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

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Multi-objective Optimization Layout of Intelligent Robot Integrated Workshop Based on Machine vision 4

Multi-objective Optimization Layout of Intelligent Robot Int...

引用

4th international conference on robotics, Intelligent control and Artificial Intelligence, RICAI 2022

作者： Guo, Lina Applied Electronics Department Shandong Institute Commerce and Technology jinan Shandong250103 China

ISBN: (纸本)9781450398343

the application object of layer manufacturing unit is mainly intelligent factory or robot manufacturing unit with high degree of automation. Compared with the traditional single layer manufacturing unit, the number of equipment of multi-layer manufacturing unit is more, and the three-dimensional space factor needs to be considered, so the problem is more complicated. this paper mainly studies the multi-objective optimization layout of intelligent robot integrated workshop based on machine vision. In this paper, based on the proposed DCSGSA algorithm, according to the computational complexity and multi-scale characteristics of the integrated model, a multi-layer optimization strategy of robot work unit layout is designed to solve the model. the proposed algorithm was used to solve a practical case of intelligent die casting island parts taking robot unit of a die casting machine company, and compared with other multi-objective algorithms, the efficiency of the proposed algorithm was verified. © 2022 ACM.

关键词： Computer vision

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Alpha-Matrix Adaptive Model-Free control for Quadrotor with Manipulator Under Wind Disturbance

Alpha-Matrix Adaptive Model-Free Control for Quadrotor with ...

引用

robotics and Computer vision (ICRCV), international conference on

作者： Ding Ding Yang Tian Haoping Wang Xincheng Zhuang School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9798331527426

ISBN: (纸本)9798331527433

this article develops a-matrix adaptive model-free control (am-AMFC) based on time delay estimation (TDE) for manipulating the position and attitude of an aerial manipulator. the system is composed of a quadrotor and a two-degree-of-freedom(2-DOF) manipulator, and it functions in the presence of friction and wind disruption. the referred am-AMFC is developed using a TDE-based intelligent PD control (TDE-iPD) and an αm online adaptive estimation law. the TDE is intended to offer estimations of the system state, model uncertainties, and lumped disturbances of the system. αm is adaptively updated by forgetting factor recursive least square (FFRLS). Finally, Lyapunov function is used to analyze the stability of the system. Numerical simulations were conducted to illustrate the efficacy of the am-AMFC controller in comparison to PID and TDE-iPD controllers.

关键词： Adaptation models Uncertainty Accuracy Trajectory tracking Estimation Manipulators Mathematical models Numerical models Steady-state Quadrotors

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Target Detection and Position Measurement Based on Machine vision for AGV

Target Detection and Position Measurement Based on Machine V...

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automation, control and robotics Engineering (CACRE), international conference on

作者： Guiyang Zhang Lingyu Zhu Siyu Ji Xu Wu School of Mechanical Engineering Changshu Institute of Technology Optical Measurement Center Suzhou TZTEK Technology Company Limited Suzhou China School of Mechanical Engineering Changshu Institute of Technology Suzhou China Software Engineering Institute East China Normal University Shanghai China

this paper proposes a strategy based on cooperative target to realize automatic guided vehicle (AGV) terminal detection and position measurement. Firstly, the enhanced YOLOv3 algorithm based on cross layer connection is employed to detect the interest area of the marker points, upon which more refined local features are restored to improve the adaptability to small targets. then, a high-precision 3D reconstruction with the aid of the ellipse center coordinates is demonstrated to ensure the reliability and avoid the loss of targets due to the failure of landmarks caused by environmental factors. the experimental results revealed that the positioning accuracy error is less than 1.5mm and the misrecognition rate is superior to 1% whilst the AGV is within 5m from the target. Consequently, the proposed approach has the crucial application in rapid and stable AGV terminal vision positioning.

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Development of a massage robot based on visiontactile fusion and adaptive force control

Development of a massage robot based on visiontactile fusion...

引用

robotics, Intelligent control and Artificial Intelligence (RICAI), international conference on

作者： Hongyu Yang Wen Zhang Haojun Si Teng Sun School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

With the rapid advancement of robotics, robotic massage systems have shown great potential in ensuring consistent massage effectiveness and providing personalized treatments. However, accurately controlling the force applied during the massage, especially given the variation in muscle stiffness and tissue properties across different body regions, remains a significant challenge. Traditional force control methods typically rely on predefined trajectories or basic feedback systems, which are insufficient in adapting to these variations, often resulting in discomfort or suboptimal therapeutic outcomes. To address this, this paper proposes a robotic massage system with adaptive force control, integrating both vision and tactile sensing. the system combines computer vision-based skeletal recognition with real-time feedback from a six-dimensional force sensor to dynamically adjust the applied force based on variations in tissue stiffness across different body areas. Experimental results demonstrate that this approach optimizes force application, significantly enhancing both the effectiveness and comfort of the massage. this study introduces a vision-tactile fusion approach, offering new insights into overcoming the challenges of diversity and adaptability in current robotic massage systems.

关键词： Visualization Adaptive systems Force thigh Robot sensing systems Real-time systems Trajectory Force control thermal stability Visual perception

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A vision-Integrated Navigation Method in AUV Terminal Mobile Docking Based on Factor Graph Optimization

A Vision-Integrated Navigation Method in AUV Terminal Mobile...

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automation, control and robotics Engineering (CACRE), international conference on

作者： Tianheng Ma Shumin Chen Liang Ruan Yuanxin Xu College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Faculty of Informatics and Electronics Zhejiang Sci-Tech University Hangzhou China

the widespread use of Autonomous Underwater Vehicles (AUVs) highlights the need for autonomous docking, during which accurate pose estimation and navigation play a vital role. this paper proposes a multi-sensor fusion navigation framework based on the factor graph optimization method, integrating tightly-coupled visual information from the light array to provide high-accuracy and high-frequency relative pose estimations between AUV and its mobile dock at the terminal docking stage. Simulation results demonstrate that the proposed algorithm outperforms PnP and achieves smaller RMSE in relative attitude and translation estimations. Furthermore, the experiments show that the proposed algorithm provides smoother estimation results and that it has the potential to be deployed in embedded applications.

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Traffic Signal control for Large-Scale Urban Traffic Networks: Real-World Experiments using vision-based Sensors

Traffic Signal Control for Large-Scale Urban Traffic Network...

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international conference on control and automation (ICCA)

作者： Jiho Park Tong Liu Chieh Wang Hong Wang Qichao Wang Zhong-Ping Jiang Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn NY USA Oak Ridge National Laboratory Oak Ridge TN USA National Renewable Energy Laboratory Computational Science Center Golden CO USA

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. the primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. these experiments demonstrated significant performance improvements in comparison to the existing method.

关键词： Energy consumption Urban areas Decentralized control Data processing Real-time systems Sensors Delays

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Image Processing for Robotic control in Life Science Laboratory automation

Image Processing for Robotic Control in Life Science Laborat...

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robotics and Computer vision (ICRCV), international conference on

作者： Haoying Yu Vilhelm Krarup Møller Rasmus John Normand Frandsen Marjan Mansourvar Department of Electrical Engineering Technical University of Denmark Copenhagen Denmark Department of Biotechnology and Biomedicine Technical University of Denmark Copenhagen Denmark

In the contemporary age of advanced technology, image processing plays a vital role as an efficient and indispensable tool across industries, enterprises, monitoring systems, and various applications. this study focuses on employing image processing techniques with an Opentrons industrial robot to ensure quality control during production. By leveraging the YOLOv5 model, the robot adeptly recognizes diverse pipette tip types, identifies liquids by their colors, and accurately measures liquid levels to estimate volume percentages within each tip. these detection results then guide a programmable robot, enabling it to perform specific actions on the tips based on predetermined parameters. this paper provides a comprehensive description of the methodology, implementation, and evaluation of our integrated control-robotic system, highlighting its potential to significantly enhance efficiency and precision in laboratory settings.

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Deep Learning Object Detection Techniques for thin Objects in Computer vision: An Experimental Investigation 7

Deep Learning Object Detection Techniques for Thin Objects i...

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7th international conference on control, automation and robotics (ICCAR)

作者： Jaffari, Rabeea Hashmani, Manzoor Ahmed Reyes-Aldasoro, Constantino Carlos Aziz, Norshakirah Rizvi, Syed Sajjad Hussain Univ Teknol Petronas Comp & Informat Sci Dept High Performance Cloud Comp Ctr HPC3 Sri Iskander 32610 Malaysia City Univ London giCtr Dept Comp Sci London EC1V 0HB England Univ Teknol Petronas Comp & Informat Sci Dept Ctr Res Data Sci CeRDaS Sri Iskander 32610 Malaysia SZABIST Dept Comp Sci Karachi Sindh Pakistan

ISBN: (纸本)9781665449861

Efficient detection of thin objects, from stationary or moving images, is significant in a variety of research areas. these research areas include but are not limited to electric power line detection systems, sperm tail detection for clinical sperm research, mooring lines detection, road-lane line detection for autonomous vehicles, and cracks detection for the integrity assessment of building structures. However, the detection of thin objects is a challenging computer vision task owing to the slimmer and less compact nature of these objects. Moreover, the complexity present in certain images, such as the background clutter, further adds to this problem of accurately detecting thin objects. In this work, we investigate a series of state-of-the-art deep learning detectors for thin objects' detection. the detectors examined in this work were: EfficientDet, YOLOv5 and U-Net. the experimental results of this study reveal that generic state-of-the-art deep detectors are not suitable for detecting thin objects due to their reliance on coarse bounding boxes and/or excessive pixel-level computations while the application-specific detectors possess poor generalization capabilities and do not work accurately outside their domains. these empirical findings indicate the necessity of the identification of critical factors affecting thin objects detection and the subsequent design of a generic thin objects' detector.

关键词： thin objects object detection deep learning line detection machine learning

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Color Sorting System Using YOLOv5 for Robotic Mobile Applications

Color Sorting System Using YOLOv5 for Robotic Mobile Applica...

引用

robotics and Computer vision (ICRCV), international conference on

作者： Samuel Peña Andrea Pilco Viviana Moya William Chamorro Juan Pablo Vásconez José Andres Zuniga Facultad de Ciencias Técnicas Universidad Internacional del Ecuador Quito Ecuador Departamento de Automatización y Control Industrial Escuela Politecnica Nacional Quito Ecuador Energy Transformation Center Faculty of Engineering Universidad Andres Bello Santiago Chile

ISBN: (数字)9798331527426

ISBN: (纸本)9798331527433

the integration of mobile robots and computer vision has revolutionized industrial tasks by enabling precise and efficient automation processes. this work proposes a mobile platform for sorting Petri dishes using advanced deep-learning techniques. We utilize the YOLOv5 framework for real-time color detection and a 6-bar mechanism with a gripper for dynamic sample sorting. the implementation enhances logistics and reduces operational errors through accurate color classification. Our methodology includes creating a training dataset of over one thousand labeled RGB images and validating the system's performance. the trained network achieved over 90% accuracy during validation and testing, demonstrating precise robot positioning and effective Petri dish manipulation. this research successfully addresses automation challenges in industrial settings, offering improved efficiency and accuracy.

关键词： YOLO Performance evaluation Petri dishes Computer vision Accuracy Service robots Image color analysis Robots Testing Sorting

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EAI-SIM: An Open-Source Embodied AI Simulation Framework with Large Language Models

EAI-SIM: An Open-Source Embodied AI Simulation Framework wit...

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international conference on control and automation (ICCA)

作者： Guocai Liu Tao Sun Weihua Li Xiaohui Li Xin Liu Jinqiang Cui Peng Cheng Laboratory Shenzhen Guangdong China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Guangdong China Beihang University Beijing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In the era of embodied intelligence, developing and testing various intelligent algorithms for robots, including unmanned aerial vehicles (UAVs) and manipulators, poses significant challenges. Researchers are increasingly depends on simulation technologies to evaluate the performance of new al-gorithms across various conditions and applications. the advent of large language model (LLM) technology creates new demand for simulations of robotics tasks with the help LLMs. this study introduces EAI_SIM, a simulation system capable of controlling unmanned aerial vehicles (UAVs) and manipulators based on user prompts. the modular framework acts as an extension of NVIDIA Isaac Sim, facilitating real-time simulation of UAVs and manipulators in photo-realistic environments. thanks to the modular implementation and user-friendly Graphical User Interface (GUI), it can be seamlessly integrated with the widely used PX4-Autopilot and ROS2 system. To showcase its performance, a variety of control Application Programming Interfaces (APIs) are implemented within EAI_SIM. A range of tasks can be achieved by combining different APIs. Supplementary material, including code and documentation for this framework, is provided to benefit the community. the source code can be found at https://***/PengICS/eai_sim, and a demo video can be found at https://***/YcNkwo_PNnQ.

关键词： Large language models Source coding Documentation Manipulators Autonomous aerial vehicles control systems Real-time systems

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