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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331-340 订阅

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UAV Control System with Time to Collision (TTC) Prediction Capability 11th

UAV Control System with Time to Collision (TTC) Prediction C...

引用

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

作者： Sabikan, Sulaiman Nawawi, Sophan Wahyudi Aziz, Nor Azlina Ab. Fakulti Teknologi Kejuruteraan Elektrik dan Elektronik Centre for Robotics and Industrial Automation Universiti Teknikal Malaysia Melaka Durian Tunggal Malaysia Faculty of Engineering School of Electrical Engineering Universiti Teknologi Malaysia Skudai Malaysia Faculty of Engineering and Technology Multimedia University Melaka Malaysia

ISBN: (纸本)9789811681288

this paper presents the development of an Unmanned Aerial Vehicle (UAV) control system simulation with collision avoidance prediction capability using the Time-to-Collision (TTC) model. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. Flight mission data collected from the quadcopter testbed platform experiments in the real environment in order to develop TTC model. the horizontal ground speed, throttle magnitudes, and flight time stamp are downloaded from the onboard quadcopter, filtered, analyzed, and optimize using Particles Swarm Optimization (PSO) algorithm to find the optimal TTC model. this model provides predictions of time before UAV will collide with the obstacle in the same path based on their current parameters, for instance, current speed and payload. this development of UAV’s control system implemented in Matlab/Simulik. the PID-based controller is utilized to stabilize the quadcopter and collision avoidance control systems with the TTC model to assist the system in order to avoid a collision from happening. Simulation tests performed proved the capability of UAV to stop at a safe distance and avoid collisions with the obstacles that existed based on TTC model prediction during flight successfully. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Collision avoidance

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Detection and Positioning of Workpiece Grinding Area in Dark Scenes with Large Exposure 1

引用

16th international conference on Intelligent robotics and Applications, ICIRA 2023

作者： Guo, Zhentao Zhao, Guiyu Bian, Jinyue Ma, Hongbin School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Workpiece grinding is a crucial process in the smart manufacturing chain. In order to meet the requirements of industrial precision and relieve heavy work, researchers have developed a vision-based grinding robot. However, the problem of workpiece grinding area detection and positioning is difficult to be solved in dark scenes with large exposure. this paper proposes a method that fuses technologies such as processing of the image, coordinate and point cloud, which can accurately detect and locate the workpiece grinding area. Firstly, A method based on YOLOv7 and improved image preprocessing is used to detect labels of the grinding area. Secondly, A model for the prediction of the coordinates based on multiple linear regression was used to predict the coordinates of missing labels for the same grinding area. Finally, Data processing of the point cloud and transformation of the system of coordinates are used to achieve the acquisition of the coordinates of positioning vertices in the grinding area and conversion from the camera coordinate system to the world coordinate system. We used several sets of data for evaluation in our experiments, and the experimental results show that our proposed method can effectively detect the workpiece grinding area. At the same time, our method can also predict the coordinates of missing labels, which provides a more stable and reliable guarantee for industrial production. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Multiple linear regression

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Onboard Real-Time Object Detection for UAV with Embedded NPU 11

Onboard Real-Time Object Detection for UAV with Embedded NPU

引用

11th IEEE Annual international conference on CYBER Technology in automation, Control, and Intelligent systems, CYBER 2021

作者： Chen, Long Hu, Jingyi Li, Xuanfu Quan, Fengyu Chen, Haoyao School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Huawei Technology Co. Ltd Department of HiSilicon Research China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9781665425278

Unmanned aerial vehicles (UAVs) endowed with the function of computer vision are widely applied. there is an urgent need to implement real-Time object detection. However, the limited memory and computing capacity of current embedded devices prevent the deployment of deep learning on UAVs. therefore, this paper proposes an efficient onboard object detection system based on an embedded NPU device. It can be deployed on a UAV to perform real-Time scenario analysis. Firstly, a deep-learning network structure based on YOLOV3-Tiny is designed for object detection. then it is compressed by a novel pruning strategy to obtain a 'slim' object detector. Finally, a detection-reinitialization mechanism is introduced to realize the robust output of detection. the experimental results demonstrate that our model and algorithm achieve efficient performance of detection compared to the unoptimized benchmark. the proposed model achieves up to 0.591 mAP with a 6M parameter size. the complete system is tested in both simulation and real environments of the aerial manipulator grasping task. the effective detection frame ratio reaches 90%, and FPS achieves about 25. © 2021 IEEE.

关键词： Object detection

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Neural Sliding Mode Control using Neural Disturbance Observer for Gyroscopes

Neural Sliding Mode Control using Neural Disturbance Observe...

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robotics, Control and automation Engineering (RCAE), international conference on

作者： Luoyu Zhang Zhiwei Wen Xinsong Zhang Yunxiang Guo Cheng Lu College of Electrical Engineering Nantong University Nantong China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

In this paper, a neural network sliding mode control based on neural network disturbance observer is proposed for the control of MEMS gyroscopes under external disturbances. In the design process, two sets of RBF neural networks are incorporated in the sliding mode controller design as well as the disturbance design separately to release the dependence of each module on gyroscope system parameters. Meanwhile, the integration of the neural disturbance observer can help to alleviate chattering phenomenon in conventional sliding mode control forces. Simulation studies are implemented to verify the effectiveness of the proposed control scheme.

关键词： Micromechanical devices automation Process control Interference Radial basis function networks Disturbance observers Gyroscopes

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Event-Triggered Fault Detection and Control in Generalized Internal Model Control Framework

Event-Triggered Fault Detection and Control in Generalized I...

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robotics, Control and automation Engineering (RCAE), international conference on

作者： Suichun Qu Jingsong Wu Weijie Guo Bin Chen School of Electrical and Energy Engineering Nantong Institute of Technology Nantong China School of Electrical Engineering Nantong University Nantong China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Business Nantong Institute of Technology Nantong Nantong China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

the paper investigates the design of event-triggered fault detection and control in the framework of Generalized Internal Model Control (GIMC). Inspired by the GIMC structure, an observer-based feedback control structure with a fault detection unit is firstly proposed, where the event-triggered technology is also employed to reduce the communication consumption between the monitored plant and the observer. then, since the separation principle is destroyed by the use of the event-triggered technology, the augmented system approach is used to design the observer-based controller. Further, a robust post-filter is designed, under the H-/H∞performance index, to guarantee that the residual (fault indicating) signal satisfies the optimized robustness against disturbances under the desired sensitivity to faults. Finally, a three-tank system is adopted to verify the effectiveness and superiority of the proposed scheme.

关键词： State feedback Sensitivity Fault detection Observers Continuous time systems Robustness Sensors

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Application of Automatic Welding System on Aluminum Alloy Corbel

Application of Automatic Welding System on Aluminum Alloy Co...

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robotics, Control and automation Engineering (RCAE), international conference on

作者： Dongnan Su Cuihong Wu Xijia Tao Lei Wang Yongfu Hai Yang Cong College of Mechanical and Electrical Engineering Changchun College of Electronic Technology Changchun China Technical Quality Department Changchun CRRC Punching Equipments Co.Ltd. Changchun China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

the body corbel is the link of traction transmission between train and bogie. It is a key component on the car body that bears both tensile and compressive loads. Its strength and stiffness have an important impact on the safety and reliability of vehicle operation. In this paper, according to the structural and technological requirements of aluminum alloy corbel products,A research plan for an automated welding system with high productivity and good welding quality was developed. through the comparison of welding quality between manual welding and automatic welding system, the advantages of automatic welding system are summarized.

关键词： Productivity automation Welding Manuals Aluminum alloys Manipulators Safety

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LiDAR Point Cloud Map Coding Framework Based on Quadric Surface Fitting and Scene Construction

LiDAR Point Cloud Map Coding Framework Based on Quadric Surf...

引用

Pattern Recognition and Machine Learning (PRML), IEEE international conference on

作者： Xuebin Sun Jinxi Wang Xiaofei Yang School of Electrical Automation and Information Engineering Tianjin University Tianjin China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Department of Aerospace Laser Technology and System Shanghai Institute of Optics and Fine Mechanics Shanghai China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

Due to rapid 3D acquisition advancements, LiDAR point clouds are prevalent in emerging applications like heritage preservation, mobile robotics, and remote sensing. Yet, the sheer data volume poses challenges for transmission and storage, especially in autonomous driving. this paper introduces an efficient coding framework for compressing large dense LiDAR point cloud maps. By recording timestamps and quaternion matrices during map construction, we reduce map compression to sequence compression. the scans are segregated into intra-frames and inter-frames. For intra-frames, a quadric surface fitting intra-prediction technique eliminates spatial redundancy. For inter-frames, by constructing the 3D scene using encoded intra-frames, the inter-frame can be simulated according to its posture and LiDAR intrinsic parameters. Coding focuses on the difference between actual and predicted point cloud data. Decoding reverses this process, reconstructing the point cloud map from the decoded sequence and quaternion matrices. KITTI dataset experiments show the point cloud map can be averagely compressed to 3.43% of its original size while maintaining centimeter-level precision. this outperforms both octree and Google Draco methods.

关键词： Point cloud compression Surface reconstruction Laser radar three-dimensional displays Quaternions Fitting Robot sensing systems Surface fitting Encoding Surface treatment

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A Novel Approach for Porcupine Crab Identification and Processing Based on Point Cloud Segmentation 20

A Novel Approach for Porcupine Crab Identification and Proce...

引用

20th international conference on Advanced robotics (ICAR)

作者： Wu, Haodong Zou, Ting Burke, Heather King, Stephen Burke, Brian Mem Univ Newfoundland Fac Engn & Appl Sci Dept Mech Engn St John NL A1C 5S7 Canada Mem Univ Newfoundland Ctr Aquaculture & Seafood Dev Fisheries & Marine Inst St John NL A1C 5R3 Canada Nunavut Fisheries Assoc NFA Nunavut ON X0A 0H0 Canada

ISBN: (纸本)9781665436847

Despite the increasing application of automated processing equipment in commercial seafood industry, such as large-scale Latin fish and snow crab production lines, manual laboring method dominates in current seafood processing, resulting in low production rate and increased cost. Among various types of seafood crabs, porcupine crabs have shown potential for quality marketable crab meat products. However, their long, sharp spines pose significant challenges for manual laboring and thereby call for robust automated system for processing. In this paper, using 3D point cloud data of the porcupine crab as the input, a novel robot-based approach is proposed to generate the robot trajectory for spine removal. this approach has been validated via a simulation example using ROS (Robot Operating systems). the proposed method can be introduced into many other manufacturing processing, including polishing, painting, grinding and deburring for work pieces with complex surfaces.

关键词： automation

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Research on Target Assignment Strategy of Multi-fighter and Multi-target Air Combat

Research on Target Assignment Strategy of Multi-fighter and ...

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robotics, Control and automation Engineering (RCAE), international conference on

作者： Yunqing Li Qiuni Li Zongcheng Liu Unit 94638 of the PLA Nanchang China Aviation Engineering School Air Force Engineering University Xi'an China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

Aiming at the problem of target assignment strategy of multi-fighter and multi-target air combat, the angle, distance, speed and energy factors are considered to establish the multi-fighter air combat target allocation model, and the theory of relative optimal genus degree is introduced to calculate the comprehensive threat matrix in this paper., the zero-sum game method, the virtual regret minimization game method, the nearest neighbor attacking method and the threat ranking method are designed to make the decision of target allocation. the comparison experimental results show that the virtual regret minimization game method is close to the actual air combat situation, and has the optimization effect on the target allocation decision.

关键词： automation Atmospheric modeling Games Minimization Resource management Game theory Robots

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Hyperparameter Tuning of Convolution Neural Network for Paddy Leaves Disease Detection 5

Hyperparameter Tuning of Convolution Neural Network for Padd...

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5th international conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Yusoff, C.M.Y.A. Che Mat Nadzri, N.Z. Yusoff, Y. UniKL Robotics and Industrial Automation Center Universiti Kuala Lumpur Malaysia France Institute Selangor Bangi Malaysia

the traditional approach to identifying paddy leaf diseases in Malaysia's agriculture sector involves visual inspection by farmers or agricultural experts. However, this method heavily relies on human expertise to recognize visual symptoms like discoloration, spots, or lesions on the leaves, leading to subjective assessments and delayed diagnosis. While various deep learning models have been utilized to detect paddy leaf diseases, there is a need for a more comprehensive discussion on the appropriate hyperparameters setting. this study focused on utilizing Convolutional Neural Network (CNN) models, specifically ResNet and VGG architectures, to identify paddy leaf diseases in Sekinchan, Selangor. the models were trained on a dataset consisting of both online and real-world images, which underwent several augmentation processes to enhance the model's robustness. the study has highlighted the optimal hyperparameters of the CNN model, resulting in an impressive accuracy rate of 98.71% and a minimal loss rate of 0.001. the integration of the final model into a specific Graphical User Interface has further enhanced its utility. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Graphical user interfaces

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