J. Robotics最新文献_第9页

A MultiModal Detection Method for UHV Substation Faults Based on Robot Inspection and Deep Learning 基于机器人检测和深度学习的特高压变电站故障多模态检测方法

J. Robotics Pub Date : 2022-04-23 DOI: 10.1155/2022/1188617

Rong Meng, Zhao-lei Wang, Zhiqian Zhao, Jian-peng Li, W. Fu

{"title":"A MultiModal Detection Method for UHV Substation Faults Based on Robot Inspection and Deep Learning","authors":"Rong Meng, Zhao-lei Wang, Zhiqian Zhao, Jian-peng Li, W. Fu","doi":"10.1155/2022/1188617","DOIUrl":"https://doi.org/10.1155/2022/1188617","url":null,"abstract":"Aiming at the problem of multi-modal fault detection of different equipment in ultrahigh voltage (UHV) substations, a method for based on robot inspection and deep learning is proposed. First, the inspection robot is used to collect the image data of different devices in the station and the source data is preprocessed by standard image augmentation and image aliasing augmentation. Then, the HSV color space model based on saliency area detection is used to extract equipment defect areas, which improves the accuracy of defect image classification. Finally, the traditional YOLOv3 network is improved by combining the residual network and the K-means clustering algorithm, and the detailed flow of the corresponding detection method is proposed. The proposed detection method and the other three methods were compared and analyzed under the same conditions through simulation experiments. The results show that the detection accuracy and recall rate of the method proposed in this study are the largest, which are 95.9% and 91.3%, respectively. The average detection accuracy under multiple intersection ratio thresholds is also the highest, and the performance is better than the other three comparison algorithms.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122739090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Personalized Travel Route Recommendation Model Using Deep Learning in Scenic Spots Intelligent Service Robots 基于深度学习的景区智能服务机器人个性化旅游路线推荐模型

J. Robotics Pub Date : 2022-04-21 DOI: 10.1155/2022/3851506

Qili Tang

引用次数: 1

The Flight Mechanism of a Bird-like Flapping Wing Robot at a Low Reynolds Number 类鸟扑翼机器人低雷诺数飞行机理研究

J. Robotics Pub Date : 2022-04-18 DOI: 10.1155/2022/6638104

Changtao Ding, Xiating Yao, Chengyao Liu

引用次数: 0

Support Vector Machine and Granular Computing Based Time Series Volatility Prediction 基于支持向量机和粒度计算的时间序列波动率预测

J. Robotics Pub Date : 2022-04-16 DOI: 10.1155/2022/4163992

Yuan Yang, Xu Ma

{"title":"Support Vector Machine and Granular Computing Based Time Series Volatility Prediction","authors":"Yuan Yang, Xu Ma","doi":"10.1155/2022/4163992","DOIUrl":"https://doi.org/10.1155/2022/4163992","url":null,"abstract":"With the development of information technology, a large amount of time-series data is generated and stored in the field of economic management, and the potential and valuable knowledge and information in the data can be mined to support management and decision-making activities by using data mining algorithms. In this paper, three different time-series information granulation methods are proposed for time-series information granulation from both time axis and theoretical domain: time-series time-axis information granulation method based on fluctuation point and time-series time-axis information granulation method based on cloud model and fuzzy time-series prediction method based on theoretical domain information granulation. At the same time, the granulation idea of grain computing is introduced into time-series analysis, and the original high-dimensional time series is granulated into low-dimensional grain time series by information granulation of time series, and the constructed information grains can portray and reflect the structural characteristics of the original time-series data, to realize efficient dimensionality reduction and lay the foundation for the subsequent data mining work. Finally, the grains of the decision tree are analyzed, and different support vector machine classifiers corresponding to each grain are designed to construct a global multiclassification model.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"117 23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126411765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Obstacle Detection and Distance Measurement Method for Sloped Roads Based on VIDAR 基于VIDAR的斜坡道路障碍物检测与距离测量方法

J. Robotics Pub Date : 2022-04-15 DOI: 10.1155/2022/5264347

Guoxin Jiang, Yi Xu, Xiao-Jin Gong, Shanshan Gao, Xiaoqing Sang, Ruoyu Zhu, Liming Wang, Yuqiong Wang

{"title":"An Obstacle Detection and Distance Measurement Method for Sloped Roads Based on VIDAR","authors":"Guoxin Jiang, Yi Xu, Xiao-Jin Gong, Shanshan Gao, Xiaoqing Sang, Ruoyu Zhu, Liming Wang, Yuqiong Wang","doi":"10.1155/2022/5264347","DOIUrl":"https://doi.org/10.1155/2022/5264347","url":null,"abstract":"Environmental perception systems can provide information on the environment around a vehicle, which is key to active vehicle safety systems. However, these systems underperform in cases of sloped roads. Real-time obstacle detection using monocular vision is a challenging problem in this situation. In this study, an obstacle detection and distance measurement method for sloped roads based on Vision-IMU based detection and range method (VIDAR) is proposed. First, the road images are collected and processed. Then, the road distance and slope information provided by a digital map is input into the VIDAR to detect and eliminate false obstacles (i.e., those for which no height can be calculated). The movement state of the obstacle is determined by tracking its lowest point. Finally, experimental analysis is carried out through simulation and real-vehicle experiments. The results show that the proposed method has higher detection accuracy than YOLO v5s in a sloped road environment and is not susceptible to interference from false obstacles. The most prominent contribution of this research work is to describe a sloped road obstacle detection method, which is capable of detecting all types of obstacles without prior knowledge to meet the needs of real-time and accurate detection of slope road obstacles.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123736979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Fault Diagnosis Method of Distribution Equipment Based on Hybrid Model of Robot and Deep Learning 基于机器人与深度学习混合模型的配电设备故障诊断方法

J. Robotics Pub Date : 2022-04-14 DOI: 10.1155/2022/9742815

Shan Rongrong, Ma Zhenyu, Ye Hong, Lin Zhenxing, Qiu Gongming, Ge Chengyu, L. Yang, Yu Kun

{"title":"Fault Diagnosis Method of Distribution Equipment Based on Hybrid Model of Robot and Deep Learning","authors":"Shan Rongrong, Ma Zhenyu, Ye Hong, Lin Zhenxing, Qiu Gongming, Ge Chengyu, L. Yang, Yu Kun","doi":"10.1155/2022/9742815","DOIUrl":"https://doi.org/10.1155/2022/9742815","url":null,"abstract":"In view of the poor effect of most fault diagnosis methods on the intelligent recognition of equipment images, a fault diagnosis method of distribution equipment based on the hybrid model of robot and deep learning is proposed to reduce the dependence on manpower and realize efficient intelligent diagnosis. Firstly, the robot is used to collect the on-site state images of distribution equipment to build the image information database of distribution equipment. At the same time, the robot background is used as the comprehensive database data analysis platform to optimize the sample quality of the database. Then, the massive infrared images are segmented based on chroma saturation brightness space to distinguish the defective equipment images, and the defective equipment areas are extracted from the images by OTSU method. Finally, the residual network is used to improve the region-based fully convolutional networks (R-FCN) algorithm, and the improved R-FCN algorithm trained by the online hard example mining method is used for fault feature learning. The fault type, grade, and location of distribution equipment are obtained through fault criterion analysis. The experimental analysis of the proposed method based on PyTorch platform shows that the fault diagnosis time and accuracy are about 5.5 s and 92.06%, respectively, which are better than other comparison methods and provide a certain theoretical basis for the automatic diagnosis of power grid equipment.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131878136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Design Method of Intelligent Ropeway Type Line Changing Robot Based on Lifting Force Control and Synovial Film Controller 基于提升力控制和滑膜控制器的智能索道式换线机器人设计方法

J. Robotics Pub Date : 2022-04-12 DOI: 10.1155/2022/3640851

Jiazhen Duan, Ruxin Shi, Hongtao Liu, Hailong Rong

{"title":"Design Method of Intelligent Ropeway Type Line Changing Robot Based on Lifting Force Control and Synovial Film Controller","authors":"Jiazhen Duan, Ruxin Shi, Hongtao Liu, Hailong Rong","doi":"10.1155/2022/3640851","DOIUrl":"https://doi.org/10.1155/2022/3640851","url":null,"abstract":"Aiming at the problems of low efficiency, reliability, and safety of manual construction for demolition of old lines, a design method of an intelligent ropeway type line changing robot based on lifting force control and synovial film controller is proposed. First, the mechanical model of robot load and line sag is established, and the sag of the overhead line where the robot is located is used to calculate the jacking force that the jacking device needs to provide to the robot. Then, by introducing the radial basis function (RBF) neural network adaptive algorithm into the synovial controller, an adaptive sliding mode position control algorithm based on the RBF neural network is designed to achieve high-precision motion control of the robot in complex operating environments. Finally, based on the compactness, weight, and reliability of the robot, the optimal design is carried out from four aspects of topology, size, shape and morphology, and the design scheme of the robot for wire removal is proposed, and the robot is produced. The developed robot and the other three robots are compared and analyzed under the same conditions through simulation experiments. The results show that the maximum operating time, maximum climbing angle, and maximum traveling speed of the robot developed in this study are all optimal, which are 45 min, 10°, and 1 m/s respectively, and the performance is better than the other three comparison algorithms.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115507321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Compliant Mechanism Soft Robot Design and Peristaltic Movement Optimization Using Random Search 柔性机构软机器人设计及随机搜索蠕动运动优化

J. Robotics Pub Date : 2022-04-12 DOI: 10.1155/2022/7562164

L. A. Páramo-Carranza, A. López-González, Juan C. Tejada

引用次数: 2

Controlling Hybrid Machine Tools concerning Error Compensation of Chain Elements 基于链单元误差补偿的混合动力机床控制

J. Robotics Pub Date : 2022-04-07 DOI: 10.1155/2022/4366888

Quoc-Khanh Duong, Thuy Le-Thi-Thu, Thanh-Long Pham, Ngoc Nong-Minh

{"title":"Controlling Hybrid Machine Tools concerning Error Compensation of Chain Elements","authors":"Quoc-Khanh Duong, Thuy Le-Thi-Thu, Thanh-Long Pham, Ngoc Nong-Minh","doi":"10.1155/2022/4366888","DOIUrl":"https://doi.org/10.1155/2022/4366888","url":null,"abstract":"This paper introduces a methodology for controlling parallel robots in case they are used as a kind of specialized fixture to expand the technological capabilities of machines. The parallel robot is mounted on the workbench to extend the number of degrees of freedom. However, there are always measurable kinematic errors of the workbench which will be eliminated by the robot’s motion. The actual working motion of the robot is then still performed by its active joints. Therefore, the displacement of each movable joint is now decided by two sources, one is due to the error compensation motion of the workbench, the other is the required work movement. According to the superposition principle, these two motions are combined into a single displacement characteristic curve to control the robot. The base exchange technique to determine the error compensation motion of the workbench, the technique of solving the inverse kinematics problem by the generalized reduced gradient (GRG) method, and the principle of joint motion combination are then introduced in detail in the paper. Finally, an example with the hexapod is presented. The obtained results, which use the robot itself to generate error-compensated movements of the workbench by means of the base exchange technique, will open up the possibility of intervening in hybrid machine systems to ensure the desired forming accuracy without no hardware intervention required.","PeriodicalId":186435,"journal":{"name":"J. Robotics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126078514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resource Optimization Technology Using Genetic Algorithm in UAV-Assisted Edge Computing Environment 无人机辅助边缘计算环境下基于遗传算法的资源优化技术

J. Robotics Pub Date : 2022-04-06 DOI: 10.1155/2022/3664663

Huijuan Sun, Hongqi Xi

引用次数: 2