2018 International Conference on Robots & Intelligent System (ICRIS)最新文献

{"title":"Maritime Intelligent Real-Time Control System Based on UAV","authors":"Rui Huang","doi":"10.1109/ICRIS.2018.00011","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00011","url":null,"abstract":"Through the analysis of deficiencies of current maritime UAV control applications, and in terms of complicated geographical, meteorological, and electromagnetic conditions in maritime control areas and also intelligent, real-time, and digital requirements on modern maritime control, a comprehensive maritime UAV intelligent real-time control system of resistance to wind and water, safe landing, real-time control, and instant responsible is developed to realize functions such as automatic detection of ships violating rules, water area intelligent monitoring, automatic tracking ships violating rules and obtaining evidence, water transportation order control, and water area pollution monitoring. The purpose is to build a maritime control system characterized by \"full coverage and fully intelligent control\" and further to enhance the maritime control capability and service level.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124146735","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}

{"title":"Navigation and Positioning System Applied in Underground Driverless Vehicle Based on IMU","authors":"Jinbao Guo, Jingyi Du, Dandan Xu","doi":"10.1109/ICRIS.2018.00012","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00012","url":null,"abstract":"A position coordinate measuring system for the multisource information fusion of underground moving trains based on IMU inertial navigation system is proposed in order that the underground location technology of wireless sensor network (WSN) is difficult to arrange the anchor nodes and with the shortages of high cost and low location accuracy in the complex environment of coal mines, The system uses ARM processing chip, combined with NAV2 inertial navigation unit and PNP photoelectric velocity sensing, using wireless network to achieve real-time interaction with the upper monitor, to eliminate the cumulative error effect of IMU positioning in the mine by the method of beacon information location calibration. Experimental results show that the average positioning accuracy of this system is 0.25m and the positioning accuracy is 98.6%, which can meet the requirement of sub-meter high-precision navigation and positioning of unmanned vehicles in the mine.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131061068","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}

{"title":"Research on Application of Healthcare Data in Big Data Era","authors":"Hengyu Cai, Hang Zhao, Yutao Liu, Guijie Li","doi":"10.1109/ICRIS.2018.00100","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00100","url":null,"abstract":"This article takes healthcare big data as the research object. It firstly introduces the source of healthcare big data, summarizes the current application status of healthcare big data, and analyzes the opportunities and challenges facing medical big data thoroughly. The development of big data and processing technologies has enriched the data foundation and analysis methods for healthcare big data analysis. The healthcare big data still faces challenges in the aspects of data cleaning, data security, personnel training, and platform development.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129806710","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}

{"title":"Design of Visual Feature Detection System for Intelligent Driving of Electric Vehicle","authors":"Nie Jin","doi":"10.1109/ICRIS.2018.00010","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00010","url":null,"abstract":"In order to improve the intelligent driving ability of electric vehicles, the optimization design of the visual feature detection system for electric vehicles is carried out. An intelligent driving visual detection algorithm for electric vehicles is proposed based on edge contour feature extraction and visual information fusion. The distributed sensor technology is used to collect the intelligent driving visual information of electric vehicle, and the principal component analysis and image filtering are carried out according to the collected image information. The edge contour of the filtered driving visual image is detected, the high resolution visual image feature is extracted, and the quantized fusion tracking recognition is carried out according to the extracted feature quantity. The hardware design of the detection system is obtained under the embedded environment. Simulation result shows that the system designed in this paper has good accuracy in detecting the visual features of intelligent driving of electric vehicles. The system is robustness and has good human-computer interaction.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121548237","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}

{"title":"Research and Application of Traffic Sign Detection and Recognition Based on Deep Learning","authors":"Canyong Wang","doi":"10.1109/ICRIS.2018.00047","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00047","url":null,"abstract":"Nowadays, with the rapid development of society and economy, automobiles have become almost one of the convenient modes of transport for every household. This makes the road traffic environment more and more complicated, and people expect to have an intelligent Vision-assisted applications that provide drivers with traffic sign information, regulate driver operations, or assist in vehicle control to ensure road safety. As one of the more important functions, traffic sign detection and recognition[1], has become a hot research direction of researchers at home and abroad. It is mainly the use of vehicle cameras to capture real-time road images, and then to detect and identify the traffic signs encountered on the road, thus providing accurate information to the driving system. However, the road conditions in the actual scene are very complicated. After many years of hard work, researchers have not yet made the recognition system practical, and further research and improvement are still needed. Traditionally, traffic signage has been detected and categorized using standard computer vision methods, but it also takes considerable time to manually process important features of the image. With the development and progress of science and technology, more and more scholars use deep learning technology to solve this problem. The main reason that the deep learning method is widely accepted is that the model can learn the deep features inside the image autonomously from the training samples, especially for many cases that do not know how to design the feature extractor, such as expression recognition, target detection Wait. Based on the application of road traffic sign detection and recognition, this article focuses on the correctness and high efficiency of detection and recognition. Through Caffe[2] which is the open-source framework, a deep convolution neural network algorithm is proposed to train traffic sign training sets to get a model that can classify traffic signs and to learn and identify the most critical of these traffic signs Features, so as to achieve the purpose of identifying traffic signs in the real scene.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123890194","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}

{"title":"Research of Sub-Pixel Inner Diameter Measurement of Workpiece Based on OpenCV","authors":"Xuefei Yan, Gang Jing, Ming-Gao Cao, Chao Zhang, Yan Liu, Xiaohao Wang","doi":"10.1109/ICRIS.2018.00098","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00098","url":null,"abstract":"A method of untouched measurement based on OpenCV is proposed to achieve the sub-pixel inner diameter Measurement of workpiece. Design and implement a visual measurement system on the inner diameter Measurement of workpiece. In the image, the grayscale of the noise and the aim is very close and very hard to be separated by the right threshold. To this difficult point, a method of two thresholds in two steps is proposed. First, remove the background noise with a smaller threshold; second, get the binarization image close to the real contour of the aim with a bigger threshold. The system deals with the image binarization, the interception of region of interest, contour extraction and so on, finally achieves the high-precision inner diameter measurement of workpiece. Repeat the measurement many times of the workpiece in different place in the field of view, the experimental results show that the consistency of the method is better than the HALCON machine vision software.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128998361","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}

{"title":"Research on Logistic Regression Algorithm of Breast Cancer Diagnose Data by Machine Learning","authors":"Lei Liu","doi":"10.1109/ICRIS.2018.00049","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00049","url":null,"abstract":"If machine learning can automatically identify cancer cells, it will provide considerable benefits to the medical system. The process of automation is likely to improve the efficiency of the detection process, and it may also provide higher detection accuracy by removing the internal subjective human factors in the process. Starting from the measurement data of biopsy cells in women with abnormal breast masses, logistic regression algorithm is applied to study the efficiency of machine learning for cancer detection. In this paper, the LogisticRegression algorithm of Sklearn machine learning library is used to classify the data sets of breast cancer (diagnosis). The classification results show that when the two features of maximum texture and maximum perimeter are selected, the classification accuracy is 96.5%, which is improved compared with the previous methods.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133943761","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}

{"title":"Robot Path Planning Based on Improved Ant Colony Optimization","authors":"Huang Shuyun, Tang Shoufeng, Song Bin, Tong Minming, Jiang Mingyu","doi":"10.1109/ICRIS.2018.00015","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00015","url":null,"abstract":"Aiming at the problem of global path planning of robots under static and complicated environment, firstly, the working environment of the robot is modeled by the grid method, and then the ant colony optimization is introduced. After analyzing the basic principle of the algorithm, this paper proposes a robot path planning scheme. Finally, the simulation experiment and analysis verify the validity and practicability of the improved algorithm.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133621746","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}

{"title":"Design and Implementation of CORDIC Algorithm Based on FPGA","authors":"Xiaoyuan Wang","doi":"10.1109/ICRIS.2018.00026","DOIUrl":"https://doi.org/10.1109/ICRIS.2018.00026","url":null,"abstract":"This paper uses FPGA to design and implement CORDIC algorithm. Defining 16-bit data to complement switch, then it can calculate the sinusoidal value, cosine value and tangent value for any angle by CORDIC coordinate rotation algorithm, and gets the results close to the exact data through multiple iterations. The design is completed in QuartusII integrated development environment, and the RTL code simulation test is carried out on ModelSim. The angle value of each quadrant can be calculated effectively by using external control circuit and LCD screen. The simulation results and demonstration results verify the authenticity and validity of the CORDIC algorithm in this design.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115512077","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}

{"title":"The Application of Artificial Intelligence for Optimizing Energy Balance Energy Smart Buildings Integrated in the Smart Area","authors":"Bohumír Garlík","doi":"10.1109/icris.2018.00083","DOIUrl":"https://doi.org/10.1109/icris.2018.00083","url":null,"abstract":"The article describes the optimization unit commitment of renewable energy sources (RES) distributed in the electric micro-grid of a fictitious Smart Cities composed of an intelligent buildings complex, both residential and offices, including a wide range of public facilities. In connection with the solution of this task, the optimized heuristic technique of simulated annealing is then generally described as one of the methods of evolutionary algorithms. Afterwards, a computer program is designed to conduct and discuss the optimization task demonstrating the computational experiment.","PeriodicalId":194515,"journal":{"name":"2018 International Conference on Robots & Intelligent System (ICRIS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127096660","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}