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A practical simulation approach for the support of wire arc DED additive manufacturing systems design

Procedia Computer Science 2024年 232卷 3161-3172页

作者： Iosif Karouanas Panagis Foteinopoulos Harry Bikas Panagiotis Stavropoulos Laboratory for Manufacturing Systems and Automation Department of Mechanical Engineering and Aeronautics University of Patras Patras 26504 Greece

Wire Arc Directed Energy Deposition (DED) is a subcategory of the DED Additive Manufacturing (AM) technology that is rapidly gaining popularity due to its potential to produce large-scale, complex metal parts while maintaining a lower cost and higher productivity and sustainability when compared with other AM technologies. Additionally, Wire Arc DED permits a high level of customization in terms of designing and implementing manufacturing systems. However, there are still important quality issues hindering wire Arc DED, along with limited simulation approaches that offer the necessary practicality, from an industrial perspective, to support the design of wire Arc DED manufacturing systems. Towards this goal, aiming to the minimization of the experimental cost and time, a simulation approach of wire arc DED is presented in this study. The model has been developed in COMSOL Multiphysics, allowing for a high level of customization, while maintaining practicality and ease of use, both in terms of implementation as well as computational cost. The modeling approach is analyzed, followed by the implementation of the methodology in a case study. Preliminary results are presented, discussed, and accompanied by suggestions for future research.

关键词： Additive Manufacturing Simulation Thermal Wire Arc Additive Manufacturing Directed Energy Deposition

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A modular framework of robot gripping tools for human robot collaborative production lines

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Procedia CIRP 2024年 126卷 164-169页

作者： A. Papavasileiou S. Aivaliotis P. Mparis P. Mantas S. Makris Laboratory for Manufacturing Systems and Automation Department of Mechanical Engineering and Aeronautics University of Patras Patras 26504 Greece

Robot gripping systems are subject to many technological transformations because of their need to adjust to a continuously changing market involving a large diversity of products and materials. This issue is further burdened by the high integration and control complexity in HRC environments. This paper proposes a modular framework of gripping tools with versatility in grasping and processing of different components based on automatic tool change solutions. control and safety modules are being investigated for the flexible and safe handling of components. The proposed framework is being applied to two industrial scenarios from the white goods and the automotive sectors.

关键词： Robot Grippers Human Robot Collaboration, Agile Production

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Suitability assessment method for safe robot tooling design in Human-Robot Collaborative applications

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Procedia CIRP 2024年 128卷 770-775页

作者： Konstantinos Katsampiris-Salgado Nikos Dimitropoulos George Michalos Sotiris Makris Laboratory for Manufacturing Systems and Automation Department of Mechanical Engineering and Aeronautics University of Patras Patras 26504 Greece

State of the art applications in human-robot collaborative work cells, are, sometimes, highly compromised by strict directives to avoid potential hazards for operators. Robot motion (e.g., speed, momentum, power etc.) is strictly defined according to ISO/TS15066 to guarantee that potential pressures and forces due to collisions do not exceed predefined limits for different parts of the human body. In this direction the authors suggest a robotic tool design methodology that could optimize Human – Robot Collaborative (HRC) applications by preventing vast reduction of robot velocity during the design phase, while eliminating the need for redesign during the validation stages of the cell. Also, actuation mechanisms and their components are also presented to uphold human safety standards. To demonstrate the effectiveness of the proposed method, a real-life industrial use case has been materialized, involving a high-payload collaborative robot performing assembly operations. The results underscore the effectiveness of these design practices in enhancing the efficiency and safety of human-robot collaboration.

关键词： Human – Robot Collaboration Workspace design Safety

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Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 47-63页

作者： Yongliang Yang Zihao Ding Rui Wang Hamidreza Modares Donald C.Wunsch Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation&Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Automation Beijng Institute TechnologyBeijing 100081China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA Department of Electrical&Computer Engineering Missouri University of Science&TechnologyRollaMO 65401 USA

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the *** presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller *** task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the ***-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance *** the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity *** this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task *** simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

关键词： Adaptive impedance control data-driven method human-robot interaction(HRI) reinforcement learning velocity-free

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Design for 3D Printing of a Robotic Arm Tool Changer under the framework of Industry 5.0 10

Design for 3D Printing of a Robotic Arm Tool Changer under t...

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10th CIRP Global Web Conference on Material Aspects of Manufacturing Processes

作者： Mourtzis, Dimitris Angelopoulos, John Papadokostakis, Michalis Panopoulos, Nikos Laboratory for Manufacturing Systems and Automation Department of Mechanical Engineering and Aeronautics University of Patras 26504 Greece

A significant shift from traditional lines to reconfigurable and reprogrammable robotic cells has occurred in Industry 4.0. Collaborative robots can be used for automating several tasks for improving Human-Machine Interface (HMI). The ability of a robot carrying out different tasks is proportional to the tools that it can use, thus it is crucial that robots are equipped with systems enabling efficient tool changing. Therefore, in this paper an automatic tool changer system is proposed. Based on Finite Element Analysis (FEA) of the design and the specifications, a 3D printed prototype was made and tested on a UR 10 Collaborative Robot. © 2022 Elsevier B.V.. All rights reserved.

关键词： Industry 4.0

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Performance Analysis and Flexible control of a Novel Ball Double-screw Hydraulic Robot Knee Joint

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Journal of Bionic engineering 2023年第5期20卷 2147-2163页

作者： Jie Shao Yongming Bian Meng Yang Guangjun Liu School of Mechanical Engineering Tongji UniversityShanghai201804China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou310027China Department of Control Science and Engineering Tongji UniversityShanghai201804China National Engineering Technology Research Center for Prefabrication Construction in Civil Engineering Tongji UniversityShanghai200092China

Focusing on the ball double-screw hydraulic knee joint as the research object,this paper analyzes the load driving performance of the hydraulic knee *** the posture data of the human body such as walking,squatting and landing buffer as initial learning objects,motion features are *** simplifying the trajectories of different motion actions into key feature control points and flexible trajectory fitting,the trajectory of joint actions is *** method can realize the adaptability of the hydraulic robot knee joint in different movements,and take the flexible action as the optimization goal under the condition of ensuring the movement performance,so as to reduce the damage to the knee joint caused by the foot impact in *** simulation model was built by Adams and Matlab to complete the performance analysis and motion optimization experiment of the knee *** simulation results show that the foot impact force of the experimental model decreases gradually through ***,the method is applied to the hydraulic joint experimental prototype to prove its load capacity and flexible motion control performance.

关键词： Bionic robot Ball double-screw hydraulic joint Robot knee joint Performance analysis Humanoid motion control Flexible control

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Simulated Ising Annealing Algorithm with Gaussian Augmented Hamiltonian Monte Carlo 42

Simulated Ising Annealing Algorithm with Gaussian Augmented ...

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42nd Chinese control Conference, CCC 2023

作者： Li, Langyu Wang, Hao Xie, Zhixin Liu, Zixuan Cui, Wei Pan, Yu Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China School of Mechanical Engineering and Automation Harbin Institude of Technology Shenzhen518055 China

ISBN: (纸本)9789887581543

A numerical technique called Simulated Ising Annealing (SIA) uses digital computers to obtain approximations of the ground states of Ising models. The quadratic unconstrained binary optimization (QUBO) problem in combinatorial optimization, which is challenging to solve through exhaustive search, has significant linkages to the Ising model. Therefore, SIA's main objective is to identify a better solution in finite iterations. In order to enhance the performance of the simulated annealing procedure, we adopt a Gaussian augmented Hamiltonian Monte Carlo (GAHMC) method in this study. We contrasted our algorithm with Gibbs sampling and local quantum annealing method. Finally, we discuss its application on QUBO problem. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Simulated annealing

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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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Safety-Aware Trajectory Tracking using High-Order control Barrier Functions 63

Safety-Aware Trajectory Tracking using High-Order Control Ba...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Rousseas, Panagiotis Panagou, Dimitra Kyriakopoulos, Kostas National Technical University of Athens Control Systems Laboratory School of Mechanical Engineering Greece University of Michigan Department of Robotics and the Department of Aerospace Engineering MI United States Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350316339

A novel method on safety-aware trajectory tracking is presented in this work. The proposed scheme employs control Barrier Functions (CBFs) along with a latent-space representation over the barrier and its derivatives. While such representations have also been employed in the literature, the innovation of the proposed method lies in formulating a novel tracking problem on the latent space, enabling for the shape of linear class -K functions that are included in the safety condition induced by the control barrier function to be chosen constructively. Additionally, the aforementioned safety condition is modified based on the latent-space tracking through the addition of an extra term. This enables maintaining safety guarantees and is demonstrated to provide decreased tracking errors compared to the nominal control barrier function scheme. Numerical simulations validate the efficacy of the proposed scheme, as well as its ability for online implementation. © 2024 IEEE.

关键词： Safety engineering

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Generative AI for automated task modelling and task allocation in human robot collaborative applications

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CIRP Annals 2025年

作者： Dimitropoulos, Nikos Kaipis, Michalis Giartzas, Stavros Michalos, George Laboratory for Manufacturing Systems and Automation Department of Mechanical Engineering and Aeronautics University of Patras Patras26504 Greece

Task modelling and assignments generation is a complex and time-consuming activity despite the availability of modern CAx and planning tools. This paper proposes an AI based framework using Large Multi-Modal Models and a Digital Twin to automatically create task models, sequences and assignment plans through the processing of video streams involving visual and audio cues on the recorded resources, tools, and tasks. The same LMMs perform the task-to-resource allocation considering metrics such as human factors and resource workload. A case study on the assembly of white goods showcases reduction in manual planning, enhanced resources utilization and improved human-robot collaborative applications. © 2025 The Author(s)

关键词： Process planning

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