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

共 5313 条记录，以下是701-710 订阅

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A fault detection method for AUV based on multi-scale spatiotemporal feature fusion 5

A fault detection method for AUV based on multi-scale spatio...

引用

5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Xia, Shaoxuan Zhou, Xiaofeng Shi, Haibo Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

Autonomous underwater vehicles (AUVs) are important equipment for ocean development and exploration. To ensure the task implementation of AUV, faults shall be detected in time. We propose a fault detection method based on multi-scale spatiotemporal feature fusion (MSF) for the time-varying characteristics and multiple correlation characteristics of AUV monitoring data. First, we apply a variety of sampling and data processing methods to generate monitoring windows with different scales along the time axis. then, a composite feature extraction method is proposed to obtain temporal and spatial features simultaneously, and a feature pyramid of temporal and spatial information is formed. We use bidirectional long short-term memory (BiLSTM) to obtain the time-series characteristics of a single monitoring variable, and convolutional neural networks (CNN) to obtain the implicit spatial relationship characteristics among multiple monitoring variables. Next, we use an adaptive feature fusion method to solve the inconsistency in different feature scales, which can adaptively suppress the possible conflict information of different scale features. Finally, we use a fully connected network to detect the fault of the fused features. the fault detection experiment of Haizhe AUV shows the effectiveness and superiority of the proposed method. © 2023 SPIE.

关键词： Autonomous underwater vehicles

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Laser Weld Defect Detection Based on Laser vision and Region Growth

Laser Weld Defect Detection Based on Laser Vision and Region...

引用

Industrial automation, robotics and control Engineering (IARCE), international conference on

作者： Dejian Li Yajun Zhang Jianing Xu Zhibo Ding Shaoli Li School of Information Science and Engineering Shenyang University of Technology Shenyang China

ISBN: (数字)9798350380323

ISBN: (纸本)9798350380330

In this paper, we propose a laser vision-based approach for detecting defects in steel laser welding. the Bounding Volume Hierarchy (BVH) algorithm is combined with region growing to effectively segment point cloud data. this segmentation process leverages both local region features and the interrelationships among neighbouring points. Initially, the BVH algorithm is utilized to group the point cloud data, identifying optimal seed point locations for subsequent analysis. Subsequently, the region growing algorithm is applied, with the establishment of specific growth criteria to determine point inclusion within their respective regions. these defined growth criteria serve as guidance for expanding the regions from the initially selected seed points. this expansion process culminates in the derivation of segmentation results and facilitates the identification of defects. Importantly, this process eliminates the need for pre-emptive defect type confirmation or the conversion of 3D data into 2D data, as typically practiced in conventional point cloud processing. this enhancement significantly enhances detection efficiency. Experimental results underscore the effectiveness of this approach in overcoming potential interferences such as light source noise, leading to successful defect segmentation. At the same time, compared with other typical methods, our method takes the shortest time. Consequently, this method holds potential for detecting welding defects within industrial settings.

关键词： Point cloud compression Accuracy three-dimensional displays Service robots Welding Laser noise Lasers Steel Surface treatment Defect detection

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Towards vision-Based Dual Arm Robotic Fruit Harvesting

Towards Vision-Based Dual Arm Robotic Fruit Harvesting

引用

IEEE international conference on automation Science and Engineering (CASE)

作者： Ege Gursoy Benjamin Navarro Akansel Cosgun Dana Kulić Andrea Cherubini LIRMM CNRS Univ. Montpellier Montpellier France Monash University Australia Deakin University Australia

Interest in agricultural robotics has increased considerably in recent years due to benefits such as improvement in productivity and labor reduction. However, current problems associated with unstructured environments make the development of robotic harvesters challenging. Most research in agricultural robotics focuses on single arm manipulation. Here, we propose a dual-arm approach. We present a dual-arm fruit harvesting robot equipped with a RGB-D camera, cutting and collecting tools. We exploit the cooperative task description to maximize the capabilities of the dual-arm robot. We designed a Hierarchical Quadratic Programming based control strategy to fulfill the set of hard constrains related to the robot and environment: robot joint limits, robot self-collisions, robot-fruit and robot-tree collisions. We combine deep learning and standard image processing algorithms to detect and track fruits as well as the tree trunk in the scene. We validate our perception methods on real-world RGB-D images and our control method on simulated experiments.

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Multi-objective Model Predictive control for Trajectory Tracking of Intelligent Electric Vehicles

Multi-objective Model Predictive Control for Trajectory Trac...

引用

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

作者： Tianchu Su Hao Chen Chen Lv School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781665476881

this paper presents a multi-objective strategy for trajectory tracking of intelligent electric vehicles incorporating tracking performance with the energy economy. A model predictive controller is built using the single-track vehicle dynamics model to predict planar motions. the optimization problem is formulated with a cost function involving tracking errors and motor efficiency. the proposed system is verified on a typical road in the co-simulation platform - CarSim/Simulink. Experimental results from the simulation demonstrate the expected performance of the developed system. Intelligent electric vehicles, trajectory tracking, multi-objective optimization, model predictive control

关键词： automation Trajectory tracking Roads Predictive models Electric vehicles Cost function Vehicle dynamics

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Facial Landmark Detection Algorithm in Complex Scenes

Facial Landmark Detection Algorithm in Complex Scenes

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IEEE international conference on control and robotics Engineering (ICCRE)

作者： Haoqi Gao Xing Yang Yihua Hu Haoli Xu Zhenyu Liang Bingwen Wang Huiqing Xiang Zhiyang Hu Shulong Hu College of Electronic Engineering National University of Defense Technology Hefei China School of Electrical Engineering and Automation Hefei University of Technology Hefei China

ISBN: (数字)9798350372694

ISBN: (纸本)9798350372700

Nowadays, Convolutional neural networks (CNNs) have become the benchmark technology for many computer vision applications. Face landmark detection has been an important topic over the last few decades. However, most algorithms are designed for small to medium-sized poses of faces and lack accuracy in complex scenes such as lighting, large poses, and occlusion. there are some challenges: first, the appearance of the face varies more from the frontal view to the profile view. Second, human faces are easily affected by occlusions or illumination, so it is hard to provide the most appropriate location. In this article, we proposed using joint CNNs to improve the accuracy of facial landmark estimation. Extensive experiments conducted on large angles and severe occlusion challenging databases such as Menpo and COFW have also demonstrated the superiority of our proposed method in challenging scenarios.

关键词： Accuracy Databases Lighting Estimation Detectors Robot sensing systems Robustness

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Path Following control for Human-Robot Collaborative Tasks

Path Following Control for Human-Robot Collaborative Tasks

引用

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

作者： Shaundell Dubay William Melek Christopher Nielsen Dept. of Mechanical & Mechatronics Engineering University of Waterloo Waterloo ON Canada Dept. of Electrical & Computer Engineering University of Waterloo Waterloo ON Canada

ISBN: (纸本)9781665476881

this paper presents a path following control designed for human-robot collaborative tasks. the path following strategy allows the task description and human-robot interaction to be defined according to components tangent and transversal to a nominal path. With this formulation, the control objectives for each task can be customized to generate motions towards task completion and getting on the nominal path when switching between tasks. Simulation examples of the path following control is presented, demonstrating the ability for the proposed controllers to be customized according to objectives of the human-robot collaboration.

关键词： automation Collaboration Human-robot interaction Switches control systems End effectors Task analysis

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Adaptive distance-based formation control

Adaptive distance-based formation control

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

作者： Minh Hoang Trinh thanh Truong Nguyen Zhiyong Sun School of Electrical and Electronic Engineering Hanoi University of Science and Technology (HUST) Hanoi Vietnam Unmanned Aerial Vehicle Center Viettel High Technology Industries Corporation Hanoi Vietnam Department of Electrical Engineering Eindhoven University of Technology (TU/e) the Netherlands

ISBN: (纸本)9781665476881

this paper studies the distance-based formation control problem where agents in the system are modeled with single-integrators with parametric uncertainties. We propose to use adaptive control as the main tool to approach the problem. Under the assumption that only local displacements are available, an adaptive distance-based control law is proposed and analysed. If additionally, each agent can sense its local position, we propose using an additional observer to estimate the uncertain parameters and stabilize the desired formation. Simulation results are also given to support the theoretical results.

关键词： Adaptation models Sufficient conditions Uncertainty automation Simulation Neural networks Observers

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Multi-agent systems with memories under DoS attacks

Multi-agent systems with memories under DoS attacks

引用

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

作者： Ricardo Almeida Ewa Girejko Luís Machado Agnieszka B. Malinowska Natália Martins Department of Mathematics Center for Research and Development in Mathematics and Applications University of Aveiro Portugal Faculty of Computer Science Bialystok University of Technology Białystok Poland Institute of Systems and Robotics - University of Coimbra Coimbra Portugal Department of Mathematics University of Trás-os-Montes e Alto Douro (UTAD) Vila Real Portugal

ISBN: (纸本)9781665476881

the paper is devoted to multi-agent systems with memories under denial-of-service (DoS) attacks. the memory is represented by the fractional derivative that appears in the dynamics of the considered systems. the problem that we aim to address is, under which conditions the system continues to be stable or is in consensus mode, despite DoS attacks. Solutions to these problems are proposed in the presented theorems. We strengthen the theoretical considerations with numerical simulations.

关键词： Linear systems Sufficient conditions automation Denial-of-service attack Numerical simulation Stability analysis Robots

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Compensation Function Observer-Based Model-Free Adaptive Full-Order Sliding Mode control for Hydraulic Manipulator with Payload Uncertainties

Compensation Function Observer-Based Model-Free Adaptive Ful...

引用

robotics and Computer vision (ICRCV), international conference on

作者： Minxuan Zha Yang Tian Haoping Wang School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9798331527426

ISBN: (纸本)9798331527433

the trajectory tracking of hydraulic manipulator under complex operating condition is a challenging job due to its inherent strong nonlinearities and unknown external disturbances. In this paper, a compensation function observer-based model-free adaptive full-order sliding mode control for hydraulic manipulator is proposed in the presence of unknown payload and friction. To simplify controller design and overcome dependency on model, the ultra-local model (ULM) is utilized to approximate the complex hydraulic manipulator system in a short sliding time window. the compensation function observer is designed based on ULM to estimate the lumped uncertainties which is robust to the high-frequency disturbances and can ensure zero estimation errors. Moreover, full-order sliding mode surface is constructed to accelerate error convergence with a switching sliding gain adaption law based on boundary layer. the switching gain increase as the sliding motion moves away from boundary to improve the trajectory performance. In contrast, the gain will maintain a small value to alleviate the chattering problem. To validate the performance of the proposed control strategy, co-simulation of 3-DOF hydraulic manipulator are realized using SolidWorks, Simscape Multibody/Fluids, Matlab/Simulink in the presence of time-varying payload and joint friction. In addition, the performance of the proposed CFO-AFOSMC is demonstrated compared with TDE-iPD and TDE-SMC.

关键词： Adaptation models Uncertainty Friction Hydraulic systems Switches Observers Mathematical models Sliding mode control Manipulator dynamics Payloads

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Robust Adaptive Attitude Trajectory Tracking control for Quadrotor UAVs based on Relaxed controllability Condition

Robust Adaptive Attitude Trajectory Tracking Control for Qua...

引用

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

作者： Jinyu Ni Zhongyu Zhang Xiao Wang Xiucai Huang Chongqing Key Laboratory of Intelligent Unmanned Systems School of Automation Chongqing University Chongqing China

ISBN: (纸本)9781665476881

this paper investigates the attitude trajectory tracking control problem for quadrotor UAVs. An uncertain nonlinear affine state system is modeled from the quadrotor with unknown external disturbances. By checking the existence of certain auxiliary matrix, a milder controllability condition for the quadrotor model is introduced building upon which a robust adaptive attitude trajectory tracking controller is proposed, which guarantees that all signals in the closed loop quadrotor system are globally ultimately uniformly bounded (GUUB) and the trajectory tracking errors converge to zero asymptotically. Finally, the effectiveness of our method is verified by simulations.

关键词： Adaptation models Tracking loops Trajectory tracking Attitude control Neural networks controllability Robots

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