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Coalition formation problem: a capability-centric analysis and general model

Science China(information Sciences) 2024年第11期67卷 180-193页

作者： Jie CHEN Miao GUO Bin XIN Qing WANG Shengyu LU Yipeng WANG Yulong DING School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering Tongji University

Coalition formation(CF) refers to reasonably organizing robots and/or humans to form coalitions that can satisfy mission requirements, attracting more and more attention in many fields such as multirobot collaboration and human-robot collaboration. However, the analysis on CF problems remains *** provide a valuable study reference for researchers interested in CF, this paper proposed a capabilitycentric analysis of the CF problem. The key problem elements of CF are firstly extracted by referencing the concepts of the 5W1H method. That is, objects(who) form coalitions(what) to accomplish missions(why) by aggregating capabilities(how) in a specific environment(where-when). Then, a multi-view analysis of these elements and their correlation in terms of capabilities is proposed through various logic diagrams, structure charts, etc. Finally, to facilitate a deeper understanding of capability-centric CF, a general mathematical model is constructed, demonstrating how the different concepts discussed in this analysis contribute to the overall model.

关键词： coalition formation capability aggregation capability metric mission requirement environmental effect

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Data-driven output regulation control for constrained linear systems

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Science China(information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Sampled-data-based synchronization of complex networks under scaling attacks

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Mathematical Methods in the Applied Sciences 2024年第18期47卷 14487-14504页

作者： Murugesan, Sathishkumar Ishizaki, Takayuki Liu, Yen-Chen Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan Department of Mechanical Engineering National Cheng Kung University Tainan Taiwan

In this study, our main objective is to address the issue of sampled-data-based synchronization of complex networks subjected to stochastic scaling attacks using a looped-functional approach. To begin with, the design of a Lyapunov functional, which involves tuning parameters and slack variables, considers the error state information of (Formula presented.) and (Formula presented.). Then, the scaling attack is a type of deception attack that is formulated using an interval matrix approach. In addition, the complex networks considered in this study incorporate uncertain inner coupling strengths, which are more general than the existing ones, owing to the presence of uncertainties in the coupling strengths. Using a looped-functional approach to construct an appropriate Lyapunov–Krasovskii functional, we derive a set of sufficient conditions to achieve mean-square asymptotic synchronization for considered complex networks under scaling attacks. In the end, the proposed results are illustrated using three examples, including a practical example that highlights their effectiveness and superiority. © 2024 John Wiley & Sons Ltd.

关键词： Synchronization

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Multi-Lens Visual SLAM with Integrated Moving Object Removal using Unsupervised Models 1

Multi-Lens Visual SLAM with Integrated Moving Object Removal...

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1st International Conference on Robotics, engineering, Science, and technology, RESTCON 2024

作者： Hara, Ryoichirou Matsushima, Kousuke Kurume College Advanced Engineering Course National Institute of Technology Fukuoka Japan Kurume College National Institute of Technology Department of Control and Information Systems Engineering Fukuoka Japan

ISBN: (纸本)9798350348842

In Advanced Driver-Assistance systems (ADAS), SLAM (Simultaneous Localization and Mapping) technology is required to accurately estimate the position and orientation of onboard cameras. Compared to LiDAR SLAM, Visual SLAM has the advantage of collecting rich environmental information at a lower cost. However, the accuracy of the estimated pose and map construction is greatly reduced by moving objects in the camera scene. To solve this problem, a multi-camera SLAM has been proposed, which works robustly in dynamic environments by using multiple cameras to acquire more feature points from omnidirectional environmental information. In this paper, we propose a robust SLAM system based on a multi-camera SLAM system combined with object detection and semantic segmentation networks. We then evaluate the robustness of the proposed method by comparing it to SLAM systems that do not remove moving objects. Experimental results showed that the Absolute Trajectory Error and the Relative Position Error performed better than conventional SLAM by masking moving objects. It also showed that more static objects were detected and constructed in the map. © 2024 IEEE.

关键词： Object detection

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Solving PnP Problem Using Improved Sparrow Search Algorithm

Solving PnP Problem Using Improved Sparrow Search Algorithm

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2024 International Symposium on Intelligent Signal Processing and Communication systems, ISPACS 2024

作者： Riku, Kurihara Matsushima, Kousuke Advanced Engineering Course National Institute of Technology Kurume College Kurume Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Kurume Japan

ISBN: (纸本)9798350389210

The Perspective-n-Point (PnP) problem is a fundamental challenge in engineering that plays a crucial role in fields such as computer vision and augmented reality. This problem aims to estimate the position and orientation (pose) of a camera from known 3D points and their corresponding 2D projections on the image plane. With recent technological advancements, application areas such as autonomous vehicles, drones, and robotics are demanding increasingly faster and more accurate camera pose estimation. To address this challenge, we have introduced an improved Sparrow Search Algorithm (SSA) with the capability to dynamically restrict the search area. While the conventional SSA demonstrated excellent optimization capabilities, it faced efficiency issues when searching in high-dimensional spaces, such as those encountered in PnP problems. Our enhancement enables the algorithm to leverage information obtained during the search process to gradually narrow down the search area, thereby more efficiently locating the optimal solution. © 2024 IEEE.

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Mobile Generalized Category Discovery for Road Damage Detection

Mobile Generalized Category Discovery for Road Damage Detect...

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2024 International Symposium on Intelligent Signal Processing and Communication systems, ISPACS 2024

作者： Rintaro, Akashi Matsushima, Kousuke Advanced Engineering Course National Institute of Technology Kurume College Kurume Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Kurume Japan

ISBN: (纸本)9798350389210

In recent years, there has been a considerable amount of research conducted on the topic of road damage detection using deep learning techniques, with the aim of supporting the safe driving of mobility vehicles. To date, convolutional neural networks and supervised learning with large datasets have been employed for road damage detection, demonstrating high classification accuracy. However, all images in the dataset must be manually labeled. Moreover, images cannot be classified into classes that are not included in the training dataset. The real world presents a vast array of damage types, and the unlabeled input images encompass both known and unknown classes. This renders the system unsuitable for use in providing safe driving support for mobility. Considering this background, Generalized Category Discovery (GCD) has been put forth as a potential solution, aiming to achieve accurate classification in a comprehensive setting where both known and unknown classes are present in unlabeled data. The purpose of this study is to propose a novel model for GCD with the aim of providing safe driving assistance for mobility. The model is based on the pre-trained MobileViT. To validate its performance, this paper examines its performance on the general CIFAR-10 and CIFAR-100 datasets and on a road damage-specific dataset, and discusses the challenges encountered. © 2024 IEEE.

关键词： Convolutional neural networks

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Uncertainty-aware Monocular 3D Object Detection for Safe Driving Assistance

Uncertainty-aware Monocular 3D Object Detection for Safe Dri...

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2024 International Symposium on Intelligent Signal Processing and Communication systems, ISPACS 2024

作者： Ida, Masahiko Matsushima, Kousuke Advanced Engineering Course National Institute of Technology Kurume College Fukuoka Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (纸本)9798350389210

Safety is of utmost importance when utilizing mobile vehicles. The introduction of safe driver assistance and automated driving systems will not only solve this problem, but also reduce road accidents and make driving smoother. To achieve these goals, 3D object detection is an essential technology and various methods have been proposed. Among these, monocular 3D object detection is an important technique and it is very difficult to identify the dimensions, direction and position of an object from a monocular image. Previous methods have predicted the dimensions directly from monocular images, resulting in poor accuracy of the dimensions in the depth direction. However, this paper proposes an indirect method for estimating the dimensions in the depth direction by predicting the volume of 3D bounding box. Detection accuracy for distant and partially visible objects is improved by using a loss function that uses uncertainty to account for the variability in predictions that occurs during learning. The proposed method has received an excellent evaluation on KITTI dataset. © 2024 IEEE.

关键词： 3D modeling

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Event-triggered consensus control of heterogeneous multi-agent systems: model-and data-based approaches

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Science China(information Sciences) 2023年第9期66卷 151-167页

作者： Xin WANG Jian SUN Fang DENG Gang WANG Jie CHEN School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This article addresses the model-and data-based event-triggered consensus of heterogeneous leader/follower multi-agent systems(MASs). A dynamic periodic transmission protocol is developed to alleviate the communication and computational burden, where the followers can interact locally with neighbors to approach the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived as linear matrix inequalities(LMIs), along with a design method for obtaining distributed event-triggered controllers and the associated triggering *** collecting noise-corrupted state-input measurements in offline open-loop experiments, a data-based leader/follower MAS representation is derived and employed to address the data-driven consensus control problem without explicit MAS models. This result is subsequently generalized to guarantee an H∞-consensus control performance. Finally, a simulation example is given to corroborate the efficiency of the proposed distributed triggering scheme and the data-driven consensus controller.

关键词： data-driven control multi-agent system consensus looped-functional LMI

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Resilient annular finite-time synchronization for master-slave systems under scaling attacks

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IET control Theory and Applications 2023年第18期17卷 2458-2473页

This paper investigates the resilient annular finite-time synchronization and boundedness problems for master-slave systems under dynamic event-triggered scheme (ETS), actuator faults, and scaling attacks. A comprehensive model for characterizing scaling attacks is presented. The switched dynamic ETS is developed to reduce the bandwidth pressure. Two different internal variables are designed, each of which changes based on the switching manifold. Simultaneously, the resilient problem of switched master-slave systems with respect to stochastic scaling attacks is considered, where there are limited malicious signals introduced by the adversary. Based on the Lyapunov-like function involving the different internal dynamic variables, a set of criteria is established in the form of linear matrix inequalities (LMIs), which guarantee the annular finite-time boundedness. Finally, two examples are presented to verify the theoretical findings. © 2023 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Linear matrix inequalities

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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