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作者： Yang, Shengluo Wang, Junyi Xu, Zhigang School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai200093 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

Distributed manufacturing has become common in the globalized production environment. Facing the tendency of mass customization, distributed workshops are required to have the reconfiguration capability to produce multiple products. Based on the scheduling demands of distributed workshops, this paper studied the dynamic distributed reconfigurable flowshop scheduling problem (DRFSP) with new job arrivals using deep reinforcement learning (DRL) for the first time. The DRL-based intelligent scheduling and reconfiguration systems are modeled by designing efficient rewards, actions, and state features for both scheduling and reconfiguration agents. A new state feature normalization approach is proposed to address the variability in production configurations and dynamics. A novel expected deep Q-network (EDQN) algorithm is proposed to provide more precise state-action values rather than using estimations. Moreover, the DRL-based training and execution procedures for the dynamic DRFSP are provided by combining decision-making, agent learning, and reconfigurable production. Training curves validate the reasonableness of system modeling and the good learning efficiency of the EDQN algorithm. Extensive comparison experiments show that our EDQN algorithm outperforms three popular DRL algorithms and four well-known priority dispatching rules (PDRs) by around 20 % and 89 % respectively, with good generalization ability and time efficiency. The average decision time under dynamics is only 0.65 ms, which enables real-time scheduling. © 2023 Elsevier Ltd

关键词： Reinforcement learning

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A Lightweight YOLOv5 Model Integrating GhostNet and Attention Mechanism 4

A Lightweight YOLOv5 Model Integrating GhostNet and Attentio...

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4th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2023

作者： Dou, Xinke Wang, Ting Shao, Shiliang School of Information Engineering Shenyang University of Chemical Technology Shenyang China Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350326444

Aiming at the problems of complex structure of neural network, large number of parameters and difficult deployment to terminal devices, this paper proposes an improved lightweight object detection model for the purpose of building a model with high classification accuracy and low complexity. First, the one-stage detector yolov5 is used as the base network. Considering the excessive redundant features of feature extraction, Ghost module is used to replace the traditional convolution, effectively allocate computing resources, to reduce the size of the model and improve the speed of model detection. When designing model bottleneck structure, Normalization-based Attention Module (NAM) is added to improve training efficiency and reduce model complexity. Experimental results show that compared with YOLOv5, the calculation speed of the proposed model is increased by 17% and the accuracy is reduced by less than 2%, which is of great significance in the environment of low-performance computing equipment. © 2023 IEEE.

关键词： Object detection

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Modeling of dynamic-elastic deformation error for a collaborative robot 18

Modeling of dynamic-elastic deformation error for a collabor...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zhu, Shijing Pan, Xinan Wang, Hongguang Li, Dianqi School of Mechanical Engineering Shenyang University of Technology Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9798350312201

In the operation of a collaborative robot, the inertial force, gravity force, and other factors can cause elastic deformation of links and joints, and hence results in considerable deviations from the desired trajectory. However, the effects of inertial force, gravity force, and Jacobian matrix are rarely considered in common deformation analyses. This paper proposes a method for modeling dynamic elastic deformation of collaborative robots including joint torsional stiffness and complementary stiffness. Firstly, the dynamics equation was established based on the Newton-Euler method, and the driving torque of the joint was analyzed. Secondly, a dynamic-elastic deformation error model was established based on the joint torsional stiffness and complementary stiffness. Finally, the simulation results show that the established dynamic error model has good predictability, and the relative error is less than 1.63% compared with the ADAMS simulation results. © 2023 IEEE.

关键词： Errors

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Cooperative Control of Dual-Arm Robot of Adaptive Impedance Controller Based on RBF Neural Network 16th

Cooperative Control of Dual-Arm Robot of Adaptive Impedance ...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Zhang, Tongyan Wang, Ting Shao, Shiliang Cao, Zonghan Dou, Xinke Qin, Hongwei School of Artificial Intelligence Shenyang University of Technology Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Software Shenyang University of Technology Shenyang China School of Information Engineering Shenyang University of Chemical Technology Shenyang China

ISBN: (纸本)9789819964918

Traditional impedance control methods often fail to accurately track force signals in unknown or changing environments, resulting in failure or instability in tasks such as coordinated handling. To solve the above problems, this paper adds the RBF neural network strategy, based on the traditional impedance control. First a model for the contact force between the dual redundant robotic arms and the environment is constructed, and the RBF neural network is used to estimate the stiffness of the changing environment online. Then, a dynamic adaptive force control co-simulation model is established. The change in the contact force is adapted to adjust the parameters of the two-arm impedance model to compensate for unknown environmental changes. Simulation experiments showed that the enhanced impedance control strategy is appropriate for the force-interaction circumstances of the robotic arm within the positional environment, has a stronger durability, enhances the sturdiness of the two-armed working together robot in an environment that shifts, and has a more effective force control effect. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Robotic arms

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System Research of Pear Picking Robot 4

System Research of Pear Picking Robot

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4th International Conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2022

作者： Chai, Jianfei Chen, Yi Zhang, Yunyou Wu, Jun Hu, Xiaomei Information Technology Office School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9781450398343

China is a big producer and consumer of pears, and Chinese pear industry has long been based on labor as the main productive force. With the decline of the demographic dividend, labor costs have gradually increased, and labor efficiency has gradually become difficult to meet the needs of modern production. The development of a pear picking robot and its application to actual picking operations is an urgent research. Based on the investigation of the planting environment of pear orchards, this paper designs and builds a pear picking robot. The picking robot consists of a right-angle mechanical arm, a moving system, a control system, and a visual recognition system. On account of the deep learning algorithm, it can accurately identify and locate the pears, and then pick the fruit in a way that the external force is released, so as to realize the damage free picking of the pears. The Outdoor picking experiment shows that the picking robot designed in this paper has a good picking rate in different time periods. © 2022 ACM.

关键词： Object detection

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A Pillbug-Inspired Morphing Mechanism Covered with Sliding Shells 24th

A Pillbug-Inspired Morphing Mechanism Covered with Sliding S...

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24th IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2024

作者： Wang, Jieyu Tian, Yingzhong Xi, Fengfeng Chablat, Damien Lin, Jianing Ren, Gaoke Zhao, Yinjun School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China Department of Aerospace Engineering Toronto Metropolitan University Toronto Canada Nantes France School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (纸本)9789819614639

This research proposes a novel morphing structure with shells inspired by the movement of pillbugs. Instead of the pillbug body, a loop-coupled mechanism based on slider-crank mechanisms is utilized to achieve the rolling up and spreading motion. This mechanism precisely imitates three distinct curves that mimic the shape morphing of a pillbug. To decrease the degree-of-freedom (DOF) of the mechanism to one, scissor mechanisms are added. 3D curved shells are then attached to the tracer points of the morphing mechanism to safeguard it from attacks while allowing it to roll. Through type and dimensional synthesis, a complete system that includes shells and an underlying morphing mechanism is developed. A 3D model is created and tested to demonstrate the proposed system’s shape-changing capability. Lastly, a robot with two modes is developed based on the proposed mechanism, which can curl up to roll down hills and can spread to move in a straight line via wheels. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： 1-DOF Bio-inspired mechanism Loop-coupled Morphing structure Multiple-mode

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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1313-1316页

作者： Tianyu Shen Jinlin Sun Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Peng Cheng Laboratory Shenzhen 518000China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real *** this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5].

关键词： Intelligence DAO TAO

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Obstacles Avoidance Path Planning for Mobile Robot Based on Cellular Automata 6

Obstacles Avoidance Path Planning for Mobile Robot Based on ...

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6th International Conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2024

作者： Li, Lili Li, Wenwei Huang, Jinglun School of Automation Science and Engineering South China University of Technology Guangzhou China Institute of Intelligent Manufacturing Shunde Polytechnic Foshan China Department of Technical Research South China Robotics Innovation Research Institute Foshan China Foshan Zhiyouren Technology Co. Ltd. Foshan China School of Electronics and Information Engineering Wuyi University Jiangmen China

ISBN: (纸本)9798331541699

In order to quickly plan the shortest path for mobile robot in two-dimensional space, a two-stage obstacles avoidance path planning algorithm based on cellular automata was presented in this paper. For the first stage, the distance between each free cell to the ending cell was gradually generated by the evolution of cellular automata, and the algorithm’s cellular space, cellular states, Moore type neighbors and evolutionary rules were described, respectively. For the second stage, by using the idea of the negative gradient, a method of generating the shortest path based on the cells’ state values was proposed. Accordingly, the corresponding flow chart and Matlab programme of the algorithm were designed. The effectiveness of the algorithm was verified by the simulation and the physical experiment. The results showed that the shortest path in complex environment can be efficiently planned by using our cellular automata algorithm. © 2024 IEEE.

关键词： Microrobots

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Kinetostatic Model of Redundant Actuation Modes in a Lockable Variable Geometry Truss Manipulator Driven by Flexible Limbs 24th

Kinetostatic Model of Redundant Actuation Modes in a Lockabl...

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24th IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2024

作者： Zhao, Yinjun Xi, Fengfeng Hao, Guangbo Tian, Yingzhong Li, Long Wang, Jieyu School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China Department of Aerospace Engineering Toronto Metropolitan University TorontoON Canada School of Engineering and Architecture-Electrical and Electronic Engineering University College Cork Cork Ireland

ISBN: (纸本)9789819614639

Manipulators consisting of multiple large deformation limbs can flexibly change their shapes and separate actuation systems from mechanism body, making them particularly suitable for requirements of compact design space, and continuous and versatile deformation. However, the low structural stiffness restricts their practical applications. To enhance the stiffness, we have integrated lockable variable geometry truss (LVGT) supports within the manipulator design. Depending on the number of locked branches within the LVGT, the active flexible limbs may exhibit redundant actuation modes, meaning that the number of working actuators exceeds the DOF of the internal LVGT. The redundant actuation modes, while beneficial for enabling heavier load manipulation, poses challenges in mechanical analysis, necessitating a comprehensive consideration of factors such as motion constraints from rigid joints, nonlinear coupling deformations in the flexible limbs, and control strategies for the redundant actuators. In this paper, we construct a mechanical analysis framework tailored for such operating modes. This framework enables the kinetostatic analyses under the consideration of distributing redundant actuation forces. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Geometry

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Simulation Research on Residual Stress of Swage Autofrettage-processed High-Pressure Cylinder 9

Simulation Research on Residual Stress of Swage Autofrettage...

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2023 9th International Conference on Applied Materials and manufacturing technology, ICAMMT 2023

作者： Sun, Lihua Zhou, Rongxuan Li, Guiqin Li, Jianing Mitrouchev, Peter Engineering Training Center Changchun University of Technology Changchun China School of Mechanical Engineering and Automation Northeastern University Shenyang China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China University Grenoble Alpes G-SCOP Grenoble France

The vital component of the high-pressure pump is the high-pressure cylinder, which undergoes pulsating cyclic loads during operation. This exposure can lead to fatigue cracking and limit the pump's overall performance. To address this issue, a swage autofrettage treatment method for the high-pressure cylinder is proposed based on the principles of autofrettage technology. The structure parameters of the mandrel are designed to optimize its role in the treatment process. Subsequently, a swage autofrettage simulation model is established, considering the Bauschinger effect to analyze the distribution of residual stress about the mandrel interference percentage. The results demonstrate that the swage autofrettage treatment improves the stress distribution in the high-pressure cylinder, causing the inner wall surface to undergo a circumferential residual compressive stress. Within a specific range, the Bauschinger effect becomes more significant as the mandrel interference percentage increases. This study provides insights for enhancing the durability and performance of high-pressure cylinders while adhering to mechanical engineering standards. © Published under licence by IOP Publishing Ltd.

关键词： Residual stresses

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