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arXiv 2025年

作者： de Heij, Vincent Niazi, M.B. Umar Johansson, Karl H. Ahmed, Saeed Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

This paper proposes a distributed prescribed-time observer for nonlinear systems representable in a block-triangular observable canonical form. Using a weighted average of neighbor estimates exchanged over a strongly connected digraph, each observer estimates the system state despite the limited observability of local sensor measurements. The proposed design guarantees that distributed state estimation errors converge to zero at a user-specified convergence time, irrespective of observers’ initial conditions. To achieve this prescribed-time convergence, distributed observers implement time-varying local output injection gains that monotonically increase and approach infinity at the prescribed time. The theoretical convergence is rigorously proven and validated through numerical simulations, where some implementation issues due to increasing gains have also been clarified. Copyright © 2025, The Authors. All rights reserved.

关键词： Digital arithmetic

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Abstraction-Based Synthesis of controllers for Approximate Opacity

Abstraction-Based Synthesis of Controllers for Approximate O...

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IEEE Conference on Decision and control

作者： Junyao Hou Siyuan Liu Xiang Yin Majid Zamani Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science University of Colorado Boulder CO USA Department of Computer Science LMU Munich Munich Germany

Opacity is an important information-flow security property which characterizes the plausible deniability of certain “secret behaviors” in dynamical systems. In this paper, we study the problem of synthesizing controllers enforcing a notion of opacity over discrete-time control systems with continuous state sets. In this paper, we develop an abstraction-based approach to tackle the controller synthesis problem. Specifically, we adopt a notion of approximate opacity which is suitable for continuous-space control systems. We propose a notion of approximate initial-state opacity preserving alternating simulation relation which characterizes the closeness between two systems in terms of opacity preservation. We show that, based on this new notion of system relation, one can synthesize an opacity-enforcing controller for the abstract system which is finite and then refine it back to enforce opacity over the original control system. Finally, we present a method for constructing opacity-preserving finite abstractions for discrete-time control systems under some stability properties. Our results are illustrated on a two-room temperature control problem.

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Benchmarking Semantic Communications for Image Transmission Over MIMO Interference Channels

arXiv

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arXiv 2024年

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong Key Laboratory of Wireless Communication Technologies Shandong University Jinan250061 China The School of Computer Science and Technology Qilu University of Technology Jinan250353 China The Communication Systems Department EURECOM Sophia Antipolis 06410 France

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-to-noise (SNR) regimes. © 2024, CC BY.

关键词： Channel state information

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Asymmetry of the Relative Entropy in the Regularization of Empirical Risk Minimization

arXiv

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arXiv 2024年

作者： Daunas, Francisco Esnaola, Iñaki Perlaza, Samir M. Vincent Poor, H. The Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom INRIA Centre Inria d'Université Côte d'Azur Sophia Antipolis06902 France The Department of Automatic Control and Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States The GAATI Mathematics Laboratory University of French Polynesia Fa'a'ā98702 French Polynesia

The effect of relative entropy asymmetry is analyzed in the context of empirical risk minimization (ERM) with relative entropy regularization (ERM-RER). Two regularizations are considered: (a) the relative entropy of the measure to be optimized with respect to a reference measure (Type-I ERM-RER);or (b) the relative entropy of the reference measure with respect to the measure to be optimized (Type-II ERM-RER). The main result is the characterization of the solution to the Type-II ERM-RER problem and its key properties. By comparing the well-understood Type-I ERM-RER with Type-II ERM-RER, the effects of entropy asymmetry are highlighted. The analysis shows that in both cases, regularization by relative entropy forces the solution's support to collapse into the support of the reference measure, introducing a strong inductive bias that can overshadow the evidence provided by the training data. Finally, it is shown that Type-II regularization is equivalent to Type-I regularization with an appropriate transformation of the empirical risk function. © 2024, CC BY.

关键词： Risk assessment

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DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network

DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatia...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Shaokun Zhang Xinde Li Chuanfei Hu Jianping Xu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Science and Technology on Information Systems Engineering Laboratory Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Recent transformer-based methods for estimating 3D human pose have gained widespread attention, achieving state-of-the-art results. Previous methods have primarily focused on capturing motion patterns of the human body at a single scale or cascading multiple scales, such as joints, bones, and body-parts. However, they are difficult to simultaneously capture spatial-temporal motion patterns of the human body at different scales due to the complex motion patterns. To address this issue, we propose Dual-scale Spatial and Temporal transFormer (DSTFormer), which can concurrently explore the spatial dependencies and temporal motion patterns of human joints and bones. Additionally, we introduce a Gcn-Spatial Transformer Block (GSTB), which introduces Graph Convolutional Networks (GCN) into transformer to enhance the exploitation of local relationships and global information between adjacent joints or bones. Extensive experiments are conducted on the Human3.6M benchmark dataset, and superior results are reported when comparing to other state-of-the-art methods. More remarkably, our model achieves to-date the best published performance, with P1 errors of 37.9 mm and 15.6 mm, respectively.

关键词： Solid modeling Three-dimensional displays Mechatronics Graph convolutional networks Computational modeling Pose estimation Transformers Bones Joints Robots

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Algorithm for Path Planning of Mobile Robot 24

Algorithm for Path Planning of Mobile Robot

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24th International Conference on Soft Computing and Measurements, SCM 2021

作者： Das, Nimai Chandra Uddin, Raihan Haque Zim, Md. Ziaul Skakun, Anastasiia D. Department of Automatic Control Systems Saint-Petersburg Electrotechnical University Leti Saint Petersburg Russia Daffodil International University Department of Software Engineering Dhaka Bangladesh Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665439749

Research in Unmanned Surface Vehicles (USVs) and Autonomous Mobile Robots navigation has demonstrated some success in navigating flat indoor environments while avoiding obstacles. But in common resilience to unsafe conditions, unmanned surface vehicles (USVs) and autonomous mobile robots have wide applications in security reconnaissance, investigation of an obscure domain, and crisis reaction. Various examinations have been directed on the driving mechanism, motion planning, and trajectory tracking strategies for robots, yet restricted investigations have been led with respect to the obstacle detection and avoiding ability of robots. However, for little scale robots that contain sensitive surveillance sensors and can't afford to utilize heavy defensive shells, the nonappearance of obstacle avoidance solutions arrangements would leave the robot helpless before possibly risky hindrances. In this paper, we present an algorithm for obstacle detection and avoidance system has been developed for miniature Unmanned Surface Vehicles (USVs) and autonomous mobile robots. We show an investigation differentiating heading build rules and relative course directions dodging distinctive operators in multi-specialist conditions, estimating separation between the two robots. The integration of distance measurement and avoiding other robots or obstacles is our observation in a multi-robot environment, where obstacles are also available. In this paper, we have discussed two algorithms, one will try to avoid other robot or obstacles and another will try to measure the distance between main agents to another agent. It utilizes an algorithm so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle. Therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance

关键词： Multi agent systems

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Research on Path Planning Algorithm Based on D* Search

Research on Path Planning Algorithm Based on D* Search

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Ocean Studies (ICOS), International Conference on

作者： Jiajun Leng Li Fu Lingling Wang Ning Tang Laboratory of Science and Technology on Marine Navigation and Control China State Shipbuilding Corporation Beijing 100036 China Tianjin Navigation Instruments Research Institute Tianjin China School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Automatic control systems Bauman Moscow State Technical University Moscow Russia

Path planning algorithms are current research hotspots. Heuristic algorithms that can solve dynamic environment problems are gradually becoming the mainstream research direction. The D* algorithm, as one of the new heuristic algorithms, has the advantages of being more computationally efficient than the A * algorithm and being able to solve dynamic problems, and has played an important role in two-dimensional path planning projects such as the NASA Mars rover. But its theoretical research and practical application in 3D environment are very rare. In this context, this paper carries out an in-depth study of the path planning problem based on the D* algorithm, and completes the theoretical derivation and simulation process in 2D and 3D environments. In this paper, a complex random 2D map is established by random generation, and the simulation of D* algorithm is realized on the map with the help of Python language, which realizes the finding of the relative optimal path. Then, in order to study the feasibility of D* solving in 3D environment, the simulation of D* algorithm under 3D map is realized with the help of Python and Unity3d. The research results show that the simulation results are good, which is valuable for the theoretical research and practical application of heuristic algorithms, and plays a role in the application of robot path planning algorithms.

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Critical Analysis and Evaluation of Current Digital Healthcare Solutions 23

Critical Analysis and Evaluation of Current Digital Healthca...

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23rd International Conference on control systems and computer science Technologies, CSCS 2021

作者： Ianculescu, Marilena Alexandru, Adriana Pop, Florin Systems and Applications for Society Department National Institute for RandD in Informatics Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Department of Computer Science and Engineering University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665439398

Digitalization of health, healthcare and healthcare delivery unequivocal have positive consequences contributing to health system goals, but they also might have some negative ones which have to be avoided or mitigated. The scope of this paper is to introduce the necessity of the assessment of Health Technology Assessment (HTA) and to identify the most appropriate and important criteria needed for the evaluation and comparison of functional digital healthcare solutions. It aims to outline consistent criteria against which digital health technologies and services can be evaluated during the prototyping phase, but also during long-term operation. © 2021 IEEE.

关键词： Health care

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Adapting Human Mesh Recovery with Vision-Language Feedback

arXiv

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arXiv 2025年

作者： Xu, Chongyang Huang, Buzhen Zhang, Chengfang Feng, Ziliang Wang, Yangang College of Computer Science Sichuan University Chengdu610065 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The School of Automation Southeast University Nanjing210096 China Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College Luzhou646000 China

Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image alignment due to the lack of explicit 2D-3D correspondences. In contrast, optimization-based methods align 3D models to 2D observations but are prone to local minima and depth ambiguity. In this work, we leverage large vision-language models (VLMs) to generate interactive body part descriptions, which serve as implicit constraints to enhance 3D perception and limit the optimization space. Specifically, we formulate monocular human mesh recovery as a distribution adaptation task by integrating both 2D observations and language descriptions. To bridge the gap between text and 3D pose signals, we first train a text encoder and a pose VQ-VAE, aligning texts to body poses in a shared latent space using contrastive learning. Subsequently, we employ a diffusion-based framework to refine the initial parameters guided by gradients derived from both 2D observations and text descriptions. Finally, the model can produce poses with accurate 3D perception and image consistency. Experimental results on multiple benchmarks validate its effectiveness. The code will be made publicly available. © 2025, CC BY.

关键词： Mesh generation

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Continual Learning of a Time Series Model Using a Mixture of HMMs with Application to the IoT Fuel Sensor Verification

Continual Learning of a Time Series Model Using a Mixture of...

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Federated Conference on computer science and Information systems (FedCSIS)

作者： Przemysław Głomb Michał Cholewa Paweł Foszner Jakub Bularz Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland AIUT Sp. z o.o. ul Gliwice Poland

This paper presents an application of a mixture of Hidden Markov Models (HMMs) as a tool for verification of IoT fuel sensors. The IoT fuel sensors report the level of fuel in tanks of a petrol station, and are a key component for monitoring system reliability (billing), safety (fuel/oil leak detection) and security (theft prevention). We propose an algorithm for learning a mixture of HMMs based on a continual learning principle, i.e. it adapts the model while monitoring a sensor over time, signalling unexpected or anomalous sensor reports. We have tested the proposed approach on a real-life data of 15 fuel tanks being monitored with the FuelPrime system, where it has shown a very good performance (average area under ROC curve of 0.94) of detecting anomalies in the sensor data. Additionally we show that the proposed method can be used for trend monitoring and present qualitative analysis of the short and long term learning performance. The proposed method has promising performance score, the resulting model has a high degree of explainability, limited memory and computation requirements and can be easily generalized to other domains of sensor verification.

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