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13th International Conference on Information, Intelligence, systems and Applications, IISA 2022

作者： Garrido, Aitor J. Marco, Aitor De La Sen, Manuel Oleagordia, Inigo Garrido, Izaskun University of the Basque Country - UPV/EHU Automatic Control Group - Acg Institute of Research and Development of Processes - Iidp Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao Po Rafael Moreno 3 Bilbao48013 Spain University of the Basque Country - UPV/EHU. Automatic Control Group - Ac Advanced Design and Analysis Department Idom Zarandoa Etorb. 23 Bilbao48015 Spain University of the Basque Country - UPV/EHU Automatic Control Group - Acg Institute of Research and Development of Processes - Iidp Department of Electricity and Electronics Faculty of Science and Technology B° Sarriena s/n Leioa48080 Spain

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

This paper deals with the upgrade and testing of the of the Ultra-Low Iota Super Elongated Stellarator of the University of the Basque Country. The main upgrades affect to the coil system but also to the microwave source and the data acquisition system. Therefore, it is necessary to update its State-Space model. The updated model is validated by means of experimental output data showing an accurate matching with the real system. Then, in order to test the new model, a Model Predictive control-MPC scheme is successfully implemented both in simulation and experimentally using a real-time control platform. © 2022 IEEE.

关键词： Model predictive control

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Node Classification in CAD Data: A Graph Learning Approach for Machining Feature Localization

Node Classification in CAD Data: A Graph Learning Approach f...

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Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Stefan Andreas Böhm Martin Neumayer Rui Song Fabian Riß Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems Technical University of Munich Munich Germany Research and Development Department Rosenheim Technical University of Applied Sciences Rosenheim Germany Fraunhofer Institute for Transportation and Infrastructure Systems Ingolstadt Germany Faculty of Engineering Sciences Rosenheim Technical University of Applied Sciences Rosenheim Germany

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

Pattern recognition is becoming increasingly important in many sectors, such as the manufacturing industry. With rising customer demands and advancing technology, product data, often represented as 3D meshes, is becoming highly complex. Therefore, intelligent approaches are needed to recognize and localize features in 3D meshes to determine complex manufacturing processes. However, previous approaches solely work on voxel-, pixel- or. STEP-based formats and not directly on mesh-based formats such as STL data. To overcome these issues, we present a configurable data generator and customize graph neural network architectures for the problem of localizing machining features directly in 3D meshes. After comparing the graph neural networks against each other, the best resulting network is compared to an existing state-of-the-art approach, i.e., SsdNet. Our results indicate that the best-performing graph neural network exhibits superior classification accuracies on meshes with few machining features compared to SsdNet with an average F1 score of 80%. While the accuracy slightly falls behind SsdNet with more features, the graph neural network shows substantially better runtime performance results, which are, on average, 70 times faster.

关键词： Training Solid modeling Three-dimensional displays Runtime Accuracy Shape Scalability Machining Graph neural networks Generators

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AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Zhang, Sichao Liang, Wei Zhang, Yinlong Pang, Zhibo State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Technology Abb Corporate Research Sweden Department of Automation Vasteras72178 Sweden

ISBN: (纸本)9781728119489

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method. © 2022 IEEE.

关键词： Semantics

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Incremental Model Predictive control for Velocity-controlled Robot Manipulators

Incremental Model Predictive Control for Velocity-Controlled...

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Annual Conference of Industrial Electronics Society

作者： Yongchao Wang Hengrui Li Cong Li Fangzhou Liu School of Aerospace Science and Technology Xidian University Xi’an China Algorithm Engineer Research and Development Department Agile Robots Beijing China College of Intelligence Science and Technology National University of Defense Technology Changsha China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In this article, an incremental model predictive controller is proposed for the velocity-controlled robot manipulator. First, the time-delay estimation (TDE) technique is used to approximate the unknown discrepancy between the command and the real joint velocity due to velocity dynamics, and the equation of motion in the incremental form is obtained. Then, on the basis of the resulting equation of motion and taking into account joint position and velocity constraints, the incremental model predictive controller is developed by formulating a constrained optimal control problem (OCP). The constrained OCP is cast to a quadratic programming (QP) problem, making it possible to employ computationally efficient QP solvers to solve the constrained OCP. As a result, real-time control is guaranteed. Finally, experiments on a robot manipulator are implemented to verify the effectiveness of the developed incremental model predictive controller.

关键词： Service robots Computational modeling Optimal control Estimation Predictive models Mathematical models Robustness Computational efficiency Quadratic programming Predictive control

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Parallelizable Parametric Nonlinear System Identification via tuning of a Moving Horizon State Estimator

arXiv

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arXiv 2024年

作者： Simpson, Léo Asprion, Jonas Muntwiler, Simon Köhler, Johannes Diehl, Moritz Research and Development Tool-Temp AG Switzerland Department of Mathematics University of Freiburg Freiburg79104 Germany Institute for Dynamic Systems and Control ETH Zürich Zürich8092 Switzerland University of Freiburg Freiburg79110 Germany

This paper introduces a novel optimization-based approach for parametric nonlinear system identification. Building upon the prediction error method framework, traditionally used for linear system identification, we extend its capabilities to nonlinear systems. The predictions are computed using a moving horizon state estimator with a constant arrival cost. Eventually, both the system parameters and the arrival cost are estimated by minimizing the sum of the squared prediction errors. Since the predictions are induced by the state estimator, the method can be viewed as the tuning of a state estimator, based on its predictive capacities. The present extension of the prediction error method not only enhances performance for nonlinear systems but also enables learning from multiple trajectories with unknown initial states, broadening its applicability in practical scenarios. Additionally, the novel formulation leaves room for the design of efficient and parallelizable optimization algorithms, since each output prediction only depends on a fixed window of past actions and measurements. In the special case of linear time-invariant systems, we show an important property of the proposed method which suggests asymptotic consistency under reasonable assumptions. Numerical examples illustrate the effectiveness and practicality of the approach, and one of the examples also highlights the necessity for the arrival cost. Copyright © 2024, The Authors. All rights reserved.

关键词： Nonlinear systems

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Trajectory planning of a manipulator based on the DDPG algorithm

Trajectory planning of a manipulator based on the DDPG algor...

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2022 International Workshop on Automation, control, and Communication Engineering, IWACCE 2022

作者： Jing, Xiangyu Zang, Chuanzhi Liu, Yuqi Liu, Yu Xia, Changqing Shenyang University of Technology No. 111 Shenliao West Road Economic and Technological Development Zone Shenyang110870 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9781510660915

Trajectory planning is one of the key technologies in the manipulator motion system, and the effectiveness of the manipulator as a whole is directly influenced by this technology. Thus, accurate and effective trajectory planning is crucial. In this study, a reinforcement learning system is used to plan a manipulator's trajectory. A trajectory planning of a manipulator based on the deep deterministic policy gradient (DDPG) method, which is easier to converge on than the Actor-Critic (AC) approach, is proposed in order to address the issue that the AC algorithm is difficult to converge on. A guiding reward function is provided in the reward function area to address the issue that the manipulator can't contact the target rapidly due to blind exploration. This can help the manipulator touch the target more quickly. In this paper, a twodegree of freedom manipulator is selected as the experimental object. The obstacle avoidance reward function based on the AC algorithm, the obstacle avoidance reward function based on the DDPG algorithm, and the obstacle avoidance reward function and guiding reward function based on the DDPG algorithm are compared. The findings demonstrate that the DDPG method converges easier than the AC algorithm, and that the directed reward function can help the manipulator avoid obstacles. © 2022 SPIE. All rights reserved.

关键词： Manipulators

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Simulation Model of a Pneumatic Drive for Compressing Electrodes of Stationary Contact Spot Welding Machine 5

Simulation Model of a Pneumatic Drive for Compressing Electr...

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5th International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Sandler, Ilya L Ivanov, Dmitriy V Terekhin, Michail A Bragina, Irina N Lebakin, Ilya V Zaripov, Ruzil A Samara State University of Railway Transport Dept. Digital Technologies Samara Russia Samara State Technical University Dept. Automation and Control in Technical Systems Samara Russia Samara National Research University Dept. Information Systems Security Samara Russia Samara State University of Transport Higher School of Medical Engineering Institute of Innovative Development FSBEI HE SamSMU MOH Russia Dept. Digital Technologies Samara Russia

ISBN: (纸本)9798350309126

The article presents a simulation model of a pneumatic drive for electrodes of a stationary contact spot welding machine. Thanks to the developed model, it becomes possible to analyze the system, as well as visually study its operation. The result of modeling the system is the obtained transients of the elements of the pneumatic system. The developed simulation model adequately describes the state and behavior of a real system of pneumatic compression of electrodes. The work is of interest to pneumatic engineers, designers and other specialists working in the field of pneumatics and can be used for more accurate and efficient design, analysis and optimization of not only a specific system of pneumatic compression of electrodes, but also pneumatic systems in general. © 2023 IEEE.

关键词： Spot welding

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Large receptive field strategy and important feature extraction strategy in 3D object detection

arXiv

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arXiv 2024年

作者： Cui, Leichao Li, Xiuxian Meng, Min Jia, Guangyu Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201800 China The Centre for Robotics Research Department of Engineering King’s College London Strand LondonWC2R 2LS United Kingdom

The enhancement of 3D object detection is pivotal for precise environmental perception and improved task execution capabilities in autonomous driving. LiDAR point clouds, offering accurate depth information, serve as a crucial information for this purpose. Our study focuses on key challenges in 3D target detection. To tackle the challenge of expanding the receptive field of a 3D convolutional kernel, we introduce the Dynamic Feature Fusion Module (DFFM). This module achieves adaptive expansion of the 3D convolutional kernel’s receptive field, balancing the expansion with acceptable computational loads. This innovation reduces operations, expands the receptive field, and allows the model to dynamically adjust to different object requirements. Simultaneously, we identify redundant information in 3D features. Employing the Feature Selection Module (FSM) quantitatively evaluates and eliminates non-important features, achieving the separation of output box fitting and feature extraction. This innovation enables the detector to focus on critical features, resulting in model compression, reduced computational burden, and minimized candidate frame interference. Extensive experiments confirm that both DFFM and FSM not only enhance current benchmarks, particularly in small target detection, but also accelerate network performance. Importantly, these modules exhibit effective complementarity. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Determination of the Characteristics of Gears of Robot-Like systems by Analytical Description of their Structure

Determination of the Characteristics of Gears of Robot-Like ...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Stefan Landler Raúl Molina Blanco Michael Otto Birgit Vogel-Heuser Markus Zimmermann Karsten Stahl Technical University of Munich Germany TUM School of Engineering and Design Department of Mechanical Engineering Munich Institute of Robotics and Machine Intelligence (MIRMI) Institute of Machine Elements Gear Research Center (FZG) Institute of Automation and Information Systems (AIS) Laboratory for Product Development and Lightweight Design (LPL)

The axes of robots and robot-like systems (RLS) usually include e-motor-gearbox-arrangements for optimal connection of the elements. The characteristics of the drive system and thus also of the robot depend strongly on the gears. Different gearbox designs are available which differ in stiffness, efficiency and further properties. For an application-optimal design of RLS a uniform documentation and a comparability of gearbox concepts is a decisive factor. The application-optimal design is supported by an interdisciplinary approach between mechanical engineering and software design, guided by adequate product development methodology. The quite heterogeneous characterization of gearboxes for RLS which is currently the state of the art is a relevant obstacle in the flexible and optimal design of RLS. The paper shows the analysis of the gear structure with unified symbols for specific machine elements and contact types. The introduced method gives insight into the mechanical structure of the gearboxes. Similarities between gear types can thus be revealed. This also enables the classification of new developments in the state of the art. Moreover, the developed method for analyzing the gear structure can be used to determine the characteristics of gears. Examples for these characteristics are backlash, efficiency or stiffness. Specifically, the stiffness of gears can be synthesized by the force action of individual contacts and the individual phenomena that occur with them. The representation by individual phenomena also makes it possible to extend the calculation to include influencing parameters such as temperature that have not been sufficiently taken into account so far.

关键词：

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Parallelizable Parametric Nonlinear System Identification via tuning of a Moving Horizon State Estimator

Parallelizable Parametric Nonlinear System Identification vi...

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IEEE Conference on Decision and control

作者： Léo Simpson Jonas Asprion Simon Muntwiler Johannes Köhler Moritz Diehl Research and Development Tool-Temp AG Switzerland Department of Mathematics University of Freiburg Freiburg Germany Institute for Dynamic Systems and Control ETH Zürich Zürich Switzerland Department of Microsystems Engineering (IMTEK) University of Freiburg Freiburg Germany

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

关键词： Linear systems Costs Buildings control systems Prediction algorithms Windows Trajectory Nonlinear systems Tuning Optimization

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