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检索条件"任意字段=5th International Conference on Informatics in Control, Automation and Robotics"

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Modelling Baby's Health Management System Using Rule-Based Algorithm 5

Modelling Baby's Health Management System Using Rule-Based A...

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5th international conference on Robotic automation System 2021, ICORAS 2021

作者： Ismail, Rohana Binti Abd. Wahab, Fauziah Binti Wan Awang, Wan Suryani Binti Azizan, Azilawati Binti Binti Rusli, Intan Shafiza Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kampus Besut Terengganu Malaysia Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Branch Tapah Campus Perak Malaysia

In Malaysia, the growth of a new-born baby is recorded in a health handbook. the data in the handbook is consistently monitored through the information attained by nurses and doctors. Details such as the baby's weight, height, immunization schedule and growth development are all recorded into the handbook. On that account, the handbook needs to be brought when having an appointment as it is recorded manually and handwritten by nurses and doctors alike. However, in some cases the probability of losing the handbook is high, hence important information such as the child's appointment dates and health data can be overlooked and missed by parents and caregivers. Moreover, with the loss of key data, parents may face difficulties identifying symptoms that might present on their baby. therefore, this study has developed a system to record all of the necessary data. It was modelled using a rule-based algorithm to assess the condition of a baby based on their symptoms, the system includes a postpartum confinement module to support mother's regarding their postpartum confinement practices. the system also serves as a reminder for parents regarding their baby's next vaccination appointment. Results shows that the system is able to improve the disadvantages of the old manual approach, allowing for maximum data storage while reducing data entering discrepancies. By using a rule-based approach, the system can model a baby's health state and keep track of immunisation schedules as well as deliver friendly reminders to parents and caregivers if the need arises. © Published under licence by IOP Publishing Ltd.

关键词： Handbooks

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Research on Multi-depth-of-field Electronic Image Stabilization Algorithm for In-Vehicle Videos

Research on Multi-depth-of-field Electronic Image Stabilizat...

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

作者： Xuewen Qiu Huawei Liang Jie Wang Junsen Jing Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China University of Science and Technology of China Hefei China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Innovation Research Institute of Robotics and Intelligent Manufacturing (Hefei) Chinese Academy of Sciences Institutes of Physical Science and Information Technology Anhui University Hefei China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

the vehicle-mounted cameras provide video streaming information for the post-processing phase of the intelligent vehicle, such as control and decision making. According to the characteristics of in-vehicle videos, this paper studies a video stabilization algorithm considering different depths of field. On the motion estimation stage, for the problem of inaccurate estimation inter-frame motion vectors caused by different depths of field of feature points, this paper proposes a method to repair inter-frame motion vectors. the method can correct the feature point position of the current frame and improve the estimation accuracy of the global motion vector. In the motion smoothing phase, a real-time online optimization framework and adaptive weights are used to balance the relationship between motion smoothing and motion following. Experiments prove that the accuracy of motion estimation of the algorithm in this paper is better than other improved algorithm, and the average value of PSNR after video stabilization is increased by more than 3dB compared with the original videos.

关键词： Smoothing methods Intelligent vehicles Motion estimation Decision making Estimation Streaming media Maintenance engineering

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Automated Suckering of Vines with a Mobile Robot and a Torque-controlled Suckering Tool 5

Automated Suckering of Vines with a Mobile Robot and a Torqu...

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5th IEEE international conference on Smart Systems and Technologies, SST 2022

作者： Stuhne, Dario Vatavuk, Ivo Hrabar, Ivan Vasiljević, Goran Kovačić, Zdenko University of Zagreb Faculty of EE&C Zagreb Croatia University of Zagreb LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing Zagreb10000 Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

the research presented in this paper focuses on the development of fully automated and autonomous vine suckering, a seasonal viticulture activity required to remove all unwanted shoots from the vine trunks. this requires human workers to do a lot of strenuous work, often using only their hands or tools such as clippers or shears. the suckering is done during the early growing season (usually April-May) to provide more energy, water, and nutrients to the main shoots. Commercially available suckering machines appear to be a large-scale solution. However, their performance varies between 10% and 85% and their purely mechanical nature can easily cause damage to the vines. In this paper, we present a concept for autonomous suckering using a mobile robot equipped with a special suckering tool driven by a torque-controlled DC motor that protects the vine from damage. the proposed suckering system was designed, analysed and experimentally validated in a real vineyard. the results showed that the system was able to remove about two thirds of the unwanted shoots, reaching a suckering rate of more than 86 vines per hour. © 2022 IEEE.

关键词： Mobile robots

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Deep Learning with Transfer Learning Method for Error Compensation of Cable-driven Robot 17

Deep Learning with Transfer Learning Method for Error Compen...

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17th international conference on informatics in control, automation and robotics (ICINCO)

作者： Akhmetzyanov, Aydar Rassabin, Maksim Maloletov, Alexander Fadeev, Mikhail Klimchik, Alexandr Innopolis Univ Ctr Technol Robot & Mechatron Components Innopolis Russia

ISBN: (纸本)9789897584428

this paper proposes the application of Deep Learning methods for kinematic error compensation. Particular attention is paid to simulation-based error estimation and the use of the Transfer Learning method for error compensation to reduce physical experiments with a real robot. the obtained results were applied and validated for 4-dof (degrees of freedom) cable-driven parallel robot. the problem of error compensation for the cable-driven parallel robot is highly non-linear. Nevertheless, deep learning-based methods for a considerable training dataset provides better accuracy than simple linear error compensators. To overcome this drawback, we applied the transfer learning method and used the knowledge of robot kinematics simulated in Unity. Unity cable-driven robot simulation was implemented, and the central hypothesis was verified first in the simulated environment. the proposed Transfer Learning method allowed to speed up the process of robotics system integration and recalibration due to the significant sample efficiency improvement.

关键词： Cable-driven Robot Kinematics Compensation Deep Learning Transfer Learning robotics

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Auto-generated control Program in Mobile Robot using Grammatical Evolution 22

Auto-generated Control Program in Mobile Robot using Grammat...

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Proceedings of the 8th international conference on robotics and Artificial Intelligence

作者： Firdaus Sukarman Eisuke Kita Graduate School of Informatics Nagoya University Japan

ISBN: (纸本)9781450397544

Complexity of robot control program is become a problem as variety of robot used today is dramatically increased due to demand of automation. Several studies has been made using GE to solve robot tasks but application in actual environment is still lack of proof. In this research, auto-generated control program using Grammatical Evolution (GE) is proposed to resolve the burden of constructing manually adjusted control program that consider both physical condition of robot and input from sensors. Grammatical Evolution (GE) is a genetic programming that map genotype to phenotype using predetermined grammar. As GE is subset to Genetic Programming which produce heuristics solution, the grammar-based algorithm enable the search range evolve in a set of rules. this search strategy can be applied to build the structure of control program which consists of multiple sets of program blocks with adjustable parameter. this system is evaluated using Santa Fe Trail problem with open world configuration. the results show the usability of the algorithm by manipulating crossover and mutation rates. Another important factors that effect the performance of the algorithm is the grammar that can govern the evolution of the control program. the proposed method able to generate control automatically with sets of rules determined using grammar.

关键词： Grammatical Evolution (GE) Context-based Knowledge BNF Grammar

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Trends in robotics and Computer Integrated Manufacturing

Trends in Robotics and Computer Integrated Manufacturing

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international conference on Contemporary Computing and informatics (IC3I)

作者： Anil Kumar Dixit T. Vijaya Kumar Abhishek Joshi Harpreet Singh Bedi M. Kalyan Chakravarthi Devesh Pratap Singh Department of LCD Uttaranchal University Dehradun India Department of Mechanical Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Uttaranchal University Uttarakhand India. School of electronics and electrical engineering Lovely Professional University Jalandhar Punjab School of Electronics Engineering VIT - AP University Amaravati Andhra Pradesh Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

Today, all manufacturing businesses are expected to have the ability to produce high-quality goods with shorter lead times and the capacity to produce to a variety of customer specifications. Any industry’s production capacity has increased exponentially as a result of the use of robots in manufacturing. To resolve the aforementioned problems and maintain a nation’s revenue in the fiercely competitive international market, robotics and computer integrated manufacturing (CIM) technology are required. the main emphasis is placed on the robot’s accuracy during milling operations, and its capacity to carry out the work with the required precision is assessed. the manipulator stiffness model is utilized to estimate failures in conformity caused by the baseline cutting force, which is the same for all robots under consideration, in order to calculate this performance metric. the feasibility of the suggested method was demonstrated in experimental research including the milling of circular notches using a robot for a variety of workgroup samples and locations. As cutting force increases, the circularity index raises as well, and it may be calculated by simple scaling. the study suggests a system that is focused on the industry and allows users to rate industrial robots according to their machining precision. Some industrial robots from the KUKA family that have been graded for various machining jobs are used to test the established methodology.

关键词： Measurement Industries Service robots Force Computer integrated manufacturing Milling Manipulators

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Depression detection using machine learning techniques on twitter data 5

Depression detection using machine learning techniques on tw...

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5th international conference on Intelligent Computing and control Systems, ICICCS 2021

作者： Govindasamy, Kuhaneswaran Al Palanichamy, Naveen Faculty of Computing and Informatics Multimedia University Cyberjaya Selangor63000 Malaysia

ISBN: (纸本)9781665412728

Depression has become a serious problem in this current generation and the number of people affected by depression is increasing day by day. However, some of them manage to acknowledge that they are facing depression while some of them do not know it. On the other hand, the vast progress of social media is becoming their 'diary' to share their state of mind. Several kinds of research had been conducted to detect depression through the user post on social media using machine learning algorithms. through the data available on social media, the researcher can able to know whether the users are facing depression or not. Machine learning algorithm enables to classify the data into correct groups and identify the depressive and non-depressive data. the proposed research work aims to detect the depression of the user by their data, which is shared on social media. the Twitter data is then fed into two different types of classifiers, which are Naïve Bayes and a hybrid model, NBTree. the results will be compared based on the highest accuracy value to determine the best algorithm to detect depression. the results shows both algorithm perform equally by proving same accuracy level. © 2021 IEEE.

关键词： Facings

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Supernumerary Robotic Fingers for Assistance in Cylindrical and Pinch Grasps

Supernumerary Robotic Fingers for Assistance in Cylindrical ...

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international conference on Bio-engineering for Smart Technologies (BioSMART)

作者： Renato Mio Alejandro Morveli Department of Engineering Laboratory of Biomechanics and Applied Robotics Pontificia Universidad Católica del Perú Peru Chair of Digital Health University of Bayreuth Germany School of Science and Engineering Pontificia Universidad Católica del Perú Lima Peru

Grasping impairments constitute a major limitation that affects the performance in many activities of daily life. Current assistive devices, such as hand exoskeletons, are designed to aid patients by giving them the additional assistance force necessary to close the hand and grip objects. However, this often results in improvement of only power grasps (such as cylindrical and spherical grasps), but not precision grasps. Another alternative for assisting hand function is to “augment” the hand with additional robotic fingers. these supernumerary robotic fingers can assist the hand grasping function by performing a grip in coordination with the palm (analogous to an extra thumb) or by performing grasps on their own when there are two or more extra fingers. this work presents an assistive device comprising two supernumerary robotic fingers aimed for people with hand grasping limitations. the extra fingers can assist in performing power grasps such as cylindrical in conjunction with the user’s palm or performing precision grasps such as pinch grasp. the fingers are actuated by servomotors and their positions are controlled by commands derived from the wearer’s wrist movements. Hence, this new design seeks to assist people through an easy-to-operate interface that avoids the use of joints unrelated to the motor task and thus provides natural control for the patient.

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Optimal Preview Distance control Using Model Prediction for Autonomous Vehicle 5

Optimal Preview Distance Control Using Model Prediction for ...

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5th CAA international conference on Vehicular control and Intelligence, CVCI 2021

作者： Li, Cheng Chen, Weihuang Luo, Xinkai Wang, Fangfang Zhang, Jingmin Yang, Yanlong Sun, Hongbin Xi'an Jiaotong University Institute of Artificial Intelligence and Robotics Xi'an China No.208 Research Institute of China Ordnance Industries China

ISBN: (纸本)9781665408462

the performance of the autonomous driving control system is the key to the stability and safety of autonomous vehicles. As part of the control system, path tracking is responsible for tracking the desired trajectory. this article proposes a multi-point preview method based on the model prediction, which uses the preview distance obtained by the Stanley path tracking method to interpolate back and forth to obtain candidate preview points, which are converted into steering angles through geometric relations. Finally, selecting the optimal steering angle is selected through the designed optimal function. Different from the traditional kinematics model, this paper also predicts the steering angle at the next moment to achieve more accurate vehicle state prediction. In this way, the proposed method is well compared and analysed with the traditional Stanley controller scheme. Comparing with the proposed method, the traditional Stanley controller is not capable of keeping the steering stable as it faces the road with changeable curvature. the results show that the implementation of model predictive multi-point preview control strategy for Stanley tracking effectively improves the stability and accuracy of tracking. © 2021 IEEE.

关键词： Autonomous vehicles

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Analytical Overview on Transfer Learning in Processing Dental X-rays 22

Analytical Overview on Transfer Learning in Processing Denta...

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5th international conference on control and Computer Vision, ICCCV 2022

作者： Al Mokdad, Seba Al Houria, Anas Abu Talib, Manar Moufti, Mohammad Bouridane, Ahmed Nasir, Qassim College of Computing and Informatics Department of Computer Science University of Sharjah United Arab Emirates

ISBN: (纸本)9781450397315

Dental x-rays have been a standard piece of dental equipment for many years and are an indispensable diagnostic tool for dentists to detect tooth damage or disease. Recent research has focused on employing computer vision algorithms to automate analysis of dental x-rays. Our study aims to review the work done using transfer learning in dental image processing. AI solutions for dental images have been developed for many purposes, including examining tooth cavities (caries) and restorations and abnormalities in the maxillary sinuses. they have also been used to classify dental implants and determine gender in forensic studies. Transfer Learning is a new approach that is being used to solve a problem that classic deep learning and machine learning techniques could not solve: that of data limitation. Our search has investigated 80 research papers, of which 30 were relevant and analyzed in this paper. the identified studies have discussed a variety of transfer learning models to process different types of x-rays and have reported their efficacy using a variety of metrics. Transfer learning was used to solve various problems depending on the research question. Some papers compared the performance of transfer learning with that of dental experts in analyzing x-ray images, the accuracy of which were surprisingly close to equal. Although the results of the majority of dental applications performed using transfer learning models are encouraging, future research will need to solve the shortcomings highlighted in the present review. © 2022 ACM.

关键词： Diagnosis

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