2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS)最新文献

Implementation of high resolution unipolar PWM inverter using Xilinx System Generator 利用赛灵思系统发生器实现高分辨率单极PWM逆变器

2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS) Pub Date : 2016-10-01 DOI: 10.1109/MAIS.2016.7761903

F. Mendoza-Mondragón, A. Espinosa-Calderón, A. Martinez-Hernandez, J. Rodríguez-Reséndiz

引用次数: 2

BLDC motor drive based on current shaping cell converter 基于电流整形单元变换器的无刷直流电机驱动

2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS) Pub Date : 2016-10-01 DOI: 10.1109/MAIS.2016.7761901

Alonso Jiménez-Garibay, J. Rodríguez-Reséndiz, J. Jáuregui-Correa

引用次数: 0

Vehicle windows control proportional to the speed, using raspberry and on board diagnostics port 车辆车窗控制与速度成正比，使用覆盆子和车载诊断端口

2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS) Pub Date : 2016-10-01 DOI: 10.1109/MAIS.2016.7761900

A. G. Blanco

引用次数: 1

Learning from demonstration with Gaussian processes 从高斯过程的演示中学习

2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS) Pub Date : 2016-10-01 DOI: 10.1109/MAIS.2016.7761899

D. Garcia-Sillas, E. Gorrostieta-Hurtado, Emilio Soto-Vargas, Guillermo Diaz-Delgado, Cristian Rodriguez Rivero

{"title":"Learning from demonstration with Gaussian processes","authors":"D. Garcia-Sillas, E. Gorrostieta-Hurtado, Emilio Soto-Vargas, Guillermo Diaz-Delgado, Cristian Rodriguez Rivero","doi":"10.1109/MAIS.2016.7761899","DOIUrl":"https://doi.org/10.1109/MAIS.2016.7761899","url":null,"abstract":"There is huge potential in the field of robotics for the application of machine learning methodologies, particularly in the case of learning by demonstration, which considerably reduces the time required to program robotic actions, and in addition, makes robotic movements more natural. Within machine learning domain supervised, unsupervised and reinforcement learning classifications can be found. Among these, the most widely used is supervised learning. This allows two learning tasks: classification and regression. The Gaussian process model is one of the methodologies used for regression. Through regression, a learning process can be performed, allowing to learn by demonstration from a given data set. In this article, the development of a learning method is presented, it is based on Gaussian process regression and intended to be applied in robotic platforms which require to learn quickly and incrementally, since the robots today maintain more contact with the environment and therefore with the human. That is why the Gaussian processes have the characteristics required to develop this type of control for robots. In this paper, a non-parametric regression model such Gaussian process is investigated, as well as how this can be applied to learning from demonstration framework.","PeriodicalId":137887,"journal":{"name":"2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114505855","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}

引用次数: 4

Finger movements classification from grasping spherical objects with surface electromyography using time domain based features 基于时域特征的表面肌电图手指抓球动作分类

2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS) Pub Date : 2016-10-01 DOI: 10.1109/MAIS.2016.7761904

G. A. Torres, V. Benitez

{"title":"Finger movements classification from grasping spherical objects with surface electromyography using time domain based features","authors":"G. A. Torres, V. Benitez","doi":"10.1109/MAIS.2016.7761904","DOIUrl":"https://doi.org/10.1109/MAIS.2016.7761904","url":null,"abstract":"In this paper the classification of fingers gestures that vary in specific mechanical positions is proposed, which consist in distinguish several finger positions with very low mechanical variation. A new approach is presented that is different to the state of the art methods for the classification of fingers movements that have traditionally, focused on very well distinguished gestures from each other. Myoelectric signals (MES) reflect the intention of the movement according to the diameter of the sphere sustained is the objective of the present study. Natural motions are collected by placing electrodes on five muscles on the forearm of six healthy subjects, while performing spherical fastenings. A time domain (TD) feature vector is given as inputs to a linear discriminant analysis (LDA) module. LDA is used as statistical pattern classifier. We show that there exist significant relationship between muscle signals and fingers positions. Therefore, it is possible to categorize each class of finger position, that is, TD feature based provide an effective representation for classification. LDA achieve the assignment of the membership of a MES collected to one fingers position class, which is defined by the diameter of sphere. These results will be useful for analysis of movement of the human hand to improve control of robotic prosthetic hand and man-machine interfaces.","PeriodicalId":137887,"journal":{"name":"2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134266380","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}

引用次数: 6

A speed performance comparative of field oriented control and scalar control for induction motors 感应电动机磁场定向控制与标量控制的速度性能比较

2016 IEEE Conference on Mechatronics, Adaptive and Intelligent Systems (MAIS) Pub Date : 2016-10-01 DOI: 10.1109/MAIS.2016.7761902

M. Martínez-Hernández, J. M. Gutiérrez-Villalobos, S. M. Malagon-Soldara, F. Mendoza-Mondragón, J. Rodríguez-Reséndiz

引用次数: 8