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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

共 5310 条记录，以下是311-320 订阅

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Stochastic Error Bounds in Nonlinear Model Predictive control with Gaussian Processes via Parameter-Varying Embeddings

Stochastic Error Bounds in Nonlinear Model Predictive Contro...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Dimitrios S. Karachalios Hossam S. Abbas Institute for Electrical Engineering in Medicine University of Luebeck Germany Department of Electrical and Information Engineering Faculty of Engineering Kiel University Germany

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

this study utilized the Gaussian Processes (GPs) regression framework to establish stochastic error bounds between nonlinear systems' actual and predicted state evolution. these systems are embedded in the linear parameter-varying (LPV) formulation and controlled using model predictive control (MPC). Our primary focus is quantifying the uncertainty of the LPVMPC framework's forward error resulting from scheduling signal estimation mismatch. We compared our stochastic approach with a recent deterministic approach and observed improvements in conservatism and robustness. To validate our analysis and method, we solved the regulator problem of an unbalanced disk.

关键词： Uncertainty Regulators Measurement uncertainty Gaussian processes Robustness Regulation Stability analysis Trajectory Noise measurement Predictive control

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Job Shop Scheduling Under Time-of-Use Electricity Prices

Job Shop Scheduling Under Time-of-Use Electricity Prices

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Jingwei Dai Yaowen Yu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Job shop scheduling is an important problem in the operations of manufacturing systems and has great potential for improving electricity efficiency. this paper studies an energy-aware job shop scheduling problem that aims to minimize the total energy cost and total weighted tardiness by selecting an optimal job schedule, considering operation and other constraints. To efficiently model operation constraints and to consider different machine types, a new set of linear integer constraints is developed. the energy-aware job shop scheduling problem considering time-of-use (TOU) electricity prices is then formulated as a mixed-integer linear programming (MILP) problem and solved using the branch-and-cut method. Numerical results tested against three examples demonstrate the computational efficiency and solution quality of our method.

关键词： Schedules Electric potential Job shop scheduling Costs Electricity Computational modeling Numerical models Mixed integer linear programming Robots Manufacturing systems

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Design of Autonomous Fire Hose Docking System for Intelligent Fire-Fighting Robots 5

Design of Autonomous Fire Hose Docking System for Intelligen...

引用

5th international conference on robotics, Intelligent control and Artificial Intelligence, RICAI 2023

作者： Yang, Zhiwei Zhang, Fei Shang, Weiwei Chaoxia, Chenyu University of Science and Technology of China Department of Automation Hefei China

ISBN: (纸本)9798350357950

Although existing fire-fighting robots have been able to extinguish fires, the docking task of fire hoses has always been the key obstacle to achieving autonomous fire extinguishing functions for fire-fighting robots. therefore, it is crucial to enable robots to autonomously dock fire hoses to fire hydrants. To solve this problem, we design a new multi-DOF docking mechanism and develop a vision-guided autonomous fire hose docking system based on a robot operating system. When the robot detects the fire, the camera mounted on it can guide the docking system to complete the docking of the fire hose, laying the foundation for the robot to achieve autonomous fire extinguishing. © 2023 IEEE.

关键词： Camera vision Fire Hose Docking Intelligent Fire-fighting Robot

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Resilient Consensus for Heterogeneous Networks Under Byzantine Attacks

Resilient Consensus for Heterogeneous Networks Under Byzanti...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Jie Jiang Mingde Huang Yiming Wu School of Cyberspace at Hangzhou Dianzi University

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

this paper investigates the consensus problem of multi-agent systems in heterogeneous networks against Byzantine attacks. Heterogeneous networks consist of different subsystems, and existing resilient consensus controllers for heterogeneous networks require specifying specific protocols for each subsystem, with no possibility for interaction between agents in different subsystems. In this study, we present a novel framework, based on hypergraph theory, for representing the complex connections within heterogeneous networks. these networks consist of diverse subsystems, including both discrete and continuous components, and also involve diverse update strategies. Based on the network model, a unified distributed resilient consensus protocol based on Weighted-Mean-Subsequence-Reduced (W-MSR) algorithm is developed and network connectivity conditions are provided in the presence of Byzantine attacks. Finally, the simulation results demonstrate the effectiveness of the proposed algorithm and support the main theoretical findings.

关键词： automation Simulation Delay effects Heterogeneous networks Consensus protocol Robots Multi-agent systems Convergence

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Inducing Social Perceptions of a Mobile Robot for Human-Aware Navigation

Inducing Social Perceptions of a Mobile Robot for Human-Awar...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Philip Scales Véronique Aubergé Olivier Aycard Univ. Grenoble Alpes CNRS Grenoble INP LIG Grenoble France GIPSA-Lab Olivier Aycard is with Univ. Grenoble Alpes CNRS Grenoble INP Grenoble France

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Human-aware navigation and Social Navigation are growing fields of robotics, attempting to tackle challenging navigation problems in human environments. One difficult aspect is understanding how a mobile robot's navigation behavior impacts the way they are perceived by humans, and how they interact together. In our previous work, we proposed an adaptable navigation architecture. In this paper, we describe how we determine which motion variables should be controlled by our architecture. We take a bottom-up approach by determining which primitive notions of locomotion and appearance have the most impact on people's perceptions of a mobile robot. We present the results of two online and one in-person experiment showing that the manner in which a mobile robot navigates has a significant impact on people's attribution of attitudes and physical properties to the robot.

关键词： automation Navigation Mobile robots

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Semantic Segmentation of Vehicle Steering Column Pattern Image Based on K-Net Network 6

Semantic Segmentation of Vehicle Steering Column Pattern Ima...

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6th international conference on robotics, Intelligent control and Artificial Intelligence, RICAI 2024

作者： Wu, Tingxuan Li, Jing Shen, Nanyan Tang, Xiaobo Wang, Xin School of Mechatronic Engineering and Automation Shanghai University Shanghai China Mechatronic Co. Ltd. Shanghai China

ISBN: (纸本)9798331541699

As an important assembly part of the automobile, the steering column module is mainly used to control the turn signal and the wiper switch. therefore, it is necessary to check the integrity of its printed beacon pattern. However, the image quality of the traditional image processing vision system is easily affected by the field environment, and due to the existence of a large number of reflection areas in the image, the image segmentation is low precision, low adaptability and high error rate. therefore, this paper uses K-Net deep learning network semantic segmentation model to automatically remove image reflection. By using Swin-T backbone network and introducing self-attention mechanism, the segmentation performance of beacon is further improved, and the anti-reflective binary segmentation of beacon is realized. Finally, the superiority of the above model is verified in the production line data set of enterprise steering column products. the experimental results show that: (1) K-Net network has a good segmentation effect, and its mIoU reaches 95.77%;(2) After using the Swin-T backbone network, the mIoU of K-Net model increased by 1.1% compared with the traditional CNN backbone network. © 2024 IEEE.

关键词： Semantic Segmentation

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Visible-Infrared Cross-Modal Person Re-Identification Based on Modality Alignment and Fine-Grained Mining 14

Visible-Infrared Cross-Modal Person Re-Identification Based ...

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14th IEEE international conference on Cyber Technology in automation, control, and Intelligent Systems, CYBER 2024

作者： Zhao, Yingchang Yu, Hang Cheng, Zhuxuan Fan, Huijie Lin, Sen School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China School of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China

ISBN: (纸本)9798331506056

In the current field of computer vision, visible-infrared cross-modal person re-identification has become a research topic of great interest. this task aims to identify and match images of the same pedestrian from different modalities and is widely applied in scenarios like night-time surveillance and multi-camera tracking. However, due to significant visual differences between modalities, this task faces many challenges. To overcome these challenges, in this paper we propose a cross-modal person re-identification method based on modality alignment and fine-grained local feature mining. First, we introduce the Modality Alignment Module, which aims to reduce visual differences between modalities, thereby providing a more consistent foundation for feature extraction and matching. then, through the Fine-grained Mining Module, we delve into the local details in pedestrian images to enhance the distinctiveness of features and the accuracy of identification. Moreover, by incorporating advanced deep learning architectures and optimization algorithms, our method shows exceptional results on both SYSU-MM01 and RegDB datasets. © 2024 IEEE.

关键词： Image enhancement

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PNC-CL a Toolbox for Piecewise Affine Convex-Liftings with Application in Planning and control Design

PNC-CL a Toolbox for Piecewise Affine Convex-Liftings with A...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Sorin Olaru Turan Konyalioglu Marius Jaegler Mickaël Martinelli Valentin Carrez Laboratoire des Signaux et Systèmes Université Paris-Saclay CNRS CentraleSupélec France

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

the paper describes a novel, publicly available toolbox for piecewise-affine (PWA) convex-lifting. the main goal is to provide a tool for efficient partitions of sets in finite-dimensional spaces with applications in navigation and control design. this objective is achieved by employing a lift-and-project philosophy that relies on performant linear programming optimization and polyhedra manipulation. Once a PWA lifting is constructed, the related polyhedral partition provides an interconnection graph that can be used for path planning, which is considered here as the main application. the paper provides the main theoretical elements of the technique's foundation and describes the toolbox's structure along with the numerical artifacts used for its implementation. Illustrative examples for the practical problems are provided, supporting the claims of efficiency and versatility.

关键词： Philosophical considerations automation control design Navigation Aerospace electronics Linear programming Path planning Planning Robots Optimization

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On Rapid Parallel Tuning of controllers of a Swarm of MAVs – Distribution Strategies of the Updated Gains

On Rapid Parallel Tuning of Controllers of a Swarm of MAVs ...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Dariusz HorIa Wojciech Giernacki Vít Krátký Petr Štibinger Tomáš Báča Martin Saska Faculty of Automation Robotics and Electrical Engineering Institute of Robotics and Machine Intelligence Poznan University of Technology Poznan Poland Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Prague Czechia

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

In this paper, we present a reliable, scalable, time deterministic, model-free procedure to tune swarms of Micro Aerial Vehicles (MAVs) using basic sensory data. Two approaches to taking advantage of parallel tuning are presented. First, the tuning with averaging of the results on the basis of performance indices reported from the swarm with identical gains to decrease the negative effect of the noise in the measurements. Second, the tuning with parallel testing of varying set of gains across the swarm to reduce the tuning time. the presented methods were evaluated both in simulation and real-world experiments. the achieved results show the ability of the proposed approach to improve the results of the tuning while decreasing the tuning time, ensuring at the same time a reliable tuning mechanism.

关键词： automation Distribution strategy Noise Gain measurement Robot sensing systems Data models Reliability Noise measurement Tuning Testing

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Distributed Predefined-Time Optimal control Algorithm for Nonconvex Optimization of MASs

Distributed Predefined-Time Optimal Control Algorithm for No...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Jing-Zhe Xu Zhi-Wei Liu Dandan Hu Xiao-Kang Liu Guanghui Wen Tao Yang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Management South-Central Minzu University Wuhan China Department of Mathematics Southeast University Nanjing China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

this paper delves into a class of distributed nonconvex optimization control (DNOC) problems for multiagent systems (MASs), aiming to attain consensus among agents while minimizing the collective sum of local cost functions, referred to as the global cost function, through local information exchange. To accomplish this objective, it is introduced a novel distributed predefined-time optimal (DPTO) control algorithm. We prove that the proposed DPTO control algorithm guides the system states towards convergence to the global optimal solution within a user-defined time frame, provided that the global cost function satisfies the Polyak-Lojasiewicz condition, which is less stringent than the standard strong convexity condition. Finally, theoretical findings are substantiated through simulation studies.

关键词： automation Optimal control Games Cost function Nash equilibrium Standards Robots Information exchange Multi-agent systems Convergence

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