J. Mendoza-Vázquez, A. Z. Escudero-Uribe, E. Tlelo-Cuautle
The modeling and simulation of a mechanical elbow of 3 degrees of freedom, is introduced by highlighting the main features of the mechanism related to the design criteria. The mechanical elbow is used as a transhumeral prosthetic part, and it has been built as a parallel topology consisting of electric linear actuators and universal joints. The parallel mechanism has 4 legs: 3 made with electric linear actuators, and the fourth leg provides mechanical support for the whole structure and holds a DC motor that performs the action of gripping objects. Furthermore, this paper shows the inverse kinematics for the elbow by geometric methods, and the MatLab-simulation results show the workspace of the movement and the ability of the mechanical elbow to replicate the movements of a biological one.
{"title":"Modeling and Simulation of a Parallel Mechanical Elbow with 3 DOF","authors":"J. Mendoza-Vázquez, A. Z. Escudero-Uribe, E. Tlelo-Cuautle","doi":"10.1109/CERMA.2008.12","DOIUrl":"https://doi.org/10.1109/CERMA.2008.12","url":null,"abstract":"The modeling and simulation of a mechanical elbow of 3 degrees of freedom, is introduced by highlighting the main features of the mechanism related to the design criteria. The mechanical elbow is used as a transhumeral prosthetic part, and it has been built as a parallel topology consisting of electric linear actuators and universal joints. The parallel mechanism has 4 legs: 3 made with electric linear actuators, and the fourth leg provides mechanical support for the whole structure and holds a DC motor that performs the action of gripping objects. Furthermore, this paper shows the inverse kinematics for the elbow by geometric methods, and the MatLab-simulation results show the workspace of the movement and the ability of the mechanical elbow to replicate the movements of a biological one.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117315798","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}
This paper presents the design of a MESH network to provide services simultaneous of voice, video and data. The network architecture is constituted by two access points(APpsilas), two mobile wireless routers (WRpsilas), a mobile unit, a portable unit and a control center. The network was implemented at Instituto Politecnico Nacional (IPN), campus Zacatenco. We make different communications tests of voice, data and video with and without the network infrastructure to carry out a system evaluation. We also tested the network with different speeds reaching up to 100 km/h.
{"title":"Characterization of a Wireless MESH Network for Voice, Data and Video","authors":"S.L.G. Coronel, M. Mosqueda, M. S. Meraz","doi":"10.1109/CERMA.2008.48","DOIUrl":"https://doi.org/10.1109/CERMA.2008.48","url":null,"abstract":"This paper presents the design of a MESH network to provide services simultaneous of voice, video and data. The network architecture is constituted by two access points(APpsilas), two mobile wireless routers (WRpsilas), a mobile unit, a portable unit and a control center. The network was implemented at Instituto Politecnico Nacional (IPN), campus Zacatenco. We make different communications tests of voice, data and video with and without the network infrastructure to carry out a system evaluation. We also tested the network with different speeds reaching up to 100 km/h.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134380067","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}
Ignacio Lazaro Roche, G. Pineda, E. Espinosa, S. Zavala
This paper presents a frequency domain based methodology using Chebyshev polynomials of the first kind, the methodology can be used to make an analysis of time-varying linear systems in transient state. The method takes advantages of the operational properties available to most orthogonal series expression, i.e. integration, differentiation, product and coefficient matrices. The approach may be seen as an extension of phasor analysis commonly used for the analysis of linear time invariant electric networks to periodic networks. A high order time-varying system is presented and it is analyzed via the proposed methodology.
{"title":"Analysis of Time Varying Power System Loads via Chebyshev Polynomials","authors":"Ignacio Lazaro Roche, G. Pineda, E. Espinosa, S. Zavala","doi":"10.1109/CERMA.2008.10","DOIUrl":"https://doi.org/10.1109/CERMA.2008.10","url":null,"abstract":"This paper presents a frequency domain based methodology using Chebyshev polynomials of the first kind, the methodology can be used to make an analysis of time-varying linear systems in transient state. The method takes advantages of the operational properties available to most orthogonal series expression, i.e. integration, differentiation, product and coefficient matrices. The approach may be seen as an extension of phasor analysis commonly used for the analysis of linear time invariant electric networks to periodic networks. A high order time-varying system is presented and it is analyzed via the proposed methodology.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115597675","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}
This paper presents a novel approach to on-line, robot-motion planning for multiple 3D moving-objects interception. Using a polynomial interpolation technique. The proposed approach utilizes the time parametric function of one or more moving objects to generate the multiple 3D interception trajectory. This methodology is efficient for the slow-maneuvering objects with constant acceleration in industrial settings, like objects moving on a circular conveyor. The multiple 3D interception trajectory allows the end-effector of a robotic arm to be oriented along the objects trajectory to avoid impact. The implementation of the proposed technique is illustrated via a simulation example. It consists of the multiple 3D interception of two objects moving along a well-known sinusoidal trajectory in the three-dimensional space.
{"title":"Robot Trajectory Planning for Multiple 3D Moving Objects Interception: A Polynomial Interpolation Approach","authors":"J. Campos, J. Flores, C. P. Montufar","doi":"10.1109/CERMA.2008.87","DOIUrl":"https://doi.org/10.1109/CERMA.2008.87","url":null,"abstract":"This paper presents a novel approach to on-line, robot-motion planning for multiple 3D moving-objects interception. Using a polynomial interpolation technique. The proposed approach utilizes the time parametric function of one or more moving objects to generate the multiple 3D interception trajectory. This methodology is efficient for the slow-maneuvering objects with constant acceleration in industrial settings, like objects moving on a circular conveyor. The multiple 3D interception trajectory allows the end-effector of a robotic arm to be oriented along the objects trajectory to avoid impact. The implementation of the proposed technique is illustrated via a simulation example. It consists of the multiple 3D interception of two objects moving along a well-known sinusoidal trajectory in the three-dimensional space.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130786557","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}
Clustering techniques are broadly used in research are as where pattern recognition is needed, like in signal processing, automatic voice analysis, computer vision, and data mining. However, for each specific problem, the adequate technique must be selected in order to achieve better results. In this paper, a comparative analysis between the three mostly used clustering techniques (k-means, ISODATA, and the sequential clustering algorithm) is presented. The goal of the analysis is to compare the efficiency of each algorithm applied to numerical databases and images. The results of the application of the algorithms to a set of 25 images (natural and artificial) and 5 numerical databases are presented and discussed.
{"title":"Analysis of Clustering Algorithms for Image Segmentation and Numerical Databases","authors":"D. Galeana, H. Pacheco, A. Magadán","doi":"10.1109/CERMA.2008.103","DOIUrl":"https://doi.org/10.1109/CERMA.2008.103","url":null,"abstract":"Clustering techniques are broadly used in research are as where pattern recognition is needed, like in signal processing, automatic voice analysis, computer vision, and data mining. However, for each specific problem, the adequate technique must be selected in order to achieve better results. In this paper, a comparative analysis between the three mostly used clustering techniques (k-means, ISODATA, and the sequential clustering algorithm) is presented. The goal of the analysis is to compare the efficiency of each algorithm applied to numerical databases and images. The results of the application of the algorithms to a set of 25 images (natural and artificial) and 5 numerical databases are presented and discussed.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120968141","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}
The aim of this paper is to present a designed software platform for the processing of electrocardiographic (ECG) and breathing signals in order to study the correlation of respiration waveform time intervals with high frequency (HF) and low frequency (LF) powers of heart rate variability (HRV). The software was tested with signals from 5 minutes recordings, including respiration paces of 12, 9, and 6 breaths per minute. Wavelet based software was used to locate the R waves of an ECG signal, in order to obtain a tachogram used to calculate parameters of HRV. Special software was developed to process breathing signals to identify defined points of the respiration waveforms and to calculate their time intervals to study the correlation of these time intervals with HF and LF powers of HRV. These powers are traditionally associated with parasympathetic and sympathetic activity, respectively. The paper presents a description of the developed signal processing software and the obtained test results.
{"title":"Processing of ECG and Breathing Signals to Study the Correlation of Respiration Waveform Time Intervals with HF and LF Powers of Heart Rate Variability","authors":"E. Barrera, M.A. Fabian, H. Ruiz","doi":"10.1109/CERMA.2008.61","DOIUrl":"https://doi.org/10.1109/CERMA.2008.61","url":null,"abstract":"The aim of this paper is to present a designed software platform for the processing of electrocardiographic (ECG) and breathing signals in order to study the correlation of respiration waveform time intervals with high frequency (HF) and low frequency (LF) powers of heart rate variability (HRV). The software was tested with signals from 5 minutes recordings, including respiration paces of 12, 9, and 6 breaths per minute. Wavelet based software was used to locate the R waves of an ECG signal, in order to obtain a tachogram used to calculate parameters of HRV. Special software was developed to process breathing signals to identify defined points of the respiration waveforms and to calculate their time intervals to study the correlation of these time intervals with HF and LF powers of HRV. These powers are traditionally associated with parasympathetic and sympathetic activity, respectively. The paper presents a description of the developed signal processing software and the obtained test results.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116969881","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}
The present paper proposes a method to calculate a set of proposed initial values for the weight matrix and the bias vector of a neural network prior to training. The method described here applies for linear neural networks with one hidden layer, and a known proportional relationship between inputs and outputs. The algorithm and the calculations are intended to be simple, to facilitate automation in small processors The method normalizes values in a tri-level form, finds the relationships on the maximum and minimum values for all combinations of inputs and outputs, averages these results and builds the weight matrix and bias vector from these results. The end result is a set of initial values prior to training, intended to have a start point for training closer to the end result. Overall result is less training time.
{"title":"Method to Approximate Initial Values for Training Lineal Neural Networks","authors":"A. G. Blanco","doi":"10.1109/CERMA.2008.40","DOIUrl":"https://doi.org/10.1109/CERMA.2008.40","url":null,"abstract":"The present paper proposes a method to calculate a set of proposed initial values for the weight matrix and the bias vector of a neural network prior to training. The method described here applies for linear neural networks with one hidden layer, and a known proportional relationship between inputs and outputs. The algorithm and the calculations are intended to be simple, to facilitate automation in small processors The method normalizes values in a tri-level form, finds the relationships on the maximum and minimum values for all combinations of inputs and outputs, averages these results and builds the weight matrix and bias vector from these results. The end result is a set of initial values prior to training, intended to have a start point for training closer to the end result. Overall result is less training time.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128481725","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}
In this work a new method is proposed for the diagnosis of faults in electric power transmission systems based on neural modularity. This method performs the diagnosis through the assignation of a generic neural module for each type of element conforming the transmission system, whether it be line, bus or transformer. A total of three generic neural modules are designed, one for each type of element. These neural modules are grouped together in repetition according to the element to be diagnosed and taking into account its breakers and relays, both primary and back-up. The most important and novel aspect of this method is that only three neural modules are required, one for each type of element, and they can be called upon for the diagnosis as a function, the moment a change of state is detected in any of the breakers, primary or back-up, relating to the element under diagnosis.
{"title":"New Formulation through Artificial Neural Networks in the Diagnosis of Faults in Power Systems: A Modular Approach","authors":"A. Flores, E. Quiles, E. García, F. Morant","doi":"10.1109/CERMA.2008.79","DOIUrl":"https://doi.org/10.1109/CERMA.2008.79","url":null,"abstract":"In this work a new method is proposed for the diagnosis of faults in electric power transmission systems based on neural modularity. This method performs the diagnosis through the assignation of a generic neural module for each type of element conforming the transmission system, whether it be line, bus or transformer. A total of three generic neural modules are designed, one for each type of element. These neural modules are grouped together in repetition according to the element to be diagnosed and taking into account its breakers and relays, both primary and back-up. The most important and novel aspect of this method is that only three neural modules are required, one for each type of element, and they can be called upon for the diagnosis as a function, the moment a change of state is detected in any of the breakers, primary or back-up, relating to the element under diagnosis.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"2021 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127331388","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":"Intelligent Environment for Training of Power Systems Operators","authors":"G. Arroyo-Figueroa, Y. Hernández, L. Sucar","doi":"10.1007/11892960_113","DOIUrl":"https://doi.org/10.1007/11892960_113","url":null,"abstract":"","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121960656","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}
This paper presents the development of a basic goniometric system for control of movements in realtime of a mini humanoid robot. The mini humanoid is Hitecpsilas Robonova-1 with a total of 16 degrees of freedom. The first prototype only included the degrees in relation with the arm, elbow joint and one shoulder joint. The project is presented in six steps: general description of Robonova; kinematic model of ok human and android arm; mechanical structure; electronic configuration and software interface.
{"title":"Model and Implementation of Master-Slave Basic Goniometric System for Real Time Control of a Mini Humanoid Robot","authors":"J. Arias, L.E.S. Guzman, M. M. Arteche","doi":"10.1109/cerma.2008.100","DOIUrl":"https://doi.org/10.1109/cerma.2008.100","url":null,"abstract":"This paper presents the development of a basic goniometric system for control of movements in realtime of a mini humanoid robot. The mini humanoid is Hitecpsilas Robonova-1 with a total of 16 degrees of freedom. The first prototype only included the degrees in relation with the arm, elbow joint and one shoulder joint. The project is presented in six steps: general description of Robonova; kinematic model of ok human and android arm; mechanical structure; electronic configuration and software interface.","PeriodicalId":126172,"journal":{"name":"2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08)","volume":"384 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122623435","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}
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