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

共 1360 条记录，以下是481-490 订阅

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Using Entropy Estimation to Detect Moving Objects 5

Using Entropy Estimation to Detect Moving Objects

引用

5th IEEE international conference Actual Problems of Unmanned Aerial Vehicles Developments, APUAVD 2019

作者： Kondratieva, I.U. Rudakova, H.V. Polyvoda, O.V. Lebedenko, Yu.O. Polyvoda, V.V. Automation Kherson National Technical University Robotics and Mechatronics Department Kherson Ukraine Kherson State Maritime Academy Ship Electrical Equipment and Automatic Devices Operation Department Kherson Ukraine

ISBN: (纸本)9781728125923

the article is devoted to the problems of analysis of the informative part of acoustic signals in the UAV control system. A method of determining the frequency range of the informative part of a signal based on the estimation of the normalized energy spectrum and spectral entropy is proposed. the sequence of steps for determining the range of the informative part of the signal, consisting of the calculation of the spectrum of the signal and the normalized energy spectrum, its digital processing, the calculation of the entropy of the spectrum, the median smoothing, logic-time processing. the results of experimental acoustic signal processing for different frame length values are analyzed. Graphic representations of the acoustic signal, spectral entropy values and logic function are given. © 2019 IEEE.

关键词： Entropy

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Glaucoma Detection: Joint Segmentation and Classification Framework via Deep Ensemble Network

Glaucoma Detection: Joint Segmentation and Classification Fr...

引用

international conference on Advanced robotics and Mechatronics (ICARM)

作者： Siyu Li Zhen Li Limin Guo Gui-Bin Bian Beijing University of Technology Beijing PR China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

Clinical research shows that glaucoma is primarily caused by pathological changes in the optic nerve structure, which may bring about irreversible damage of sight. In relevant literature research, the cup-to-disc ratio (CDR) is mainly used as an important indicator for glaucoma detection, which needs to segment optic disc (OD) and optic cup (OC) region clearly and accurately. However, due to the low contrast image of boundary, the segmentation of OD and OC is still a challenging problem. In this paper, a novel hybrid model based on the ensemble random-forest deep-neural-network (RF-DNN) is proposed for OD and OC segmentation, which can calculate more accurately for glaucoma detection. At the same time, the advantages of DNN and ensemble RF are combined to carry out the corresponding feature extraction and classification, which employs the winner-takes-all strategically to the segmentation and classification for glaucoma detection. Finally, the experiment result shows that the proposed method has reached the best evaluation level in terms of OD and OC segmentation results on ORIGA dataset and SCES dataset, which achieves highest diagnosis accuracy with AUC of 0.96 and 0.98 on ORIGA dataset and SCES dataset, respectively.

关键词： Feature extraction Image segmentation Training Optical imaging Decoding Neural networks Robots

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Autonomous Cloud Robotic System for Smart Agriculture 5

Autonomous Cloud Robotic System for Smart Agriculture

引用

Moratuwa Engineering Research conference (MERCon) / 5th international Multidisciplinary Engineering Research conference

作者： Dharmasena, tharindu de Silva, Rajitha Abhayasingha, Nimsiri Abeygunawardhana, Pradeep Sri Lanka Inst Informat Technol Dept Comp Syst Engn Malabe Sri Lanka Sri Lanka Inst Informat Technol Dept Elect & Elect Engn Malabe Sri Lanka

ISBN: (纸本)9781728136325

Agriculture sector occupies 25.9% of the world employment. the demand for food production is rapidly increasing with the increase of world population. Developing the existing agricultural infrastructure by incorporating modern technologies will help to match this increasing demand. this paper proposes a automated system to optimally control the climate and irrigation in a greenhouse by monitoring temperature, soil moisture, humidity and pH through a cloud connected mobile robot which can detect the unhealthy plants using image processing. A fuzzy controller will control the heating and cooling system, irrigation system and humidifiers installed in the greenhouse based on the sensor readings. the mobile robot navigates through a predefined map of the greenhouse and collect soil samples to perform measurements while onboard sensors will collect the ambient climate data. A camera mounted on the mobile robot will capture the plant and detect unhealthy crops based on the colour and the texture of the leaves.

关键词： Cloud robotics Smart Agriculture Internet of things Monitoring automation

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Performance Evaluation of Main Steam Temperature Control System of thermal Power Unit Based on Mahalanobis Distance

Performance Evaluation of Main Steam Temperature Control Sys...

引用

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

作者： Boyong Hu Jianbo Xie Yusheng He Yinsong Wang Pingyan Ma Zhejiang key Laboratory of High efficiency Energy Saving and Pollutant Control Technology for Thermal Power Generation Zhejiang Energy Technology Research Institute Co.Ltd. Zhejiang Energy Group Co.Ltd. Automation department North China Electric Power University

ISBN: (数字)9781728198880

ISBN: (纸本)9781728198897

As the main parameter of thermal power unit, the measurement and control of main steam temperature play an important role in the safe and economic operation of power plant. In order to improve the control quality of main steam temperature control system of thermal power unit, this paper presents a performance evaluation method of main steam temperature control system of thermal power unit based on Mahalanobis distance. this method is based on the output data of leading steam temperature and main steam temperature. Firstly, the data set representing the best performance of the system is selected according to Hurst index, and the benchmark of performance evaluation is established based on this data. then the calculation process of traditional Mahalanobis distance is improved, and the specific calculation method of performance evaluation index based on the combination of Hurst index and improved Mahalanobis distance is given. Finally, the performance evaluation index is classified by membership function. the simulation results show that the evaluation method is effective and reasonable and the calculation is simple.

关键词： main steam temperature performance evaluation Mahalanobis distance Hurst index

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Design and testing of automated tube-based hydroponic system

Design and testing of automated tube-based hydroponic system

引用

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

作者： Nihong Liu Zheng Xiong Can Xu Yufa Wu Huiling Li Xianping Jiang Junfeng Cheng Facilities Agricultural Equipment Technology Research and Development Center Guangdong Institute of Modern Agricultural Equipment

ISBN: (数字)9781728198880

ISBN: (纸本)9781728198897

Tube-based hydroponics is one of the main production methods of greenhouse gardening in China. the traditional tube-based hydroponics method is labor intensive, inefficient, and labor costly to sustain. In this paper, an automated tube-based hydroponics system was designed, consisting of a longitudinal conveying mechanism, a transverse conveying mechanism, and a cleaning and disinfection mechanism, which can complete the automatic conveying of planting tubes, cleaning and disinfection of planting tubes, and realize the automatic production of leafy vegetables. In addition, key components for planting tube slope were designed and prototype preparation and performance testing were studied. the results showed that the prototype's longitudinal conveying success rate was 100% with an average period of 2.09 s and transverse conveying success rate was 98.67% with an average period of 12.17 s. the prototype performance met the agronomic requirements. this equipment provides the technical basis for the unmanned production of piped hydroponic leafy vegetables.

关键词： automation tube-based hydroponic system greenhouse horticulture nutrient film technique

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Image Matching Algorithm based on ORB and K-Means Clustering

Image Matching Algorithm based on ORB and K-Means Clustering

引用

Information Science, Computer Technology and Transportation (ISCTT), international conference on

作者： Liye Zhang Fudong Cai Jinjun Wang Changfeng Lv Wei Liu Guoxin Guo Huanyun Liu Yixin Xing School of Computer Science and Technology Shandong University of Technology Zibo China Electric Power Automation Division Shandong Senter Electronic Zibo China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China Jinan Xintongda Electronic Technology Co. Ltd Jinan China

ISBN: (数字)9781728185750

ISBN: (纸本)9781728185767

With the rapid development of science and technology, image processing technology plays an important role in the field of computer vision. In order to improve the matching speed and real-time requirements, this paper proposes an image matching algorithm based on ORB and K-means clustering, which can effectively improve the accuracy of image feature point location and the accuracy and efficiency of image feature matching, and reduce the time consumption. the algorithm uses sub-pixel interpolation to optimize the traditional ORB algorithm, which improves the accuracy and characteristics of clustering calculation.

关键词： Interpolation Information science Image matching Clustering algorithms Transportation Real-time systems Stereo vision

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Monocular SLAM Initialization Using Epipolar and Homography Model

Monocular SLAM Initialization Using Epipolar and Homography ...

引用

IEEE international conference on Control and robotics Engineering (ICCRE)

作者： Maaz Mohammed Butt Hai Zhang XiaoChen Qiu Baoshuang Ge School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9781728167916

ISBN: (纸本)9781728167923

the performance of the initialization module for any visual Simultaneous Localization and Mapping (SLAM) algorithm is crucial in determining the overall accuracy of the navigation solution. this paper proposes an automatic real time initialization module based on a heuristic algorithm which is a model selection method that provides robustness for both non-planar and planar initial scenes using the epipolar and homography geometry respectively. Initialization is made more robust by utilizing features comprising of lines, edges and corner points in a scene adaptive method so that there is a balance between the trade-off of computation speed and accuracy of the algorithm. the proposed algorithm has been effectively used to initialize map and showed to improve the pose estimation and tracking of the state of the art visual odometry algorithm by simulation over benchmark datasets. the executable code implementation of the proposed initialization module has been made open source publically to provide as a valuable reference for the students of SLAM at https://***/maazmb/***.

关键词： Simultaneous localization and mapping Computational modeling Robustness Feature extraction Image edge detection Optical flow Transmission line matrix methods

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Industrial Robot Grasping with Deep Learning using a Programmable Logic Controller (PLC)

Industrial Robot Grasping with Deep Learning using a Program...

引用

IEEE international conference on automation Science and Engineering (CASE)

作者： Eugen Solowjow Ines Ugalde Yash Shahapurkar Juan Aparicio Jeff Mahler Vishal Satish Ken Goldberg Heiko Claussen Siemens AUTOLAB at University of California Berkeley Ambidextrous Laboratories Inc

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Universal grasping of a diverse range of previously unseen objects from heaps is a grand challenge in e-commerce order fulfillment, manufacturing, and home service robotics. Recently, deep learning based grasping approaches have demonstrated results that make them increasingly interesting for industrial deployments. this paper explores the problem from an automation systems point-of-view. We develop a robotics grasping system using Dex-Net, which is fully integrated at the controller level. Two neural networks are deployed on a novel industrial AI hardware acceleration module close to a PLC with a power footprint of less than 10 W for the overall system. the software is tightly integrated with the hardware allowing for fast and efficient data processing and real-time communication. the success rate of grasping an object form a bin is up to 95% with more than 350 picks per hour, if object and receptive bins are in close proximity. the system was presented at the Hannover Fair 2019 (world's largest industrial trade fair) and other events, where it performed over 5,000 grasps per event.

关键词： Grasping automation Service robots Machine learning Robot sensing systems Software

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Research on water quality prediction method based on AE-LSTM

Research on water quality prediction method based on AE-LSTM

引用

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

作者： Huiqing Zhang Kemei Jin School of Automation Department of Informatics Beijing University of Technology

ISBN: (数字)9781728198880

ISBN: (纸本)9781728198897

Aiming at the traditional prediction methods of related parameters that affect water quality, they usually only consider the temporal characteristics of the related parameters of water quality and ignore the problem that water quality changes are multivariate related, A prediction method of spatiotemporal correlation water quality parameters based on automatic encoder(AE) dimensionality reduction and long and short time memory(LSTM) neural network is proposed. Firstly, considering that water quality parameter changes have obvious time characteristics, a time series prediction model of water quality parameters is established based on LSTM. Secondly, considering that the water quality changes have multiple correlations, the upstream water quality will also affect the downstream water quality. If all the water quality parameters of the upstream station are added to the prediction model, redundant features will reduce the accuracy of parameter prediction. therefore, the automatic encoder is used to reduce the dimensionality of the relevant parameters. Finally, the data set of Lang fang Water Quality Automatic Monitoring Station is applied to monitor the effectiveness of the method. By predicting the concentration of total phosphorus(TP) and total nitrogen(TN), the method is found to have better prediction accuracy and robustness.

关键词： long-short-term memory network auto-encoder water quality prediction feature extraction multivariate correlation

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automation of Shopping Carts using Technology 5

Automation of Shopping Carts using Technology

引用

5th IEEE international conference for Convergence in Technolog, I2CT 2019

作者： Aiswarya Padma, B. Aravindakshan, Arun Prakash, Amal College of Engineering Thiruvananthapuram India Rajiv Gandhi Institute of Technology Thiruvananthapuram India Sree Buddha College of Engineering Thiruvananthapuram India

ISBN: (纸本)9781538680759

the advancements and developments in the field of innovative and creative thinking have played a pivotal role in kick-starting a whole new phase of technology - Internet of things (IoT). A lot of research is being done in the line of robotics and artificial intelligence, all of which has helped us think of a very effective and economical means of reducing manual labor in our day to day activities. We found our inspiration in a supermarket. Moving shopping carts manually can sometimes become too tedious to control, especially for the elderly and physically disabled. the objective of our work was to solve a major problem of existing shopping carts, which is that they rely on manual labor to move. Our cart uses the principles of image processing to map itself to one particular user using a pattern tag and follows the user based on single object tracking and the distance sensed by ultrasonic sensors interfaced with a Raspberry Pi. © 2019 IEEE.

关键词： Ultrasonic sensors

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