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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

共 1356 条记录，以下是241-250 订阅

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Improved 2D LiDAR Adaptive Matching Localization Method Based on Gradient Features

Improved 2D LiDAR Adaptive Matching Localization Method Base...

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

作者： Wenyang Zhang Ping Li Wenjie Yu Guoliang Zhang School of Automation Chengdu University of Information Technology Chengdu China

Aiming at the problem that the 2D LiDAR reflective intensity feature of reflector in indoor laser multilateral localization is easily affected by the environment, which makes the multilateral localization method ineffective, an improved 2D Li-DAR adaptive matching localization method based on gradient features is proposed. First, the 2D LiDAR detects and generates gradient features in real time after the laser target is prearranged at the indoor edge, and then the laser target is preprocessed by the gradient features. Secondly, the template matrix and feature matrix are constructed and matched in real time to realize the ID adaptive matching of the laser target. Finally, the least squares method is used to solve the robot localization coordinates in the framework of the multilateral localization method. the experimental results show that the method in this paper can solve the environmental limitations of the reflector and 2D LiDAR multi-lateral localization method and maintain its absolute localization advantage, which is characterized by high localization accuracy, stronger robustness and lower cost.

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2022 IEEE 27th international conference on Emerging Technologies and Factory automation, ETFA 2022

2022 IEEE 27th International Conference on Emerging Technolo...

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27th IEEE international conference on Emerging Technologies and Factory automation, ETFA 2022

ISBN: (纸本)9781665499965

the proceedings contain 270 papers. the topics discussed include: 5G RAN slicing to support reliability in industrial applications;a blueprint of digital twins in high volume production environments using the asset administration shell;a civil protection early warning system to improve the resilience of Adriatic-Ionian territories to natural and man-made risk;a coordination artifact for multi-disciplinary reuse in production systems engineering;a digital twin-based approach performing integrated process planning and scheduling for service-based production;a factory planning and design framework for integrating the digital twin in industry 4.0;a framework for safe and intuitive human-robot interaction for assistant robotics;a graph-based knowledge representation and pattern mining supporting the digital twin creation of existing manufacturing systems;a methodology for classifying data relevance to utilize external data sources in the digital twin;a methodology for creating semantic digital twin models supported by knowledge graphs;and a methodology to select wearable devices for industry 5.0 applications.

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Real-time Trajectory Planning for Redundant 7-dof Space Manipulators with Unknown Link Lengths

Real-time Trajectory Planning for Redundant 7-dof Space Mani...

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robotics, Control and automation (ICRCA), international conference on

作者： Jian Liu Zhiqi Li Shicai Shi Minghe Jin State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

Trajectory planning for redundant space manipulators in complex spatial environments is critical for ensuring successful on-orbit task execution, especially when the manipulator’s link lengths are unknown. Traditional algorithms struggle to establish the transformation between task space and joint space under such conditions, posing significant challenges to autonomous trajectory planning. this study proposes a novel trajectory planning method for a seven-degree-of-freedom redundant space manipulator with a shoulder-wrist offset. the method utilizes a trained pose control decision system to generate continuous, smooth, and singularity-free trajectories in real time, satisfying positional and orientational accuracy requirements for target capture. A neural network with strong nonlinear fitting capabilities is employed as the position control decision module for joints 1-4, trained using a "cautious exploration, greedy exploitation" strategy for efficient and safe trajectory optimization. For joints 5-7, an analytical orientation control decision module adjusts the end-effector’s attitude. Together, these modules form a pose control decision system that adheres to constraints on joint angular velocity, acceleration, and singularity avoidance. the proposed approach is validated through simulations in both static and dynamic scenarios, with simulation results confirming its effectiveness.

关键词： Accuracy Trajectory planning Simulation Position control Aerospace electronics Manipulators Control systems Real-time systems Angular velocity Manipulator dynamics

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Dynamic feature elimination method based on target detection and depth information

Dynamic feature elimination method based on target detection...

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Science and Technology Innovation (IAECST), international Academic Exchange conference on

作者： Xunjia Li Zhiming Wang School of Mechanical and Electrical Engineering and Automation Shanghai University Shanghai China

SLAM (simultaneous localization and mapping) technology is a key technology in the field of robotics. Visual SLAM has received widespread attention because of its low cost and rich information. However, traditional SLAM is based on the assumption of static environment. this paper proposes a method to eliminate dynamic feature points in SLAM systems. First, a target detection algorithm is used to obtain potential dynamic points, and then depth information is used to find and eliminate dynamic feature points. Use geometric relationships to check motion consistency, find dynamic frames that are not defined in advance, and use depth information to eliminate dynamic feature points. Only remaining static features are retained in the tracking and optimization module to achieve accurate camera tracking in dynamic environments. Pose estimation. this improves the stability and accuracy of SLAM systems in dynamic environments.

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A Top-View Hand Gesture Recognition System for IoT Applications

A Top-View Hand Gesture Recognition System for IoT Applicati...

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international conference on Smart systems and Inventive Technology (ICSSIT)

作者： William J. Wisener Jorge Diaz Rodriguez Ammy Ovando Christopher Woolford Kishan Patel Dept. of Robotics & Mechatronics Engineering Department of Physics Kennesaw State University Atlanta Georgia

Gesture recognition integrated into Internet of things (IoT) systems is a growing field with opportunities for improvement. Identifying hand gestures from vertical angles with a cooperative network of cameras can enable a broader collection of control methods for controlling IoT devices within residential and commercial environments. Integrating this smart home framework with other IoT control methodologies also creates a more user-friendly experience. To generate a proof of concept of the effectiveness with this control framework, a convolutional neural network was created using the YOLOv7 deep learning architecture and Roboflow software. this image detection network was connected to a simulated IoT device via Home Assistant home automation software and communicates using the MQTT protocol. the gesture detection system was tested on different camera setups to evaluate the importance of camera position and data sharing within a smart-home device network.

关键词： Protocols Deep architecture Gesture recognition Smart homes Cooperative systems Cameras Software

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the Mobility and High Load-to-weight Ratio Oriented Design Criteria of Hybrid Robots

The Mobility and High Load-to-weight Ratio Oriented Design C...

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robotics, Control and automation (ICRCA), international conference on

作者： Bingbing Yuan Hongguang Wang Xinan Pan State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

To solve the problem of hybrid mechanism design with mobility and high load-to-weight ratio constraints, this paper presents a design criterion for the hybrid robots, namely Mobility and High Load-to-weight Ratio(MHLWR)Oriented Design Criteria. Firstly, a new concept, the unit power concentration vector, which represents the anisotropy of power transmission, is proposed. And then, the kinematic model of the mechanism is established based on the screw theory. thirdly, the unit power concentration vector of the hybrid robot is derived in the configuration space. Finally, an evaluation index is defined as the maximal ratio between unit power and power density. the MHLWR design criterion requires the designer to minimize this ratio by designing the configuration to increase the power density. Based on this criterion, a 5 DOF hybrid robot with a high load-to-weight ratio is developed to replace faulty insulators in the substation. Many experiments have been implemented, and the simulation and experimental results show that the MHLWR design criterion is correct and valid.

关键词： Power system measurements Anisotropic magnetoresistance Density measurement Power transmission Kinematics Fasteners Hybrid power systems

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Human-Robot Pose Tracking Based on CNN with Color and Geometry Aggregation 16th

Human-Robot Pose Tracking Based on CNN with Color and Geo...

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16th international conference on Social robotics, ICSR + InnoBiz 2024

作者： Xu, Yue Zhang, Yinlong Liu, Shuai Liu, Yuanhao Liang, Wei He, Hongsheng Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9789819611508

Accurately tracking the robotic arm and human joints is crucial to ensure safety during human-robot interaction. However, traditional pose tracking methods often exhibit insufficient performance and robustness in complex environments. the variations in the robotic arm’s environment and posture make it challenging for traditional methods to accurately capture the positions and posture of its joints. Specifically, when addressing challenges such as high similarity, occlusion, background complexity, and joint recognition failures, they often struggle to provide reliable and accurate results. To address these challenges, this paper proposes a human-robot pose tracking algorithm based on a new convolutional neural network model. To enhance detection accuracy, an improved color detection module is introduced to resolve joint misclassification. A geometric perception module is designed to accurately locate joints even under occlusion. Additionally, innovative iEMA and DBB modules are incorporated. the iEMA module employs edge detection technology to dynamically adjust thresholds for correct matching by improving the edge matching process. the DBB module refines the boundary box parameters for precise localization by introducing adaptive bounding box updates in real-time. this algorithm also integrates human pose recognition, enabling real-time pose recognition, thereby facilitating more intelligent and natural human-robot interaction. the algorithm has been rigorously evaluated on a custom-designed robotic arm platform. Experimental results validate the algorithm’s effectiveness and feasibility. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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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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Deep Learning Methods for Ship Classification: From Visible to Infrared Images

Deep Learning Methods for Ship Classification: From Visible ...

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

作者： Tianci Liu Hengjia Qin Zhuo Zhan Yunpeng Liu Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang China Key Laboratory of Image Understanding and Computer Vision Shenyang Liaoning Province China The Third Military Representative Office of the Air Force Equipment Department in Shenyang Region Shenyang Liaoning Province China

Deep learning methods have achieved excellent performances on visual tasks of target recognition and classification. the rapid development of autonomous seafaring vessels comes up with the requirement to recognize other maritime ships day and night. However, the recognition of ships based on the deep neural networks may not always access the results as expectation when the ships are under the nighttime environment. To this issue, we consider the ship recognition task under the deep learning framework with paired visible images and infrared images. In this article, we propose an end-to-end convolutional network based on visible images and infrared images of the autonomous seafaring vessels. To demonstrate the effectiveness of our model, we choose the V AIS dataset to test the performance of classifying the maritime ships. Experimental results show that the proposed network outperforms the state-of-the-art methods based on the V AIS database.

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Enhance Robotic Process automation Using a Rule-Based Approach 11th

Enhance Robotic Process Automation Using a Rule-Based Approa...

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11th international conference on robotics, Vision, Signal Processing and Power Applications, RoViSP 2021

作者： Chuan, Wu Chia Manickam, Selvakumar Seng, Yeap Wei Wen, Kevin Yeap Khai Universiti Sains Malaysia Penang George Town Malaysia IOTG Intel Technology Sdn. Bhd Penang Bayan Lepas Malaysia

ISBN: (纸本)9789811681288

Robotic Process automation (RPA) is an important research area in the revolution of industrial 4.0 throughout the world. RPA technology can increase manufacturing productivity and reduce cost in the long term. One of the most important facts that exist in existing RPA systems are they are platform dependent. It must be used in a general-purpose operating system environment and cannot be applied to other software systems such as embedded software or BIOS. RPA then captures a screenshot of the desktop graphical user interface display, analyzes the image, determines the next steps or process and then prompts the user to act as keyboard and mouse. this proposed an RPA solution with the intelligence to offload the high processing task via edge or cloud, based on a set of rules. the ability to decide when to offload tasks is the key factor to increase the adoption rate of the industry. this process will be done based on a set of rules. this type of programable rules-based RPA system is essential to provide a wide range of industry needs. the prototype RPA operated on a rules-based approach has demonstrated that it is possible to apply it to different operating *** proposed rule-based RPA algorithm shows the RPA had the intelligence to route th task to the most suitable RPA processing system. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： robotics

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