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arXiv 2025年

作者： Jarosz, Anna Zagorowska, Marta Baranowski, Jerzy AGH University of Krakow Dept. of Automatic Control & Robotics al. Mickiewicza 30 Krakow30-059 Poland NTNU Department of Engineering Cybernetics Trondheim7034 Norway

Understanding degradation is crucial for ensuring the longevity and performance of materials, systems, and organisms. To illustrate the similarities across applications, this article provides a review of data-based method in materials science, engineering, and medicine. The methods analyzed in this paper include regression analysis, factor analysis, cluster analysis, Markov Chain Monte Carlo, Bayesian statistics, hidden Markov models, nonparametric Bayesian modeling of time series, supervised learning, and deep learning. The review provides an overview of degradation models, referencing books and methods, and includes detailed tables highlighting the applications and insights offered in medicine, power engineering, and material science. It also discusses the classification of methods, emphasizing statistical inference, dynamic prediction, machine learning, and hybrid modeling techniques. Overall, this review enhances understanding of degradation modelling across diverse domains. © 2025, CC BY-SA.

关键词： Hybrid materials

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A control Framework for a Robotic Endoscope Holder Based on Lightweight Foundational Segmentation Models

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical robotics and Bionics 2025年

作者： Zhou, Song Zhou, Chunlin Shi, Jinze Ma, Honghai He, Zhehao Wang, Luming Hu, Jian Zhejiang University College of Control Science and Engineering Hangzhou310000 China Zhejiang University Robotics Research Lab the College of Control Science and Engineering Hangzhou310000 China First Affiliated Hospital of Zhejiang University School of Medicine Department of Thoracic Surgery Hangzhou310000 China

Minimally Invasive Surgeries (MIS) present significant challenges due to the limited field of view (FOV), constrained motion range, and the reliance on manual endoscope operation, which can lead to fatigue and unstable imaging. Robotic-assisted endoscope systems address these issues by providing precise, stabilized positioning with constrained motion control. In this work, we propose a control framework for a robotic endoscope holder, incorporating a training-free method based on lightweight foundational segmentation models for surgical instrument localization, and a Quadratic Programming (QP) controller for motion planning under constraints. The framework ensures adherence to the Remote Center of Motion (RCM) constraint for patient safety, while image-based visual servoing enables real-time autonomous tracking of surgical instruments. The proposed method is validated using a 7-DOF Rokae Pro3 robotic arm with a rigid endoscope, achieving real-time performance with an RCM error consistently within 4.49 mm and smooth trajectory tracking. Experimental results demonstrate the framework’s effectiveness in addressing the challenges of constrained motion planning in MIS, enabling safe, precise, and autonomous endoscope positioning and instrument tracking. © 2018 IEEE.

关键词： Surgical equipment

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Modified Backstepping Algorithm with Disturbances Compensation for Nonlinear MIMO Systems ⁎

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IFAC-PapersOnLine 2020年第2期53卷 6012-6018页

作者： Dmitry E. Konovalov Sergey A. Vrazhevsky Igor B. Furtat Artem S. Kremlev Department of Control Systems and Industrial Robotics ITMO University The Laboratory ”Control of Complex Systems” Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences (IPME RAS)

The paper deals with a novel modified backstepping algorithm to ensure the stability of the nonlinear multiple-input multiple-output plant under unknown bounded parametric uncertainties, Lipschitz nonlinear disturbances, and cross-couplings. The modification is based on the auxiliary loop method that permits to estimate undesired dynamics as disturbances and suppress them. High robustness of the closed-loop system without using high-gain components is achieved. The ractical contribution of the results is demonstrated using laboratory platform ”Twin Rotor MIMO System”.

关键词： Backstepping recurcive procedure auxiliary loop method robust control nonlinear system MIMO systems output control parametric uncertainties external disturbances cross reactions

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Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion

Visual-Inertial and Leg Odometry Fusion for Dynamic Locomoti...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Victor Dhédin Haolong Li Shahram Khorshidi Lukas Mack Adithya Kumar Chinnakkonda Ravi Avadesh Meduri Paarth Shah Felix Grimminger Ludovic Righetti Majid Khadiv Joerg Stueckler Embodied Vision Group Max Planck Institute for Intelligent Systems Tuebingen Germany Movement Generation and Control Group Max Planck Institute for Intelligent Systems Tuebingen Germany Tandon School of Engineering New York University New York USA Oxford Robotics Institute University of Oxford England Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany

Implementing dynamic locomotion behaviors on legged robots requires a high-quality state estimation module. Especially when the motion includes flight phases, state-of-the-art approaches fail to produce reliable estimation of the robot posture, in particular base height. In this paper, we propose a novel approach for combining visual-inertial odometry (VIO) with leg odometry in an extended Kalman filter (EKF) based state estimator. The VIO module uses a stereo camera and IMU to yield low-drift 3D position and yaw orientation and drift-free pitch and roll orientation of the robot base link in the inertial frame. However, these values have a considerable amount of latency due to image processing and optimization, while the rate of update is quite low which is not suitable for low-level control. To reduce the latency, we predict the VIO state estimate at the rate of the IMU measurements of the VIO sensor. The EKF module uses the base pose and linear velocity predicted by VIO, fuses them further with a second high-rate IMU and leg odometry measurements, and produces robot state estimates with a high frequency and small latency suitable for control. We integrate this lightweight estimation framework with a nonlinear model predictive controller and show successful implementation of a set of agile locomotion behaviors, including trotting and jumping at varying horizontal speeds, on a torque-controlled quadruped robot.

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Optimized Space-Vector Modulation Schemes for Five-Phase Precision Low-Speed Drives with Minimizing the Stator Current Ripple

Optimized Space-Vector Modulation Schemes for Five-Phase Pre...

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Compatibility in Power Electronics (CPE)

作者： Valentin Tomasov Aleksander Usoltsev Denis Vertegel Pawel Szczepankowski Ryszard Strzelecki Nikolai Poliakov Department of Control Engineering and Robotics ITMO University St. Petersburg Russia Department of Electrical and Control Engineering Gdansk University of Technology Gdansk Poland

ISBN: (数字)9781728142180

ISBN: (纸本)9781728142197

One of the main ways to improve the quality of a precision electric drive is minimization of the stator current pulsations generated by the voltage inverter. The solution of this problem can be achieved by using of multiphase inverters, as well as improving control algorithms. This paper considers the influence of the space-vector modulation algorithm with different switching sequences of basic vectors on the stator current pulsations generated by the five-phase voltage inverter.

关键词： Modulation Inverters Stator windings Harmonic analysis Torque Switches

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Flexible MPC-based conflict resolution using online adaptive ADMM

arXiv

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arXiv 2021年

作者： An, Jerry Giordano, Giulia Liu, Changliu Robotics Institute Carnegie Mellon University Pittsburgh United States Delft Center for Systems and Control Delft University of Technology Delft Netherlands Department of Industrial Engineering University of Trento Italy

Decentralized conflict resolution for autonomous vehicles is needed in many places where a centralized method is not feasible, e.g., parking lots, rural roads, merge lanes, etc. However, existing methods generally do not fully utilize optimization in decentralized conflict resolution. We propose a decentralized conflict resolution method for autonomous vehicles based on a novel extension to the Alternating Directions Method of Multipliers (ADMM), called Online Adaptive ADMM (OA-ADMM), and on Model Predictive control (MPC). OA-ADMM is tailored to online systems, where fast and adaptive real-time optimization is crucial, and allows the use of safety information about the physical system to improve safety in real-time control. We prove convergence in the static case and give requirements for online convergence. Combining OA-ADMM and MPC allows for robust decentralized motion planning and control that seamlessly integrates decentralized conflict resolution. The effectiveness of our proposed method is shown through simulations in CARLA, an open-source vehicle simulator, resulting in a reduction of 47.93% in mean added delay compared with the next best method. © 2021, CC BY-NC-ND.

关键词： Model predictive control

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State Observation of Affine-in-the-States Systems with Unknown Time-Varying Parameters and Output Delay

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IFAC-PapersOnLine 2022年第12期55卷 341-346页

作者： Alexey Bobtsov Nikolay Nikolaev Romeo Ortega Denis Efimov Olga Kozachek Department of Control Systems and Robotics ITMO University Kronverkskiy av. 49 Saint-Petersburg 197101 Russia Departamento Académico de Sistemas Digitales ITAM Ciudad de México México INRIA Univ. Lille CNRS UMR 9189 - CRIStAL F-59000 Lille France Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia

In this paper we address the problem of adaptive state observation of affine-in-the-states time-varying systems with delayed measurements and unknown parameters. The development of the results proposed in the [Bobtsov et al. 2021a] and in the [Bobtsov et al. 2021c] is considered. The case with known parameters has been studied by many researchers—see [Sanz et al. 2019, Bobtsov et al. 2021b] and references therein—where, similarly to the approach adopted here, the system is treated as a linear time-varying system. We show that the parameter estimation-based observer (PEBO) design proposed in [Ortega et al. 2015, 2021] provides a very simple solution for the unknown parameter case. Moreover, when PEBO is combined with the dynamic regressor extension and mixing (DREM) estimation technique [Aranovskiy et al. 2016, Ortega et al. 2019], the estimated state converges in fixed-time with extremely weak excitation assumptions.

关键词： Nonlinear time-varying systems state observer delay systems parameter estimation

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Defect Sample Generation System Based on DCGAN for Glass Package Electrical Connectors

Defect Sample Generation System Based on DCGAN for Glass Pac...

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Chinese Intelligent Systems Conference, CISC 2020

作者： Liu, Qunpo Wang, Mengke Hanajima, Naohiko Department of Robotics Engineering Henan Polytechnic University 2001 Century Avenue JiaozuoHenan454003 China Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment 2001 Century Avenue JiaozuoHenan454003 China College of Information and Systems Muroran Institute of Technology 27-1 Mizumoto-cho Muroran-shiHokkaido050-8585 Japan

ISBN: (纸本)9789811584572

Precision glass packaged electrical connectors are widely used to connect precision modular electrical appliances. Manual detection is currently used due to its small size. In order to improve the detection efficiency and accuracy, deep learning is applied to the automatic detection of the defect. In this paper, in order to solve the problem of lack of defect samples, a defect sample generation system for micro-precision glass package electrical connectors based on deep convolutional generation confrontation network (DCGAN) is constructed. A network model of defect samples based on DCGAN is constructed, and algorithm design, parameter settings, network training and experiments are performed. More than 1,500 samples were generated. Finally, the generated samples were tested for defects (including missing blocks and bubbles). The results show that the samples generated by this method can be used as real samples in defect detection training. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Defects

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Gradient-tracking over directed graphs for solving leaderless multi-cluster games

arXiv

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arXiv 2021年

作者： Zimmermann, Jan Tatarenko, Tatiana Willert, Volker Adamy, Jürgen Control Methods and Robotics Lab Department of Electrical Engineering and Information Science Technical University of Darmstadt Darmstadt64283 Germany Faculty of Electrical Engineering University of Applied Sciences Würzburg-Schweinfurt Schweinfurt97421 Germany

We are concerned with finding Nash Equilibria in agent-based multi-cluster games, where agents are separated into distinct clusters. While the agents inside each cluster collaborate to achieve a common goal, the clusters are considered to be virtual players that compete against each other in a non-cooperative game with respect to a coupled cost function. In such scenarios, the inner-cluster problem and the game between the clusters need to be solved simultaneously. Therefore, the resulting inter-cluster Nash Equilibrium should also be a minimizer of the social welfare problem inside the clusters. In this work, this setup is cast as a distributed optimization problem with sparse state information. Hence, critical information, such as the agent’s cost functions, remain private. We present a distributed algorithm that converges with a linear rate to the optimal solution. Furthermore, we apply our algorithm to an extended cournot game to verify our theoretical results. © 2021, CC BY.

关键词： Game theory

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Evaluation of Robustness Metrics for Defense of Machine Learning Systems

Evaluation of Robustness Metrics for Defense of Machine Lear...

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International Conference on Military Communications and Information Systems (ICMCIS)

作者： J. DeMarchi R. Rijken J. Melrose B. Madahar G. Fumera F. Roli E. Ledda M. Aktaş F. Kurth P. Baggenstoss B. Pelzer L. Kanestad Collaborative Engineering Systems & Aerospace Systems Information Supremacy Royal Netherlands Aerospace Centre NLR Amsterdam NLD Cyber & Information Systems Division Defence Science and Technology Laboratory Portondown GBR Department of Electrical and Electronic Engineering University of Cagliari Cagliari ITA Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa ITA Department of Computer Control and Management Engineering Sapienza University of Rome Rome ITA Defence Systems Technologies Division ASELSAN Ankara TUR Fraunhofer Institute for Communication Information Processing and Ergonomics Bonn DEU Swedish Defence Research Agency Cyber Defence and C2 Technology Division Stockholm SWE

In this paper we explore some of the potential applications of robustness criteria for machine learning (ML) systems by way of tangible “demonstrator” scenarios. In each demonstrator, ML robustness metrics are applied to real-world scenarios with military relevance, indicating how they might be used to help detect and handle possible adversarial attacks on ML systems. We conclude by sketching promising future avenues of research in order to: (1) help establish useful verification methodologies to facilitate ML robustness compliance assessment; (2) support development of ML accountability mechanisms; and (3) reliably detect, repel, and mitigate adversarial attack.

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