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

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Fractional Order vs Integer Order Transfer Function Models of a Pendulum

Fractional Order vs Integer Order Transfer Function Models o...

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international conference on automation, automation 2021

作者： Oprzędkiewicz, Krzysztof Rosól, Maciej Żegleń-Wlodarczyk, Jakub Department of Automatic Control and Robotics Faculty of Electrotechnics Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783030748920

The paper presents the comparison of fractional order to integer order transfer function models of physical pendulum. The considered transfer functions describe the behaviour of the system around the lower, stable equilibrium point. Fractional order models are built using ORA approximation. Models were verified using real experimental data. Results of tests show that the fractional order transfer function can correctly describe the physical pendulum. Integer order models are a little bit more accurate, but they require more parameters to identify. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Linear systems

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Approach to Image-Based Segmentation of Complex Surfaces Using Machine Learning Tools During Motion of Mobile Robots 16th

Approach to Image-Based Segmentation of Complex Surfaces Usi...

引用

16th international conference on Electromechanics and robotics "Zavalishin’s Readings", ERZR 2021

作者： Rubtsova, Julia St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences 39 14th Line St. Petersburg199178 Russia

ISBN: (纸本)9789811628139

In development of formation control systems for modular robotic devices, especially relevant is the problem of analysis and, particularly, segmentation of complex surfaces, down which the robotic device will move. An approach based on fine-tuning of a neural network model HRNet was developed to solve the problem of segmentation of complex surfaces. Model fine-tuning was performed based on a custom dataset, which included 15,000 labeled images. The training dataset included the scenes of the following types: scenes with stairways, scenes with even surfaces, scenes with isolated obstacles and with groups of obstacles. Approbation and functional quality assessment of the developed approach were performed based on the test dataset, which included 3000 images with different levels of scene illumination. According to the results of the testing, the developed approach shows decent quality of segmentation on images with even surfaces (IoU = 90.2%) and with stairways (IoU = 71.3%) as well maintains some resilience to the variations in the scene luminosity levels. After fine-tuning, the averaged performance metrics of this neural network model on images with luminosity levels of 100% and 70% increased by 9.1% and 7.3% at average and resulted in 65.5% and 52%, respectively. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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Efficient Load Forecasting Model Assessment for Embedded Building Energy Management Systems

Efficient Load Forecasting Model Assessment for Embedded Bui...

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IEEE international conference on automation, Quality and Testing, robotics, AQTR

作者： Cristina Nichiforov Nicoleta Arghira Grigore Stamatescu Iulia Stamatescu Ioana Fă gă ră san Sergiu Stelian Iliescu Department of Automatics and Industrial Informatics University "Politehnica" of Bucharest

Growing urbanization tendencies have increased the role that buildings play in future energy systems. We present a comparative study of load forecasting methods for large commercial buildings’ energy traces. Forecasts can be used to improve control algorithms at the local and grid level and to devise practical anomaly detection algorithms. The main approaches for classical modeling, machine learning, and deep learning methods are illustrated with considerations for statistical relevance and contextual information. Model parameter design is achieved using heuristics or systematic parameter space searches for robustness. For the available building consumption datasets, two short-term prediction methods are deployed: Seasonal AutoRegressive Integrated Moving Average (SARIMA) and Recurrent Neural Networks (RNN). An extensive evaluation of prediction performance was conducted based on several metrics. The daily load energy forecast for the 7 considered buildings showed higher precision when using RNN methods compared to the SARIMA auto-regressive algorithm. Implementation of the proposed embedded online building management system can be replicated for other buildings.

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Human Following Robot Based on Object Detection for Aerospace Application

Human Following Robot Based on Object Detection for Aerospac...

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Aerospace Electrical Engineering and informatics (ICAAEEI), international conference of Adisutjipto on

作者： Arwin Datumava Wahvudi Sumari Ahnaf Bagus Aryandika Ndaru Atmi Purnami Denny Dermawan Ika Noer Syamsiana Department of Electrical Engineering Cognitive Artificial Intelligence Research Group State Polytechnic of Malang Malang Indonesia Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Navigation Instrumentation Control Automation and Robotics System Research Group Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Digital System Microprocessor Microcontroller and Programmable Logic Devices Research Group Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia

ISBN: (数字)9798331507930

ISBN: (纸本)9798331507947

In this research, the Human Following Robot (HFR) prototype has been designed and implemented using YOLO v3-Tiny and Tensor Flow Lite on Raspberry Pi hardware named Rewang. The HFR Rewang is designed to assist aircraft technicians by bringing maintenance tool kits to aircraft shelters. Rewang's movement is based on a camera as a vision sensor following the movement of human entities. Image input is processed by YOLO v3-Tiny through the determination of the bounding box, the calculation of Euclidean Distance, and the determination of the pixel value of the camera as the basis of Rewang's movement which is regulated by an L298N driver motor that controls two Direct Current (DC) motors for the left and right wheels. The test results show that Rewang can move at an average speed of 0.18 m/s at 2 m with a travel time of 11 seconds with a light intensity of more than 250 lux. The minimum and maximum distance of object detection is as far as 120 cm and 400 cm, with an object detection accuracy of 95.8%. Rewang allows the HFR to have a larger carrying capacity to bring more complete aircraft maintenance tools and is prospective for other aerospace and general applications.

关键词： YOLO Tensors Accuracy Prototypes Wheels Cameras Hardware Maintenance Aircraft Aerospace industry

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Simultaneous control of Two robotics Arms Sharing Workspace via Visual Predictive control 16th

Simultaneous Control of Two Robotics Arms Sharing Workspace ...

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16th international conference on informatics in control, automation and robotics, ICINCO 2019

作者： Le Flécher, E. Durand-Petiteville, A. Cadenat, V. Sentenac, T. CNRS LAAS 7 Avenue du Colonel Roche Toulouse31400 France Univ de Toulouse UPS Toulouse31400 France Department of Mechanical Engineering Federal University of Pernambuco UFPE Recife Brazil

ISBN: (纸本)9783030631925

This work addresses the problem of simultaneously controlling two robotic arms to automatically pick up fruits in an orchard. When considering such a scenario, the design of the controller has to face several challenges: (i) the arms share the same workspace, (ii) the presence of obstacles such as branches and other fruits, and (iii) the system evolves in a dynamic environment, i.e., the positions of the fruits and branches change over time. In this paper, it is proposed to control the two robotic arms relying on a Visual Predictive control (VPC) scheme. It allows to control the system in a reactive fashion while taking into account a large number of constraints. The global and local models of the VPC scheme as well as constraints dealing with collisions or joint boundaries are presented. Finally, the efficiency of the proposed approach is highlighted with numerous simulation results using the PR2 arms model. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fruits

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Automated Water Quality Monitoring System for Aquaponic Pond using LoRa TTGO SX1276 and Cayenne Platform 4

Automated Water Quality Monitoring System for Aquaponic Pond...

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4th IEEE international conference of Computer Science and Information Technology, ICOSNIKOM 2022

作者： Silalahi, Alfriska Oktarina Sinambela, Amsal Pardosi, Jekson T.N. Panggabean, Hans Mawito Institut Teknologi Del Department of Informatics and Electrical Engineering Toba Samosir Indonesia

ISBN: (纸本)9798350399073

Freshwater aquaculture inland areas with a densely stocked fish pond system requires higher pond maintenance. Two factors support the success of aquaculture in densely stocked freshwater fish ponds, namely the feeding system that must be appropriate and scheduled and the water quality in the pool must be in good condition. However, the problem that often arises is the quality of pool water that is not properly monitored and requires a large amount of money if it has to use human power. This certainly affects the productivity of fish yields. In this study, a smart automation system was designed and implemented to perform water quality control in aquaponics ponds. The method that was used is controlling the oxygen content of the pond water through an aerator pump and controlling the ammonia level of the pond water by utilizing ammonia reduction by pakcoy plants in aquaponic system ponds. This system is accessed through the Cayenne website and the microcontroller used is LoRa TTGO SX1276 and the mechanical feed ejection system uses a 12 Volt DC motor. The test results showed that the use of an aquaponic system with 40 netpots of pakcoy vegetables gave a significant reduction of ammonia in aquaponic plants of 4.94 ppm in one day. From the results of testing the entire system, it can be concluded that this automatic system can help optimize the process of freshwater aquaculture. © 2022 IEEE.

关键词： Water quality

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A New Neural Network Feature Importance Method: Application to Mobile Robots controllers Gain Tuning 17

A New Neural Network Feature Importance Method: Application ...

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

作者： Hill, Ashley Lucet, Eric Lenain, Roland CEA LIST Interact Robot Lab F-91191 Gif Sur Yvette France Univ Clermont Auvergne Inrae UR TSCF Ctr Clermont Ferrand F-63178 Aubiere France

ISBN: (纸本)9789897584428

This paper proposes a new approach for feature importance of neural networks and subsequently a methodology using the novel feature importance to determine useful sensor information in high performance controllers, using a trained neural network that predicts the quasi-optimal gain in real time. The neural network is trained using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm, in order to lower a given objective function. The important sensor information for robotic control are determined using the described methodology. Then a proposed improvement to the tested control law is given, and compared with the neural network's gain prediction method for real time gain tuning. As a results, crucial information about the importance of a given sensory information for robotic control is determined, and shown to improve the performance of existing controllers.

关键词： Machine Learning Neural Network robotics Mobile Robot control Theory Gain Tuning Adaptive control Explainable Artificial Intelligence

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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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Design Documentation Agreement Automated System with Approving Person Intelligent Support

Design Documentation Agreement Automated System with Approvi...

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international Russian Smart Industry conference (SmartIndustryCon)

作者： Viktoriya Latypova The Faculty of Informatics and Robotics Ufa University of Science and Technology Ufa Russia

The design documentation agreement procedure is one of the production process stages. The procedure is usually rather long because it demands the participation of a large group of staff, conducting the complex documentation control execution. During the agreement process errors in design documentation are identified and a review with relevant remarks to finalize it is formed, typically in manual mode. This operation is repeated until all remarks are finally eliminated. In the latter case, the design documentation agreement procedure ends. In existing research attention has been paid to automation and information support in different stages of the agreement procedure. But the issue of automatization of approving person review formation has not been given enough attention. A method of automated review formation, when agreeing on the design documentation, using text mining of approving person remarks and an automated system, implementing this method, is proposed to solve the problem. Approbation of the automated system was carried out in the agreement of design documentation on the example of design models of printed circuit boards of electronic devices for CNC machines for plasma metal cutting. The results of approbation show that the usage of an automated system allows to reduce the time of review preparation by approving persons. This in turn allows to decrease the time of the design documentation agreement process execution and the time of the manufacturing process in general.

关键词： Text mining Industries Manufacturing processes Printed circuits Metals Documentation Production

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