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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681-690 订阅

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Performance Analysis of Computer vision Based Feature Detectors for 3D Laser Rasterized Images 5

Performance Analysis of Computer Vision Based Feature Detect...

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5th international conference on automation, control and Robots, ICACR 2021

作者： Ali, Waqas Liu, Peilin Ying, Rendong Shanghai Jiaotong University School of Electronic Information And Electrical Engineering Shanghai China

ISBN: (纸本)9781665438490

the 3D point cloud processing and scan registration is a computationally expensive task as each scan contains thousands of points. An effective solution is to use feature detection methods to reduce the dimensions of the point cloud. these methods include feature detection directly from a point cloud or using a 2D projection. the 2D projection methods have proven to require lower computational resources. In this paper, a pinhole camera model is used to rasterize the 3D point cloud to a 2D image. this paper provides a detailed analysis of the performance of several computer vision-based feature detectors on rasterized laser images. We perform an extensive evaluation on multiple datasets including, KITTI, FORD campus, and an indoor dataset. the primary goal is to compare the quality of features and computational requirements for each method. © 2021 IEEE.

关键词： Computer vision

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On Asymptotic Nash Equilibrium for Linear Quadratic Mean-Field Games

On Asymptotic Nash Equilibrium for Linear Quadratic Mean-Fie...

引用

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

作者： Zhipeng Li Minyue Fu Qianqian Cai College of Engineering Qufu Normal University Rizhao China School of Engineering University of Newcastle NSW Australia School of Automation University of Technology Guangzhou China

ISBN: (纸本)9781665476881

A new asymptotic Nash equilibrium for a class of linear quadratic mean-field game problem with a finite number of agents is found by using the cost function decomposition method. the cost function value corresponding with this equilibrium is also computed. this value turns out to be smaller than the one obtained by the state average approximation method. the difference is prominent when the number of agents is small, but vanishes as the agents' number tends to infinity.

关键词： automation Decentralized control Games Nash equilibrium Cost function Robots Centralized control

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Recognition of insulator based on yolov5 algorithm 11

Recognition of insulator based on yolov5 algorithm

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11th IEEE Annual international conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2021

作者： Feng, Han Jiang, Yong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9781665425278

the pollution flashover accident of insulator strings in substation is the main threat to the safety of power systems, water washing operations on the surface of insulator strings can effectively eliminate this risk, and use intelligent robots to perform water washing tasks instead of manual labor is gradually becoming mainstream. In order to accomplish water washing task, the robot needs to find out the position of the insulator string by using vision sensors. In this paper, we build an insulator strings dataset with 150 images, train and compare the performance differences of four models of Yolov5 for insulator strings detection. Experiments show that when performing the insulator string detection, the difference of detection precision between the four Yolov5 models is small, Yolov5x having 0.02 higher precision than Yolov5s. While the difference in inference speed is large, with Yolov5s being 5 times faster than Yolov5x and can reach 43 FPS on GTX1060. © 2021 IEEE.

关键词： Intelligent robots

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Research on Autonomous Charging Method for Quad-Rotor Drone Based on Magnetic Induction Coupling

Research on Autonomous Charging Method for Quad-Rotor Drone ...

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international conference on control and Robots (ICCR)

作者： Haoyi Zheng Sen Zhang Wendong Xiao Shunde Innovation School University of Science and Technology Beijing Foshan China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

the limited battery capacity carried by drones has greatly affected their endurance. When the drone detects a low battery during operation, if it can replenish energy independently, it will greatly improve the drone's operating range and working time, which has profound significance for the normal operation of drones in automation scenarios. In response to the issue of autonomous charging for unmanned aerial vehicles, this article proposes a method for autonomous charging of quadcopter unmanned aerial vehicles. the method of using machine vision to recognize Apriltag markers enables the drone to accurately land at the charging position. the structure of a rounded rectangular coupling coil allows the drone to wirelessly obtain electricity. the system hardware circuit uses the LCC-S compensation structure to improve the transmission efficiency of the system. the experimental results indicate that this system can provide power to the drone. the method proposed in this article provides a reference for achieving autonomous energy acquisition of unmanned aerial vehicles.

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Intelligent control Systems for Industrial automation and robotics

Intelligent Control Systems for Industrial Automation and Ro...

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IEEE UP Section conference on Electrical Computer and Electronics (UPCON)

作者： Vijaykumar S. Biradar Ali Khudhair Al-Jiboory Gaurav Sahu S. B G Tilak Babu Kommabatla Mahender Natrayan L Department of Electrical Engineering N B NavaleSinhgad College of Engineering Solapur Maharashtra Department of Mechanical Engineering University of Diyala Baqubah Department of Electronics& Communication Engineering B K Birla Institute of Engineering & Technology Pilani Rajasthan Department of ECE Aditya Engineering College Surampalem Department of ECE Sumathi Reddy institute of technology for women Telangana India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

Intelligent control systems are a game-changer for robotics and industrial automation. this abstract explores how computer vision (CV) and artificial neural network (ANN) algorithms may be used to improve automation and robotics in terms of efficiency, accuracy, and flexibility. the goal of industrial automation is to streamline processes, decrease the need for human interaction, and increase output, all of which have progressed dramatically over the years. Integrating intelligent control systems that make use of computer vision and artificial neural networks is crucial to this transformation. the ability of these systems to detect and understand their environments is made possible by computer vision (CV). In order to make sound judgements, CV algorithms analyse data captured by cameras and other sensors. CV lets robots recognise things, navigate hazardous terrain, and carry out precise industrial tasks. CV has become an integral part of industrial automation, used for anything from monitoring production quality to navigating warehouses autonomously. Artificial neural networks (ANN s) mimic the human brain in many ways, including their ability to learn and make decisions on their own. ANNs are built from networks of nodes (neurons) that work together to analyse and process information. ANN s may learn to identify patterns, refine their control settings, and adjust to new circumstances. Predictive maintenance, problem identification, and control strategy optimisation are just some of the ways in which ANN s are put to use in industrial automation and robotics. Combining CV with ANN algorithms makes for a formidable tool with many practical uses in industry. the automated examination of produced goods is one significant use. Cracks and imperfections are easy targets for CVs, while ANNs can analyse the data in real time to make judgements about the product's quality. As a result, we can maintain constant quality control, cut down on waste, and boost output. Combining C

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DR-SLAM: vision-Inertial-Aided Degenerate-Robust LiDAR SLAM Based on Dual Confidence Ellipsoid Oblateness

DR-SLAM: Vision-Inertial-Aided Degenerate-Robust LiDAR SLAM ...

引用

IEEE international conference on Cyber Technology in automation, control, and Intelligent Systems

作者： Zhixing Song Runhua Wang Songyang Wu Youwei Wang Yunze Tong Xuebo Zhang Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In environments with similar geometric structures or sparse features, it is extremely challenging for mobile robots to perform LiDAR simultaneous localization and mapping. this paper presents a new vision-inertial-aided degenerate-robust LiDAR SLAM (DR-SLAM) based on dual confidence ellipsoid oblateness. First, to solve the problem of scale inconsistency between rotation and translation subspaces in traditional degradation judgment algorithms, this paper proposes a novel degradation judgment algorithm based on dual confidence ellipsoid oblateness, which is insensitive to environmental changes. then, we develop a vision-inertial-aided degenerate-robust LiDAR SLAM system. the visual-inertial odometry provides a priori pose, and the LiDAR point cloud is used to update the pose in well-constrained directions. Finally, experimental results in both self-built simulation environments and real-world scenarios demonstrate that DR-SLAM outperforms state-of-the-art methods in terms of accuracy and robustness.

关键词： Degradation Point cloud compression Laser radar Simultaneous localization and mapping Accuracy Robustness Odometry Mobile robots Intelligent systems Ellipsoids

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Determining the Position of an Object in three-Dimensional Space Using a Single Image with Computer vision Methods

Determining the Position of an Object in Three-Dimensional S...

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Information, control, and Communication Technologies (ICCT), international conference on

作者： G. A. Algashev A.V. Kupriyanov Samara National Research Univercity Samara Russian Federation

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

Determining the position of objects in three-dimensional space from two-dimensional images is a crucial task in computer vision. this paper proposes a novel method that accurately determines the position of an object using only a single image, reducing dependence on complex hardware and manual configuration. Our approach involves using a reference three-dimensional model of the object to generate training data and subsequently calculate its position in space. the method comprises several key steps: object detection in the image, keypoint detection, orientation determination, depth and scale calculation of the object and rendering the object in a three-dimensional scene. A distinctive feature of our approach is the automation of training data preparation, making it scalable and efficient for various objects and conditions. this method enhances the accuracy and convenience of object position determination, which can significantly impact fields such as robotics, autonomous vehicles and virtual reality.

关键词： Solid modeling Computer vision Accuracy Computational modeling Training data Manuals Position measurement Rendering (computer graphics) Reliability Autonomous vehicles

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Research on Robot Visual Grabbing Based on Mechanism Analysis 11

Research on Robot Visual Grabbing Based on Mechanism Analysi...

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11th IEEE Annual international conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2021

作者： Liu, Haichao Liu, Zhitai Liu, Huanli Lin, Weiyang Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9781665425278

this paper mainly studies the problem of grasping objects by manipulator based on vision, and a model-based visual grabbing strategy is proposed. Compared with the existing classical image processing methods including the Sobel operator edge extraction method, the superiority of the corrosion operation edge extraction method used in this strategy has been verified, through several fruit image processing experiments. In order to solve the lack of sufficient number of labeled object recognition samples required by machine learning methods, a model-based image classifier is also established, which is based on artificially extracted object features. Hence, it can be interpreted strongly and does not require training using a large number of data samples. Finally, a visual robot grabbing experiment has been constructed and carried out. the results show that efficiency and accuracy of the image recognition algorithm are proved, and this algorithm is efficient, light and interpretable. © 2021 IEEE.

关键词： Extraction

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A Novel Approach to Grasping control of Soft Robotic Grippers based on Digital Twin

A Novel Approach to Grasping Control of Soft Robotic Gripper...

引用

international conference on automation and Computing (ICAC)

作者： Tianyi Xiang Borui Li Quan Zhang March Leach Enggee Lim School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9798350360882

ISBN: (纸本)9798350360899

this paper has proposed a Digital Twin (DT) framework for real-time motion and pose control of soft robotic grippers. the developed DT is based on an industrial robot workstation, integrated with our newly proposed approach for soft gripper control, primarily based on computer vision, for setting the driving pressure for desired gripper status in real-time. Knowing the gripper motion, the gripper parameters (e.g. curvatures and bending angles, etc.) are simulated by kinematics modelling in Unity 3D, which is based on four-piecewise constant curvature kinematics. the mapping in between the driving pressure and gripper parameters is achieved by implementing OpenCV based image processing algorithms and data fitting. Results show that our DT-based approach can achieve satisfactory performance in real-time control of soft gripper manipulation, which can satisfy a wide range of industrial applications.

关键词： three-dimensional displays Computational modeling Fitting Kinematics Soft robotics Industrial robots Real-time systems Mathematical models Workstations Grippers

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Autonomous Sensor-Based control of Aerial Manipulator for Horizontal Pipe Structure Tracking with Continuous Contact

Autonomous Sensor-Based Control of Aerial Manipulator for Ho...

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international conference on robotics and automation Sciences (ICRAS)

作者： Naisarg Pandya Amit Shukla Pushkar Kumar Ankit Mehra Indian Institute of Technology Mandi

ISBN: (数字)9798350352504

ISBN: (纸本)9798350352511

this paper proposes an autonomous sensor-based control of an aerial manipulator for tracking horizontal pipe structures with continuous contact. this approach can be used for continuous contact inspection of long-range industrial pipe structures. To automate the aerial manipulator, the perception module of the proposed approach includes a deep learning technique for pipe identification in the image, a classical vision for feature extraction, and a Kalman filter to increase the frequency of data flow in a system. the integration of LiDAR and the camera sensor has been used to locate the approximate contact point. We have designed and developed a novel manipulator along with feed-forward position control to maintain continuous contact with the pipe. the sliding mode controller has been developed for lateral, yaw, and altitude motion control of the aerial platform. the novel forward velocity function is introduced which serves the purpose of smooth tracking along with maintaining a pipe in the reachable space of the manipulator. the fully autonomous operation strategy has been designed to organize subtasks sequentially with feedback. During the tracking of a pipeline, the lateral and altitude position of pipe with respect to the manipulator's base did not deviate beyond ± 0.2m. Fully autonomous sensor-based control of aerial manipulator has been validated experimentally on a 10-meter-long pipeline.

关键词： Laser radar Tracking Pipelines Position control Inspection Manipulators Robot sensing systems

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