the real environment, which will lead to errors and drift. This paper proposes an improved direct visual odometry system, which combines luminosity and depth information. The algorithm proposed in this paper uses Kinect 2 to collect RGB images with the corresponding depth information, and selects points with large changes of gray gradient to construct a luminosity error function and uses the corresponding depth information to construct a depth error function. The two error functions are merged into one function and converted into the least squares function of the pose of camera, the Levenberg-Marquardt algorithm is used to solve the camera pose. Finally, the Graph optimization theory and the g2o library are used to optimize the initial pose. Experiments show that the algorithm can reduce the error to a certain extent and reduce the drift caused by illumination changes. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Vision

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Dimensional synthesis and static/dynamic analysis of a robot in automobile hubs polishing 20

Dimensional synthesis and static/dynamic analysis of a robot...

引用

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

作者： Chen, Long Xi, Manru Ma, Yue Li, Bin Liu, Qi Li, Changrui 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 Tianjin300384 China

ISBN: (纸本)9798350320831

Focusing on the polishing operation of automobile hubs, this paper proposed a polishing robot by combining a 1T2R parallel mechanism (PM) and an X-Y worktable. The dimensional synthesis and static/dynamic performance analysis of the 1T2R PM are also presented with the key points as follows. Firstly, the inverse displacement model and velocity model of the PM are built to formulate the motion/force transmissibility indices on the basis of the generalized Jacobian matrix. Secondly, the dimensional synthesis problem is formulated to determine the optimized normalized dimensional parameters by maximizing the global force/motion transmissibility of the PM subject to geometric constraints without mechanical interference. Finally, the finite element (FE) model of the 1T2R PM is built with the aid of the SAMCEF, and the static stiffness and lower-order natural frequencies of the PM are evaluated. The research results of this paper provide dimensions and mechanical structures for developing the physical prototype of the automobile hub polishing robot. © 2023 IEEE.

关键词： Finite element method

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Visual servoing of magnetic swimming robot based on mean shift and fast template matching algorithm

Visual servoing of magnetic swimming robot based on mean shi...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Xiang, Hongbiao Zhang, Tilei Li, Mengwei Wang, Shoujun Yang, Xiuping Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781728163215

The actuation and control of mini-scale swimming robots have exhibit promising potential in limited and constrained environments, such as biomedical, micro-assembly and microfluidic applications. However, closed-loop control is still a challenging for the precision and repeatability in those applications. In this paper, a new type of soft-micro swimming robot based on magnetoelastic composite material is designed, and the swimmer can move freely on the water surface controlled by a rotating magnetic field with visual servoing. The visual feedback control strategy is proposed based on Mean Shift Algorithm and Fast Template Matching. The algorithm includes three parts: prediction, template matching, target positioning and template updating. To understand the characteristics of the swimmer, the relationship between swimming speed and magnetic field strength and frequency is verified by the algorithm in experiments. Furthermore, the proposed path following method with visual servoing applied in this control system. The experimental results show that the algorithm runs fast, has high accuracy and good real-time performance, and can provide great potential in mini-scale robot applications. © 2019 IEEE.

关键词： Visual servoing

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Research on intelligent Fault Diagnosis Method of Planetary Gearbox based on ITD and CNN 15

Research on Intelligent Fault Diagnosis Method of Planetary ...

引用

15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Zhu, Songsong Chen, Jiwei Xie, Ruitong Song, Yuhao Zhang, Mian Zhao, Mengxiong 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 Tianjin300384 China

ISBN: (纸本)9798350354010

Accurate fault diagnosis of planetary gearboxes (PGs) is crucial for preventing equipment failures and extending their lifespan. To enhance the efficiency and accuracy of PG fault diagnosis, this paper proposes a novel method integrating intrinsic time scale decomposition (ITD) with convolutional neural network (CNN). The proposed method leverages the demodulation capability of ITD to decompose and reconstruct the original signal, effectively removing irrelevant noise and isolating core fault features, and the learning ability of CNN to accurately identify the fault features. Compared to methods relying on CNN only, the proposed method not only improves the computational efficiency but also achieves higher fault diagnosis accuracy. © 2024 IEEE.

关键词： Convolutional neural networks

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Exploration and Practice of Hierarchical Graduation Project under the Background of Science Collaborative Education and Engineering Education Accreditation 5

Exploration and Practice of Hierarchical Graduation Project ...

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5th International Conference on Advances in Artificial Intelligence, ICAAI 2021

作者： Gao, Lilan Tan, Yansong Sun, Yanfang Lv, Linwei Li, Bin Gao, Qijun Wang, Xiaofei Zhao, Yijiao 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 Tianjin300384 China

ISBN: (纸本)9781450390699

Graduation project is an important integrated practice segment for undergraduate education, since the quality of undergraduate education can be directly evaluated by the quality of graduation project. Under the background of science collaborative education and engineering education accreditation, it is necessary to explore an intelligent and integrated graduation project system to train students by all sorts of engineering and research projects, thus improve students' practical ability and innovation ability. This paper first analyzed the problems of the graduation project in the major of process equipment and control engineering, then introduced a novel hierarchical graduation project system to adapt to the concept of science collaborative education and engineering education. By putting the novel graduation project system into effect, the quality of graduation project has significantly improved. © 2021 ACM.

关键词： Accreditation

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An Order Demodulation Analysis Method for Planetary Gearboxes

An Order Demodulation Analysis Method for Planetary Gearboxe...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Chen, Jiwei Xie, Ruitong Zhu, Songsong Zhao, Mengxiong Wang, Zhiyuan Zhang, Mian Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

In addressing challenges such as the speed change of planetary gearbox (PG) during operation and the complexity in extracting fault features, an order demodulation analysis method based on order tracking (OT) and variational mode decomposition (VMD) is proposed. Non-stationary time domain signals are transformed into relatively stable angular domain signals through angular resampling. The intrinsic mode function (IMF) is obtained by demodulation of the angular multi-component signal using the VMD method. The instantaneous order of a proper IMF is calculated via Hilbert Transform. The sensitive single component is selected by matching the meshing order and the central order of the instantaneous order. Finally, the amplitude of the characteristic order components extracted from the instantaneous order spectrum was used as features and Support Vector Machine (SVM) was employed for the classification of four different conditions in the sun gear. Comparing the results of the proposed method with Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), the experimental results demonstrate the effectiveness of the proposed method in diagnosing PGs under non-stationary conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Epicyclic gears

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