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International Joint Conference on Neural Networks (IJCNN)

作者： Matheus Henrique Dal Molin Ribeiro Ramon Gomes da Silva Cristiane Canton Naylene Fraccanabbia Viviana Cocco Mariani Leandro dos Santos Coelho Industrial & Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil Department of Mathematics Federal Technological University of Parana (UTFPR) Pato Branco Parana Brazil Pato Branco University Center (UNIDEP) Pato Branco Parana Brazil Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil Department of Electrical Engineering Federal University of Parana (UFPR) Curitiba Parana Brazil

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

The development of accurate models to forecast electricity energy prices is a challenge due to the number of factors which can affect this commodity. In this paper, a hybrid multi-stage approach is proposed to forecast multi-stepahead (one, two and three-month-ahead) Brazilian commercial and residential electricity energy prices. The proposed data analysis combines the pre-processing named complementary ensemble empirical mode decomposition (CEEMD) in the first stage coupled with the coyote optimization algorithm (COA) to define the CEEMD's hyperparameters, aiming to deal with time series non-linearities and enhance the model's performance. On the next stage, four machine learning models named extreme learning machine, Gaussian process, gradient boosting machine, and relevance vector machine are employed to train and predict the CEEMD's components. Finally, in the final stage, the results of the previous step are directly integrated to compose a heterogeneous ensemble learning of components to obtain the final forecasts. In this case, a grid of models is obtained. The best model is one that has better generalization out-of-sample. Through developed comparisons, results showed that combining COA-CEEMD with a heterogeneous ensemble learning can develop accurate forecasts. The modeling developed in this paper is promising and can support decision making in electricity energy price forecasting.

关键词： Predictive models Biological system modeling Forecasting Data models Optimization Empirical mode decomposition

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Multi-robot exploration using Dynamic Fuzzy Cognitive Maps and Ant Colony Optimization

Multi-robot exploration using Dynamic Fuzzy Cognitive Maps a...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Márcio Mendonça Rodrigo H. C. Palácios Elpiniki I. Papageorgiou Lucas Botoni de Souza Eletric Engineering Academic Department (DAELE) Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil Computer Engineering Academic Department (DACOM) Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil Faculty of Technology University of Thessaly Larissa Greece Mechanical Engineering Graduate Program (PPGEM) Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

An application field of Multi-Robot Systems (MRS) is within victim rescue operations. The main challenge faced by disaster rescue teams is response time. The chances of finding survivors decrease significantly over time and dramatically decrease after 48 hours. In this context, the motivation of this work is to present an MRS inspired by the concepts of swarm robotics to rescue victims in unknown environments. In this case, the robots are unaware of the search area boundaries and obstacles, knowing the number of victims to be rescued as a stopping criterion for the simulations made in Matlab®. Therefore, three approaches inheriting the main aspects of fuzzy logic are used based on previous works: a fuzzy logic controller (FLC), a dynamic fuzzy cognitive map (DFCM) controller, and a DFCM inspired by the ant colony optimization metaheuristic (DFCM- ACO). The proposed task simulates real life disaster rescue operations, or even humans lost in unfamiliar environments such as forests. The simulations were performed in three environments in order to test the overall robustness against unpredictable situations, autonomy, explored area and processing time for both approaches using a subsumption-based architecture. In general, the results suggest that the DFCM-based MRS approaches are able to complete the tasks consuming less processing time, with robots travelling shorter distances to explore a similar environment to the FLC approach and with the DFCM-ACO presenting balanced results between the other techniques. Finally, future works are outlined.

关键词： Robot kinematics Robot sensing systems Task analysis Ant colony optimization Multi-robot systems

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Digital game-based learning in a robotics course

Digital game-based learning in a robotics course

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Márcio Mendonça Konstantinos Papageorgiou Diene Eire de Mello Elpiniki I. Papageorgiou José Augusto Fabri Lucas Botoni de Souza Rodrigo Henrique Cunha Palácios Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil Departament of Computer Science & Telecommunications University of Thessaly Lamia Greece Departamento de Educação Universidade EStadual de Londrina Londrina PR Brazil Faculty of Technology University of Thessaly Geopolis Campus Larissa Greece Mechanical Engineering Graduate Program (PPGEM) Universidade Tecnológica Federal do Paraná Cornélio Procópio Brazil

ISBN: (数字)9781665422284

ISBN: (纸本)9781665422291

This paper deals with two experiments regarding games developed in Scratch in the course of robotics at the Universidade Tecnológica Federal do Paraná campus Cornélio Procópio (UTFPR-CP) to assist in the learning of an autonomous vehicle using a similar classic game of war tanks, existing since the 80s for the Atari 2600. In the first experiment, applied to the class 2019/2, a student (player) controls a tank using the keyboard in a battle against another autonomous tank. In this game, certain fundamentals are presented, such as pose (position x, y and the angle formed in relation to the x axis), basic notions about controlled and autonomous robots, hierarchy of actions, modeling using state machine. These concepts were extracted through a questionnaire filled out by the students after the end of the games. The second experiment, applied to the 2020/1 class, was based on a game inspired by the classic Pong, using though more degrees of freedom (DOF). In this case, the player must operate the keyboard to reach a ball through a robotic arm with two rotating joints. Moreover, concepts such as workspace (in two dimensions), multiple solutions, inverse and direct kinematics were introduced. Delivery rates were 90% and 80% regarding the first and the second experiment, respectively. Finally, despite the limited number of these experiments, it is believed that the objective of using more modern didactic tools to teach important concepts in the discipline of robotics has been achieved. Thus, students perceived more easily the basic concepts of robotics presented in the experiments than ever before.

关键词： Three-dimensional displays Keyboards Prototypes Games Tools Manipulators Robots

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Semi-Unknown Environments Exploration Inspired by Swarm Robotics using Fuzzy Cognitive Maps

Semi-Unknown Environments Exploration Inspired by Swarm Robo...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Márcio Mendonça Henrique Seiti Kondo Lucas Botoni de Souza Rodrigo Henrique C. Palácios João Paulo Lima Silva de Almeida Electrical Academic Department (DAELE) Federal University of Technology -Paraná (UTFPR) Cornélio Procópio Brazil Mechanical Engineering Graduate Program (PPGEM) Federal University of Technology -Paraná (UTFPR) Cornélio Procópio Brazil Computer Academic Department (DACOM) Federal University of Technology -Paraná (UTFPR) Cornélio Procópio Brazil Federal Institute of Paraná Jacarezinho Brazil

This paper aims to present a fuzzy cognitive map (FCM) controller on multiple autonomous mobile robots (multirobot system) in order to complete a foraging task in semiunknown environments, and to compare the FCM results with a fuzzy logic controller (FLC). In this work, the limits of the searching area are known. However, everything within it (goals, obstacles and position of other robots during navigation) is unknown. The foraging task simulates a real-life application of robots on rescue missions, where the main objective is rescuing the victims of a tragedy, or lost in a forest, or even victims of a major accident in an industry. Although it is a simulated environment, we tested the autonomy and cooperation among all robots for this kind of operation in different simulated scenarios. We used a reactive (real-time) architecture to enhance the robots' global robustness on dealing with unpredictable situations. The results imply that the FCM approach presented, in general, less simulation processing time and distance traveled, without significant prejudice in the explored area. In this way, we expect to collaborate and serve as inspiration for future works on this research area.

关键词： Robot kinematics Robot sensing systems Fuzzy cognitive maps Task analysis Service robots

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Electromagnetic Optimization Based on Gaussian Crow Search Approach

Electromagnetic Optimization Based on Gaussian Crow Search A...

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2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2018

作者： Dos Santos Coelho, Leandro Klein, Carlos Eduardo Mariani, Viviana Cocco Do Nascimento, Carlos Augusto Richter Askarzadeh, Alireza PUCPR Industrial and Systems Eng. Graduate Program PPGEPS Federal University of Parana UFPR Department of Electrical Engineering DEE/PPGEE Pontifical Catholic University of Parana Curitiba PR Brazil PUCPR Mechanical Engineering Graduate Program PPGEM Curitiba Pontifical Catholic University of Parana PR Brazil Department of Energy Management and Optimization Institute of Science and High Technology and Environmental Sciences Graduate University of Advanced Technology Kerman Iran

ISBN: (纸本)9781538649411

Metaheuristic algorithms have provided efficient tools to designers by which it became possible to determine the optimum solutions of optimization problems encountered in several fields such as engineering, finance and computation. Generally metaheuristics are based on metaphors that are taken from nature or some other processes. Recently, an optimization metaheuristic paradigm based on the social behavior of the crows, called crow search algorithm (CSA), has been proposed. The idea of CSA is motivated from the storing process of the excess food in hiding places then restoring it in the necessary time. The CSA has many favorable characteristics, such as ease of implementation, the need to adjust only a few parameters, a favorable balance between search diversification and intensification, and fast convergence and high sensitivity. However, to enhance the performance of the standard CSA approach, this paper proposes to tune the control parameters using population diversity information and normal (Gaussian) probability distribution function. Loney's solenoid benchmark and circular antenna array design problems are used to evaluate the effectiveness of the conventional CSA and the proposed variant. Simulation results and comparisons with the CSA demonstrated that the performance of the proposed MCSA approach is promising in electromagnetics optimization. © 2018 IEEE.

关键词： Optimization

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A Conceptual Model of a Stereo Vision System to Aid a Teleoperated Robot in Pruning Vegetation Close to Overhead Urban Power Lines

A Conceptual Model of a Stereo Vision System to Aid a Teleop...

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2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2018

作者： Filho, Jose Francisco Bianchi Siebert, Luciano Cavalcante Mariani, Viviana Cocco Dos Santos Coelho, Leandro Electrical Engineering Department Federal University of Parana Power System Division Lactec Institutes Curitiba Brazil Mechanical Eng. Graduate Program - PPGEM And Federal University of Parana - UFPR Department of Electrical Engineering - DEE Pontifical Catholic University of Parana - PUCPR Uritiba PR Brazil

ISBN: (纸本)9781538649411

Detection of overhead urban lines is a primal information to ensure that a telerobotic pruning system will perform its task in a safe manner. In this context, this paper proposes a conceptual model of a computer vision system capable of identifying overhead urban lines and its three dimensional positioning by reviewing sensing technologies, applications of stereo vision with telerobotics and proposing a conceptual model to perform such task. © 2018 IEEE.

关键词： Maintenance

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Erratum to: Frictional and wear performance of hard coatings during machining of superduplex stainless steel

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The International Journal of Advanced Manufacturing Technology 2017年第1期92卷 433-433页

作者： de Paiva, José M. F. Torres, Ricardo D. Amorim, Fred L. Covelli, Danielle Tauhiduzzaman, Mohammed Veldhuis, Stephen Dosbaeva, Goulnara Fox-Rabinovich, German Mechanical Engineering Department Centro Universitário Católica SC Joinville Brazil Mechanical Engineering Graduate Program-PPGEM Pontifícia Universidade Católica do Paraná-PUCPR Curitiba Brazil Biointerfaces Institute McMaster University Hamilton Canada Department of Mechanical Engineering McMaster University Hamilton Canada

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Multi-objective symbiotic search algorithm approaches for electromagnetic optimization

Multi-objective symbiotic search algorithm approaches for el...

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IEEE Conference on Electromagnetic Field Computation

作者： Helon Vicente Hultmann Ayala Carlos Eduardo Klein Viviana Cocco Mariani Leandro dos Santos Coelho Pontificia Universidade Catolica do Parana Curitiba PR BR Pontifical Catholic University of Parana (PUCPR) Industrial and Systems Engineering Graduate Program (PPGEPS) Curitiba PR Brazil Pontifical Catholic University of Parana (PUCPR) Mechanical Engineering Graduate Program (PPGEM) Curitiba PR Brazil Department of Electrical Engineering Federal University of Parana Curitiba PR Brazil

ISBN: (纸本)9781509010332

Optimization metaheuristics are a powerful way to deal with many electromagnetic optimization problems. Recently, the symbiotic organisms search (SOS) algorithm was proposed to solve single-objective optimization problems. SOS mimics the symbiotic relationship among the living beings. In order to extend the classical mono-objective SOS algorithm approach, this paper proposes a new multi-objective SOS (MOSOS) and an improved IMOSOS. Results on a multi-objective constrained brushless direct current (DC) motor design show that the MOSOS and IMOSOS present promising performance.

关键词： Optimization Brushless DC motors Symbiosis Algorithm design and analysis Organisms

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Multiobjective cross entropy for electromagnetic optimization

Multiobjective cross entropy for electromagnetic optimizatio...

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IEEE Conference on Electromagnetic Field Computation

作者： Teodora Cardoso Bora Viviana Cocco Mariani Leandro dos Santos Coelho Piergiorgio Alotto Department of Electrical Engineering Federal University of Parana Curitiba PR Brazil Pontifical Catholic University of Parna (PUCPR) Mechanical Engineering Graduate-Program (PPGEM) Curitiba PR Brazil Pontifical Catholic University of Parana (PUCPR) Industrial and Systems Engineering Graduate Program (PPGEPS) Curitiba PR Brazil Dipartimento di Ingegneria Industriale Università di Padova Padua Italy

ISBN: (纸本)9781509010332

The Cross-Entropy (CE) method has been designed to solve rare event simulation problems and later extended to single-objective optimization problems. In this paper, we propose a novel CE approach for multi-objective optimization and applied it to the multiobjective version of TEAM (Testing Electromagnetic Analysis Method) workshop problem 22, demonstrating promising results in terms of performance.

关键词： Optimization Conferences Monte Carlo methods Entropy Testing Electromagnetic analysis Histograms

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A numerical analysis on forming limits during spiral and concentric single point incremental forming

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IOP Conference Series: Materials Science and engineering 2017年第1期164卷

作者： M L Gipiela V Amauri C Nikhare P V P Marcondes Faculty of Technology - SENAI - CIC National Service for Industrial Apprenticeship in Paraná 298 Senador Accioly Filho Street Curitiba 81310-000 Brazil Mechanical Engineering The Pennsylvania State University Erie PA-16563 USA Graduate Program in Mechanical Engineering - PPGEM Federal University of Paraná 210 Coronel Francisco H. dos Santos Avenue Curitiba 81531-990 Brazil

Sheet metal forming is one of the major manufacturing industries, which are building numerous parts for aerospace, automotive and medical industry. Due to the high demand in vehicle industry and environmental regulations on less fuel consumption on other hand, researchers are innovating new methods to build these parts with energy efficient sheet metal forming process instead of conventionally used punch and die to form the parts to achieve the lightweight parts. One of the most recognized manufacturing process in this category is Single Point Incremental Forming (SPIF). SPIF is the die-less sheet metal forming process in which the single point tool incrementally forces any single point of sheet metal at any process time to plastic deformation zone. In the present work, finite element method (FEM) is applied to analyze the forming limits of high strength low alloy steel formed by single point incremental forming (SPIF) by spiral and concentric tool path. SPIF numerical simulations were model with 24 and 29 mm cup depth, and the results were compare with Nakajima results obtained by experiments and FEM. It was found that the cup formed with Nakajima tool failed at 24 mm while cups formed by SPIF surpassed the limit for both depths with both profiles. It was also notice that the strain achieved in concentric profile are lower than that in spiral profile.

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