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检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

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Robust ESO Based Control for Interval Plant: Application to Piezoelectric Positioning Stage Working at Changing Temperatures

Robust ESO Based Control for Interval Plant: Application to ...

引用

Electrical Engineering, Control and robotics (EECR), international conference on

作者： Mingchen Chen Peng Yan School of Automation Science and Electrical Engineering Beihang University Beijing China School of Mechanical Engineering Shandong University Jinan China

ISBN: (数字)9798350370003

ISBN: (纸本)9798350370010

There are a number of challenges in precision control of piezoelectric actuated micro/nano-motion devices, including uncertainty in modeling and environmental disturbances. Especially, the parameters of piezoelectric actuated systems may wander noticeably at varying temperatures due to the intrinsic properties of piezoelectric materials. In this work the issue is addressed by importing an interval model to cover all kinds of uncertainties and developing a robust extended state observer(ESO) based control which can limit the closed-loop zeros and poles to acceptable areas although the interval plant exists. With the aid of an equivalency between linear ESO-based control and a type of two-degree-of-freedom controller and root locus approach, all of the controller parameters are adjusted collaboratively in the proposed method. Lastly numerical simulations are performed to validate the effectiveness of the proposed method and to compare it with a conventional ESO based control.

关键词： Robust control Uncertainty Temperature Piezoelectric materials Numerical simulation Temperature control Numerical models

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Diagnosis of Localized Bearing Defects using Texture Analysis of Vibration Envelope Signals and Machine Learning

Diagnosis of Localized Bearing Defects using Texture Analysi...

引用

international conference on robotics and Artificial Intelligence (ICRAI)

作者： Cong Dai Nguyen Fazal E Nasir Shahbaz Khan Sheraz Ali Khan Jong-Myon Kim Faculty of Radio-Electronic Engineering Le Quy Don Technical University Hanoi Vietnam Advanced Robotics and Automation Lab National Center for Robotics and Automation Peshawar Pakistan Institute of Manufacturing University of Engineering and Applied Sciences Swat Pakistan Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan Department of IT Convergence University of Ulsan Ulsan South Korea PD Technology Ulsan South Korea

Bearings are important because they play a critical role in the operation of many machines and devices by reducing friction and enabling smooth motion between two moving parts. They are commonly used in rotating machinery, such as electric motors, turbines, pumps, and gearboxes, where they support and guide the rotating shafts. The primary cause of failure in wind turbines and induction motors is bearing faults, resulting in significant downtime and economic losses. Detecting these faults accurately and promptly is crucial to preventing unexpected shutdowns. Most of the existing methods for bearing fault detection rely on envelope analysis, which involves filtering and demodulating the raw signal, and Fourier analysis of the envelope signal to identify defect frequencies. Recent research has focused on improving the visibility of these frequencies by selecting an optimal band for filtering, using sub-band analysis and spectral kurtosis, which is a complex process and can be time-consuming. This paper presents a new approach to envelope signal analysis using texture analysis of the envelope signals that are projected as 2D grayscale images where each fault generates a unique texture. These textures are encoded using the local binary pattern operator and then used for fault classification. The method is tested on a publicly available seeded fault dataset.

关键词： Vibrations Fault diagnosis Shafts Time-frequency analysis Filtering Pumps Machine learning

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CDHD: Contrastive Dreamer for Hint Distillation 48

CDHD: Contrastive Dreamer for Hint Distillation

引用

48th IEEE international conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Yu, Le Hua, Tongyan Yang, Wenming Ye, Peng Liao, Qingmin Tsinghua University Shenzhen International Graduate School China Country Garden Group Bright Dream Robotics China

ISBN: (纸本)9781728163277

Replaying previous training data is the most effective approach for Class-Incremental Learning (CIL), with its performance bounded by data availability. Therefore, many recent studies consider the Data-Free Class-Incremental Learning (DFCIL) problem that requires no previous data. However, the existing methods do not consider synthesising data of heterogeneity, thus limiting models' generalizability. Such homogenous images further hinder the knowledge distillation process when regularising only the deeper layers close to the output, resulting in catastrophic forgetting. To address these issues, we present CDHD: a contrastive dreamer for hint distillation. Our approach starts with training a generator for data synthesis. A model inversion technique is introduced to obtain a generator capable of producing heterogeneous images from the classifier by imposing the ContRastive Loss. Moreover, to better transfer the previous knowledge to the current model, we force the teacher network to provide more general knowledge to its students by enforcing the Hint Loss in shallower layers rather than only in deeper ones. We validate the performance of CDHD on CIFAR-100 for various tasks and compare it against the SOTA baseline for DFCIL, demonstrating our superiorities and thus constituting a new benchmark. © 2023 IEEE.

关键词： Distillation

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Research on Image Denoising Algorithm Based on Self-Supervised Learning

Research on Image Denoising Algorithm Based on Self-Supervis...

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robotics and Computer Vision (ICRCV), international conference on

作者： Weijie Lv Xiangyang Chen Mingyu Yang School of Computer Science and Engineering Wuhan Institute of Technolog Wuhan China

ISBN: (数字)9798331527426

ISBN: (纸本)9798331527433

In recent years, neural network models based on self-supervised learning have shown excellent performance in the field of image denoising. However, current denoising methods either rely on specific noise models or can only perform denoising tasks under specified noise distributions. Moreover, these network models often have a large number of parameters, leading to inefficient parameter usage. To address these issues, inspired by the traditional Partial Differential Equation (PDE) methods in image denoising, we attempted to combine Neural Ordinary Differential Equations (NODEs) with Convolutional Neural Networks (CNNs) to produce a neural network model with NODE-like properties. This was aimed at improving the parameter efficiency of the model. Additionally, we introduced a new architecture within the model, namely normalization equivariance, which enables existing neural network models to possess the property of normalization equivariance. Compared to models lacking this property, models with normalization equivariance often exhibit stronger generalization capabilities and robustness. Through comparative experiments conducted on artificially synthesized noise and noise from real-world colored images, the results indicate that our proposed method demonstrates remarkable denoising effects across different scenarios. It exhibits stronger generalization capabilities and restores most of the texture details within the original images.

关键词： Partial differential equations Noise Noise reduction Neural networks Self-supervised learning Ordinary differential equations Mathematical models Robustness Image restoration Image denoising

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HILO: A Large-Scale Heterogeneous Object Dataset for Benchmarking Robotic Grasping Approaches

HILO: A Large-Scale Heterogeneous Object Dataset for Benchma...

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international conference on Autonomous Robots and Agents, ICARA

作者： Xinchao Song Sean Banerjee Natasha Kholgade Banerjee Dept. of Computer Science Clarkson University Potsdam NY USA Dept. of Computer Science & Engineering Wright State University Dayton OH USA

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Robust object manipulation is essential for robotics applications in real-world environments, especially when handling diverse and complex everyday objects. To facilitate this research, we present HILO, a large-scale dataset of 253 real-world everyday objects and 288 diverse scenes. HILO bridges a crucial gap in existing manipulation datasets through its heterogeneity and dual-resolution approach, combining high-resolution individual object scans with low-resolution scans of cluttered scenes. This provides both the precise geometric data needed for grasp planning and realistic environmental context. The dataset's comprehensive representations enable rigorous benchmarking of robotic grasping algorithms. Our evaluation of three leading grasping algorithms-Contact-GraspNet, GraspNet Baseline, and DexNet 4.0-reveals critical trade-offs between grasp quantity and quality, demonstrating the dataset's value in advancing robotic grasping research. HILO's rich object diversity and dual-resolution methodology provide a foundation for developing more versatile robotic systems capable of reliable real-world robotic manipulation. Our dataset is available at https://***/hilo_dataset/.

关键词： Bridges automation Diversity reception Collaboration Grasping Benchmark testing Diversity methods Planning Reliability Robots

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A fast simulation method for magnetically driven deformation of a sheet micro soft robot 8

A fast simulation method for magnetically driven deformation...

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2022 8th international conference on Mechanical Engineering, Materials and automation Technology, MMEAT 2022

作者： Gao, Jian Rong, Weibin Gao, Peng Li, Dongjie Wang, Lefeng State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Heilongjiang Harbin150080 China

The magnetically driven micro soft robot is a hot research topic in the field of micro robotics. The magnetic torque of each part of the robot rotates with its deformation, so the magnetic torque and magnetic force to which the robot is subjected are difficult to be calculated directly. The lack of physical interfaces for torque distribution in many finite element software reduces the speed and accuracy of calculating the deformation of a robot using finite element simulation methods. In this paper, a fast simulation method to convert the local magnetic torque into equivalent load density for the deformation mode of the sheet micro soft robot is proposed. A finite element model of the fabricated micro soft robot is established, and the deformation and total magnetic moment of the robot under different magnetic field strength and magnetic field gradient are simulated and calculated. Experiments are executed to verify the validity of the simulation results. © Published under licence by IOP Publishing Ltd.

关键词： Robots

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Searching & Generating Discrete-Event Systems 18

Searching & Generating Discrete-Event Systems

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18th international conference on Informatics in Control, automation and robotics (ICINCO)

作者： Helliwell, T. J. Morgan, B. Mahfouf, M. Univ Sheffield Automat Control & Syst Engn Dept Sheffield S Yorkshire England Univ Shefeld Adv Mfg Res Ctr AVIRC Sheffield S Yorkshire England

ISBN: (纸本)9789897585227

In this paper we introduce a new method for the automatic generation and computer experimentation of Discrete-Event Systems (DES). We introduce the concept that DES descriptions may be used to define a searchable configuration space. Configuration instances in this space a represented as a permutation encoding which shows the number-of and types-of resources in a given configuration. Each instance is checked that the number of resources does not exceed a maximum and whether a fixed set of processes (a decomposed goal of uncertain time intervals drawn from a Gaussian distribution) can be logically completed on the given set of resources. If the permutation instance satisfies these constraints, it is subsequently constructed as a simulation model to quantify completion through global features of makespan and total processing time. We claim this is the basis for a powerful tool in high-level informed design of these types of systems that have hitherto avoided autonomous description or have been previously individually designed using time consuming manually defined programs.

关键词： Generative models Discrete-Event Systems Variable Structures Event Calculus Metaprogramming

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Universally Strict Black-Box Attacks Against Deep Neural Networks 8

Universally Strict Black-Box Attacks Against Deep Neural Net...

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8th international conference on Image, Vision and Computing, ICIVC 2023

作者： Lu, Zhengzhi Yang, Guoan School of Automation Science and Engineering Xi'An Jiaotong University Xi'an China

ISBN: (纸本)9798350335231

Adversarial attacks have demonstrated the vulnerability of deep neural networks (DNNs), which raises considerable security concerns. The existing attack methods require either prior knowledge of the victim DNNs and labels or frequent model querying. However, these requirements are usually infeasible or time-consuming, leading to suspicions about whether the attacks can be launched in real-world scenarios. To this end, we propose a universally strict black-box attack, which generates adversarial samples only using unlabeled data. It reduces the reliance on external information such as victim models, training processes, and ground-truth labels. Specifically, we first learn a latent manifold using contrastive learning. Then a novel universally adversarial loss is proposed to obtain adversaries directly in the latent space. It utilizes the dissimilarity between samples to craft perturbations without accessing labels and decision boundaries. Moreover, we propose a cluster selection for negative samples to improve the effectiveness of our attack. By evaluating the universally strict black-box attack against baseline models, we find it reaches an average fooling rate of 57.93%, which is on par with transfer-based black-box attacks. Our method shows the threats of adversarial attacks under more practical conditions and could serve as a new benchmark for assessing the robustness of DNNs. © 2023 IEEE.

关键词： Image classification

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The Concept and Means of Adaptive Shading 12

The Concept and Means of Adaptive Shading

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12th international conference on Advanced Computer Information Technologies, ACIT 2022

作者： Romanyuk, Olexandr Romanyuk, Oksana Chekhmestruk, Roman Mykhaylov, Pavlo Maidaniuk, Volodymyr Korobeinikova, Tetiana Vinnytsia National Technical University Faculty of Information Technologies and Computer Engineering Vinnytsia Ukraine 3D Generation Ua Vinnitsa Ukraine Ceo 3D Gneration GmbH Dortmund Germany Institute of Computer Technologies Automation and Metrology Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

In computer graphics systems during the formation of realistic images in most cases are used models of shading, which take into account the background, diffuse and specular components of color, which may be redundant and affect the time of formation of three-dimensional images. This is due to the fact that specular highlights on the surface of the object is on average about 10% of its total area, and therefore the use of computationally complex models for the whole object is impractical, as the use of simple and complex lighting models gives identical results for specular highlight zones. The concept of structural-adaptive shading is developed, which consists in preliminary analysis of the triangulation structure of a three-dimensional object with subsequent adaptive choice of lighting models and shading methods, and provides increased productivity of shading by removing redundant calculations that do not affect the quality. © 2022 IEEE.

关键词： Rendering (computer graphics)

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Developing an Agent-Based Simulation Model for Predicting Technology Acceptance at Border Crossing Points

Developing an Agent-Based Simulation Model for Predicting Te...

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international conference on Autonomous Robots and Agents, ICARA

作者： Sarang Shaikh Sule Yildirim Yayilgan Dept. of Information Security and Communication Technology Norwegian University of Science and Technology (NTNU) Gjovik Norway

In this paper, we are focusing on the use of agent-based approach to generate simulations of various scenarios for border crossing points and making technology acceptance predictions. This paper is related to the Horizon 2020 project METICOS 1 1 https://***/, for which we are extracting user (traveler and border control staff) perceptions from sources such as online social networks e.g., Twitter, Web, Interviews, Questionnaires etc. However, for the scope of this paper we have only included the synthetic data for the experiments to validate the proposed simulation model. The existing studies made a strong justification for choosing this approach to model the defined problem. To the best of our knowledge, this paper is a first research study focusing on defining how agent-based modeling and simulation can be used to model border crossing scenarios and predicting the acceptance of the border control technologies by explaining travelers' profile based on synthetic data, perceptions based on manual rules. This is important for stakeholders who take decisions related to what technologies to place at the border crossing points and what features such technologies should have to improve throughputs and traveler and border staff satisfaction.

关键词： Social networking (online) Focusing Manuals Predictive models Agent-based modeling Throughput Data models

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