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Bearing-Based Target Entrapping control of Multiple Uncertain Agents With Arbitrary Maneuvers

IFAC-PapersOnLine 2023年第2期56卷 8821-8826页

作者： Haifan Su Ziwen Yang Shanying Zhu Cailian Chen Wenbin Yu Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

This paper is concerned with bearing-based cooperative target entrapping control of multiple uncertain agents with arbitrary maneuvers including shape deformation, rotations, scalings, etc. A leader-follower structure is used, where the leaders move with the predesigned trajectories, and the followers are steered by an estimation-based control method, integrating a distance estimator using bearing measurements and a stress matrix-based formation controller. The signum functions are used to compensate for the uncertainties so that the agents’ accelerations can be piecewise continuous and bounded to track the desired dynamics. With proper design of the leaders’ trajectories and a geometric configuration, an affine matrix is determined so that the inter-agent relative bearings can be persistently exciting since the bearing rates are related to different weighted combinations of the affine matrix vectors. The asymptotic convergence of the estimation and control error is proved using Filipov properties and cascaded system theories. A sufficient condition for inter-agent collision avoidance is also proposed. Finally, simulation results are given to validate the effectiveness of the method.

关键词： Target entrapping control bearing measurement persistent excitation uncertainty

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Impact of Perception Errors in Vision-Based Detection and Tracking Pipelines on Pedestrian Trajectory Prediction in Autonomous Driving Systems

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Sensors 2024年第15期24卷 5066页

作者： Chen, Wen-Hui Wu, Jiann-Cherng Davydov, Yury Yeh, Wei-Chen Lin, Yu-Chen Graduate Institute of Automation Technology National Taipei University of Technology Taipei10608 Taiwan Department of Automatic Control Engineering Feng Chia University Taichung40724 Taiwan

Pedestrian trajectory prediction is crucial for developing collision avoidance algorithms in autonomous driving systems, aiming to predict the future movement of the detected pedestrians based on their past trajectories. The traditional methods for pedestrian trajectory prediction involve a sequence of tasks, including detection and tracking to gather the historical movement of the observed pedestrians. Consequently, the accuracy of trajectory prediction heavily relies on the accuracy of the detection and tracking models, making it susceptible to their performance. The prior research in trajectory prediction has mainly assessed the model performance using public datasets, which often overlook the errors originating from detection and tracking models. This oversight fails to capture the real-world scenario of inevitable detection and tracking inaccuracies. In this study, we investigate the cumulative effect of errors within integrated detection, tracking, and trajectory prediction pipelines. Through empirical analysis, we examine the errors introduced at each stage of the pipeline and assess their collective impact on the trajectory prediction accuracy. We evaluate these models across various custom datasets collected in Taiwan to provide a comprehensive assessment. Our analysis of the results derived from these integrated pipelines illuminates the significant influence of detection and tracking errors on downstream tasks, such as trajectory prediction and distance estimation. © 2024 by the authors.

关键词： Object detection

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Investigation of a Simulated Robot Model when it is Trained to Set Trajectories in the Task of controlling Assembly Parameters at Remote Visualization

Investigation of a Simulated Robot Model when it is Trained ...

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2022 International Russian automation Conference, RusAutoCon 2022

作者： Malkarov, A.Yu. Arkhipov, M.V. Kocherevskaya, L.B. Moscow Polytechnic University Faculty of Mechanical Engineering Department of Automation and Control Moscow Russia Moscow Aviation Institute National Research University Foreign Language Department for Aerospase Specialities Moscow Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

The science of robotics is becoming more and more relevant for industrial production. Visualization of the production system involves the exact modeling of its components as accurately as possible. For a robotic technological complex, such a main component is an industrial robot. The robot model should most accurately reflect what is happening in real production, since the robot is the basis of robotic production. Modeling allows you to perform a comprehensive analysis of the production system without direct design and start-up and, if possible, easily redesign it. An application was developed for building a virtual model of the robot and the workspace. An analysis of the behavior of the manipulator makes it possible to consistently improve the accuracy of modeling and the efficiency of designing a robotic technological complex. © 2022 IEEE.

关键词： Visualization

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Automatic Nonlinear MPC Approximation with Closed-loop Guarantees

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IEEE Transactions on Automatic control 2025年

作者： Tokmak, Abdullah Fiedler, Christian Zeilinger, Melanie N. Trimpe, Sebastian Kohler, Johannes Aalto University Department of Electrical Engineering and Automation Espoo02150 Finland RWTH Aachen University Institute for Data Science in Mechanical Engineering Aachen52068 Germany ETH Zurich Institute for Dynamic Systems and Control ZurichCH-8092 Switzerland

Safety guarantees are vital in many control applications, such as robotics. Model predictive control (MPC) provides a constructive framework for controlling safety-critical systems but is limited by its computational complexity. We address this problem by presenting a novel algorithm that automatically computes an explicit approximation to nonlinear MPC schemes while retaining closed-loop guarantees. Specifically, the problem can be reduced to a function approximation problem, which we then tackle by proposing Alkia-x, the Adaptive and Localized Kernel Interpolation Algorithm with eXtrapolated reproducing kernel Hilbert space norm. Alkia-x is a non-iterative algorithm that ensures well-conditioned computations, a fast-to-evaluate approximating function, and the guaranteed satisfaction of any desired bound on the approximation error. Hence, Alkia-x automatically computes an explicit function that approximates the MPC, yielding a controller suitable for safety-critical systems and high sampling rates. We apply Alkia-x to approximate two nonlinear MPC schemes, demonstrating reduced computational demand and applicability to realistic problems. © 1963-2012 IEEE.

关键词： Predictive control systems

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KN-LIO: Geometric Kinematics and Neural Field Coupled LiDAR-Inertial Odometry

arXiv

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arXiv 2025年

作者： Wang, Zhong Ren, Lele Wen, Yue Wang, Hesheng The Department of Automation School of Electronics Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China The School of Information and Control Engineering China University of Mining and Technology Xuzhou221008 China

Recent advancements in LiDAR-Inertial Odometry (LIO) have boosted a large amount of applications. However, traditional LIO systems tend to focus more on localization rather than mapping, with maps consisting mostly of sparse geometric elements, which is not ideal for downstream tasks. Recent emerging neural field technology has great potential in dense mapping, but pure LiDAR mapping is difficult to work on high-dynamic vehicles. To mitigate this challenge, we present a new solution that tightly couples geometric kinematics with neural fields to enhance simultaneous state estimation and dense mapping capabilities. We propose both semi-coupled and tightly coupled Kinematic-Neural LIO (KN-LIO) systems that leverage online SDF decoding and iterated error-state Kalman filtering to fuse laser and inertial data. Our KN-LIO minimizes information loss and improves accuracy in state estimation, while also accommodating asynchronous multi-LiDAR inputs. Evaluations on diverse high-dynamic datasets demonstrate that our KN-LIO achieves performance on par with or superior to existing state-of-the-art solutions in pose estimation and offers improved dense mapping accuracy over pure LiDAR-based methods. The relevant code and datasets will be made available at https://**. Copyright © 2025, The Authors. All rights reserved.

关键词： Mapping

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Reliability Models for a Safe Train Traffic control Systems Accounting the Railway Infrastructure States

Reliability Models for a Safe Train Traffic Control Systems ...

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2023 International Russian automation Conference, RusAutoCon 2023

作者： Efanov, Dmitrii V. Mikhailiuta, Evgenii M. Khoroshev, Valerii V. Peter the Great St. Petersburg Polytechnic University Higher School of Mechanical Engineering Material and Transport Institute in St. Petersburg St. Petersburg Russia Tashkent State Transport University "Automation and Remote Control"Department Tashkent Uzbekistan Russian University of Transport "Automation Remote Control and Communication on Railway Transport"Department Moscow Russia Higher School of Mechanical Engineering Material and Transport Institute in St. Petersburg Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350345551

The authors developed the advanced train traffic control system architecture. This architecture is based on the railway infrastructure facilities monitoring techniques integrated into the railway automation and remote-control equipment. Such system has a higher level of safety due to the transferring data about the infrastructure facilities state into control complexes directly without the "human - operator"link of the monitoring system. Data from infrastructure facilities that do not directly interact with railway automation equipment's make it possible to quickly develop control actions for the timely developing defects counteract. The authors developed reliability models for the train traffic control systems, in which the railway infrastructure facilities states are considered. Authors presents the accounting the infrastructure complex safe state relevance in train traffic control systems. The developed reliability models using are advisable in the safe train traffic control systems development, as well as in railway infrastructure facilities digital twins developing include real-time modeling of processes. © 2023 IEEE.

关键词： automation

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The fuzzy sliding mode control-based autonomous vehicle controller design

The fuzzy sliding mode control-based autonomous vehicle cont...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Xinxin Liu Xiaojie Su Jianxing Liu Department of Automation Nanjing University of Information Science and Technology Nanjing Department of Automation Chongqing University Chongqing Department of Control Science and Engineering Harbin Institute of Technology Harbin

Fuzzy control and sliding mode control technologies play an increasingly important role in a myriad of applications, like the autonomous vehicle systems. In this paper, the fuzzy model for the autonomous vehicle system with a dynamic positioning system is established firstly. Then the stability analysis and controller synthesis are provided, the solution method of the sliding mode control gain is synthesized. Finally, a simulation example provides evidence of the availability of the control strategy.

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Benefits and drawbacks of radiofrequency ablation via percutaneous or minimally invasive surgery for treating hepatocellular carcinoma

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World Journal of Gastrointestinal Surgery 2024年第11期16卷 3400-3407页

作者： Ching-Lung Hsieh Cheng-Ming Peng Chun-Wen Chen Chang-Hsien Liu Chih-Tao Teng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724Taiwan Department of Surgery Chung Shan Medical University HospitalTaichung 40201Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Department of Radiology Taichung Armed Forces General HospitalTaichung 406Taiwan Department of Medical Imaging and Radiological Sciences Central Taiwan University of Science and TechnologyTaichung 406Taiwan Department of Radiology School of MedicineNational Defense Medical CenterTaipei 11490Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital and China Medical UniversityHsinchu 302Taiwan Institute of Nuclear Engineering and Science National Tsing Hua UniversityHsinchu 300Taiwan Department of Radiology Nantou Hospital of the Ministry of Health and WelfareNantou 540Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia UniversityTaichung 407Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

The management of early stage hepatocellular carcinoma(HCC)presents significant *** radiofrequency ablation(RFA)has shown safety and effectiveness in treating HCC,with lower mortality rates and shorter hospital stays,its high recurrence rate remains a significant ***,achieving improved survival solely through RFA is challenging,particularly in retrospective studies with inherent *** is commonly used for guiding percutaneous RFA,but its low contrast can lead to missed tumors and the risk of HCC *** enhance the efficiency of ultrasound-guided percutaneous RFA,various techniques such as artificial ascites and contrast-enhanced ultrasound have been developed to facilitate complete tumor *** invasive surgery(MIS)offers advantages over open surgery and has gained traction in various surgical *** studies suggest that laparoscopic intraoperative RFA(IORFA)may be more effective than percutaneous RFA in terms of survival for HCC patients unsuitable for surgery,highlighting its ***,combining MIS-IORFA with these enhanced percutaneous RFA techniques may hold greater significance for HCC treatment using the MIS-IORFA *** article reviews liver resection and RFA in HCC treatment,comparing their merits and proposing a trajectory involving their combination in future therapy.

关键词： Percutaneous radiofrequency ablation Minimally invasive surgery Hepatocellular carcinoma Intraoperative radiofrequency ablation Contrast-enhanced ultrasound

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MFANet: Mixed Feature Attention Network for Port Lane Detection 42

MFANet: Mixed Feature Attention Network for Port Lane Detect...

引用

42nd Chinese control Conference, CCC 2023

作者： Zhang, Jinwei Su, Jinya Yi, Dewei Yang, Jun Ministry of Education The School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China University of Aberdeen Department of Computing Science AberdeenAB24 3UE United Kingdom

ISBN: (纸本)9789887581543

With the advancement of industrial automation and artificial intelligence technology, unmanned port autonomy has gained increasing attention. Port automatic driving technology is a critical component of unmanned autonomous systems, enabling rubber tire gantry cranes (RTGs) to autonomously navigate by detecting port lanes and implementing control commands. In this study, a deep learning-based method is proposed for detecting port lanes in complex port scenes. The method employs the Inception module and attention mechanism to enhance lane feature extraction, and a structural loss is introduced to explicitly constrain the detection results and incorporate the prior characteristics of port lanes. A novel Mixed Feature Attention Network (MFANet) is proposed to implement the method for port lane detection. Experimental results demonstrate that MFANet effectively improves the accuracy of port lane detection while maintaining high computational efficiency. Furthermore, the performance of MFANet is evaluated in a real-world application scenario. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Computational efficiency

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Distributed Optimization with Efficient Communication, Event-Triggered Solution Enhancement, and Operation Stopping

arXiv

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arXiv 2025年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Finland Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden Digital Futures United Kingdom

In modern large-scale systems with sensor networks and IoT devices it is essential to collaboratively solve complex problems while utilizing network resources efficiently. In our paper we present three distributed optimization algorithms that exhibit efficient communication among nodes. Our first algorithm presents a simple quantized averaged gradient procedure for distributed optimization, which is shown to converge to a neighborhood of the optimal solution. Our second algorithm incorporates a novel event-triggered refinement mechanism, which refines the utilized quantization level to enhance the precision of the estimated optimal solution. It enables nodes to terminate their operation according to predefined performance guarantees. Our third algorithm is tailored to operate in environments where each message consists of only a few bits. It incorporates a novel event-triggered mechanism for adjusting the quantizer basis and quantization level, allowing nodes to collaboratively decide operation termination based on predefined performance criteria. We analyze the three algorithms and establish their linear convergence. Finally, an application on distributed sensor fusion for target localization is used to demonstrate their favorable performance compared to existing algorithms in the literature. © 2025, CC BY.

关键词： Dynamic programming

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