2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)最新文献_第3页

A Novel Defect Inspection Approach Based on Self-attention Convolutional Adversarial Auto-Encoder 一种基于自关注卷积对抗自编码器的缺陷检测新方法

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995893

Jian Wang, Yakun Li, Zhiyan Han

{"title":"A Novel Defect Inspection Approach Based on Self-attention Convolutional Adversarial Auto-Encoder","authors":"Jian Wang, Yakun Li, Zhiyan Han","doi":"10.1109/RCAE56054.2022.9995893","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995893","url":null,"abstract":"Defect inspection based on computer vision has gradually replaced the traditional detection method, which is widely used in industry and greatly improving the efficiency of industrial production. Most defect inspection methods use supervised learning, which require vast amounts of label images for training. However, the complete defect inspection task is challenging due to some problems, such as diversity of defects, high similarity defects (e.g., low contrast, ambiguous boundary and small background difference) and large defect scale. To solve the above problems, a novel unsupervised defect inspection approach with Self-attention Convolutional Adversarial Auto-Encoder (SCAAE) is proposed in this paper, based on the encoder-decoder-discriminator structure. In this approach, we improve the encoder and decoder via the self-attention mechanism to enhance the feature extraction ability of convolutional autoencoder (CAE), and then the discriminator helps SCAAE impose the latent variable to cluster by a prior distribution. Finally, large number of experiments on four datasets demonstrate the effectiveness of SCAAE and outperforms state-of-the-art methods.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132902518","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: 1

Research on Part Edge Detection Algorithm Based on Deep Learning 基于深度学习的零件边缘检测算法研究

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9996046

Wang Zhou, Weibo Yu, Hongtao Yang

引用次数: 3

Research on Mobile Robot Path Planning Based on IHBS-A* Algorithm 基于IHBS-A*算法的移动机器人路径规划研究

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995923

Hongbo Li, Hong Zheng, Gang Liu, Jianwei Guo

{"title":"Research on Mobile Robot Path Planning Based on IHBS-A* Algorithm","authors":"Hongbo Li, Hong Zheng, Gang Liu, Jianwei Guo","doi":"10.1109/RCAE56054.2022.9995923","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995923","url":null,"abstract":"With the rapid development of mobile robot robots over the years, path planning has become one of the key technologies for mobile robot applications. Although the traditional A* algorithm has high search efficiency and fast computing speed, the planned paths are easy to collide with obstacles, have more inflection points and redundant nodes, and the robot keeps turning in the process of actual operation, which seriously affects the efficiency of robot operation, so this paper proposes the improved algorithm IHBS-A* (Improve heuristic, Bidirectional node and Smoothing path): for the safety problem by improving the heuristic function and introducing safety coefficient, which makes the mobile robot keep a certain For the safety problem, the heuristic function is improved and the safety factor is introduced to make the mobile robot keep a certain safety distance from the obstacles. The results show that the IHBS-A* algorithm not only retains the advantages of the fast computing speed of A*, but also makes the path safer, and the path is smoother, and shorter, which improves the efficiency of the mobile robot.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116791416","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: 1

Forward Kinematics Solution for Stewart and TBBP: A Neural Network Approach Based on LSTM Stewart和TBBP的正解:基于LSTM的神经网络方法

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9996010

Qiming Wang, Muyu Xue, Jian Su, Qiyuan Liu, Boqiang Chen, Ming Fang

{"title":"Forward Kinematics Solution for Stewart and TBBP: A Neural Network Approach Based on LSTM","authors":"Qiming Wang, Muyu Xue, Jian Su, Qiyuan Liu, Boqiang Chen, Ming Fang","doi":"10.1109/RCAE56054.2022.9996010","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9996010","url":null,"abstract":"Aiming the problems of the traditional numerical method for solving the pose forward kinematics of parallel mechanism, which relies heavily on the initial value of iteration, has low accuracy and offers poor real-time performance, this article thus proposed a method combining LSTM (Long-Short-Term Memory) prediction model with inverse kinematics solution of parallel mechanism. This method takes the typical Stewart platform (SP) and the test bench for bogie parameters (TBBP) as sample robots. First, the constraint conditions of the two mechanisms were considered in order to obtain the workspace for each; the pose inverse solution Simulink models for both mechanisms were then generated. Second, given the motion posture in the workspace, the telescopic amount of the driving rod can be obtained. Then the data corresponding to the time series of the 6-DOF pose and the telescopic amount was taken as sample training data for LSTM in the next step. Finally, RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) were applied as optimisation indexes to determine the optimal structural parameter combinations of LSTM networks to analyse the prediction effects for both the SP and TBBP mechanisms under a circular trajectory, a spiral trajectory, and 0∽5 Hz linear sweep vibration trajectory. The results showed that the order of magnitude of RMSE of the prediction models for both mechanisms was 10–4 for both the circular and spiral trajectory, especially the RMSE for TBBP was 10–5 for the spiral trajectory, a MAPE of just 0.0013%. Comparing the above-fixed frequency trajectory, the RMSE and MAPE under the 0∽5Hz linear variable frequency trajectory are 0.0931 and 4.45% respectively; The prediction results for both structures meet the stated accuracy requirements and verify that the proposed LSTM prediction method offers both strong universality and good rationality.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129184605","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: 1

Design of Directional Bird Dispersal Device in Substation Based on Infrared Sensing 基于红外传感的变电所定向放鸟装置设计

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995817

Hanwu Luo, Shikuan Chen, Wenzhen Li, Fang Li, Yifeng Song, Fengren Jing, Zhenyu Yang

{"title":"Design of Directional Bird Dispersal Device in Substation Based on Infrared Sensing","authors":"Hanwu Luo, Shikuan Chen, Wenzhen Li, Fang Li, Yifeng Song, Fengren Jing, Zhenyu Yang","doi":"10.1109/RCAE56054.2022.9995817","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995817","url":null,"abstract":"In order to reduce the impact of bird activities on the operation of power equipment, important power stations such as substations and converter stations are equipped with dispelling birds devices that can continuously output acoustic, optical and electrical signals for dispelling birds. However, due to the lack of target orientation for dispelling birds, birds can quickly produce adaptability, resulting in a significant decline in the effect of dispelling birds. In this paper, a directional dispersal device for substation birds based on infrared sensing is designed for directional aiming dispelling birds. Firstly, an improved image template matching method is used to complete the identification and location of bird targets. Then bird's directional tracking and dispersion control algorithm based on PID is proposed. Finally, the experiment proves that the device has the characteristics of high positioning accuracy and fast-tracking speed for the dispersal of birds, which can quickly and effectively dispel moving birds accurately.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126485817","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: 1

A Design Method of Transmission Line Sag Measurement Robot 输电线路垂度测量机器人的设计方法

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995915

Guofang Huang, Bin Zhang, Dongliang Xue, Xiaoming Liu, Xiangqin Wen, Jianguo Hou

引用次数: 1

Research on Target Assignment Strategy of Multi-fighter and Multi-target Air Combat 多机多目标空战目标分配策略研究

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995982

Yunqing Li, Qiuni Li, Zongcheng Liu

引用次数: 1

The Design of Cathode Copper Quality Inspection System Based on Machine Vision 基于机器视觉的阴极铜质量检测系统设计

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995964

Juan Lin, Yuan Yuan, Yongjing Wang

{"title":"The Design of Cathode Copper Quality Inspection System Based on Machine Vision","authors":"Juan Lin, Yuan Yuan, Yongjing Wang","doi":"10.1109/RCAE56054.2022.9995964","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995964","url":null,"abstract":"in order to meet the market requirements for the surface quality of cathode copper, a copper plate surface quality detection system based on machine vision is designed. The surface quality of cathode copper is judged by image acquisition and processing. According to the actual production conditions of a cathode copper production workshop in Guangxi and the characteristics of the cathode copper itself, the hardware equipment related to the Jetson nano and camera are selected to ensure that the images that can meet the processing requirements are collected. The Yolo algorithm is used to train the target detection, feature extraction and target recognition on the Linux system to obtain a data set. The data set trained by the computer is run on the Jeston nano micro controller, After the CSI camera collects the image data, the data is compared and displayed on the LCD1602. The detection system can increase the efficiency to automatically judge whether the product quality is qualified, solve the problems of low manual detection accuracy and large amount of labor, and realize the full-automatic production of cathode copper.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131449576","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: 1

An Improved YOLOv5s for Lane Line Detection 一种改进的YOLOv5s车道线检测方法

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995995

Xiaohui Lu, Xinzhan Lv, Junchen Jiang, Shaosong Li

引用次数: 0

Position Tracking Control of a Mobile Vehicle-Manipulator System with Disturbances 具有扰动的移动车辆-机械手系统的位置跟踪控制

2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE) Pub Date : 2022-10-28 DOI: 10.1109/RCAE56054.2022.9995856

Fang Guo, Yi Qin, Fujie Wang

引用次数: 1